Mechanical properties of Indonesian organic-rich shales from the Central Sumatra and North Sumatra Basin, and comparison with US shales

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Here we report the laboratory-based mechanical properties of Indonesian shale potentials located within Tertiary basins in active margin settings. Samples from surface-outcrops of lacustrine sediments in the Central Sumatra Basin (CSB) and subsurface-cores of marine deposits in the North Sumatra Basin (NSB) were examined in a series of experiments for their mechanical properties including rock strength, elastic properties, and creep compliance. Results show that the Indonesian shales studied here are generally more compliant than Mesozoic/Paleozoic U.S. shales reported in the literature. Within the context of a binary mixture model (stiff and soft components) used to explain shale elastic properties, these differences in mechanical properties imply that the soft and stiff end-members are more compliant in Indonesian shales. We interpret these differences as the difference in mechanical maturity, which reflects the degree to which mechanical properties have evolved due diagenesis. CSB and NSB samples are considered to be early mature, mechanically, compared to the mechanically mature U.S. shales. Particularly, the Baong Formation samples from the NSB studied here come from a hard-overpressured interval and are mechanically immature, despite their moderate thermal maturity based on vitrinite reflectance. Laboratory results also show no significant differences in mechanical properties between shales deposited in lacustrine (CSB samples) and marine (NSB samples) environments. Indonesian shale elastic modulus creep compliance strength anisotropy mechanical maturity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 Figure 15 Figure 16 Figure 17 Highlights Laboratory-measured mechanical properties (rock strength, elastic properties, creep compliance) of Indonesian shales located within Tertiary basins in an active margin setting. Indonesian shales are generally more compliant than Mesozoic/Paleozoic U.S. shales reported in the literature despite similar porosity, thermal maturity, and burial depth. The difference is attributed to the difference in mechanical maturity, the extent to which mechanical properties have evolved due to diagenesis, mainly influenced by the age of the shales. 1 Introduction Organic-rich shales exhibit a wide range of organic and mineral compositions, fabric anisotropy, and organic maturity. Studying how this leads to varying petrophysical properties and affect reservoir mechanical properties which are critical information in optimizing reservoir development and production. For instance, elastic properties control the propagation of seismic waves, which is important in locating reservoirs and obtaining early information on reservoir properties. Brittle strength is essential in planning and managing parameters necessary for stable drilling and reservoir stimulation (Zoback, 2007 ). Elastic and ductile properties are necessary to obtain prior estimates of the stress distribution inside reservoirs (Eaton, 1969 ; Thiercelin and Plumb, 1994 ; Blanton and Olson. 1999; Sone and Zoback, 2014b ). Laboratory studies of organic-rich shales have shown that the volume of soft components (i.e., clay minerals and organic matters) and their distribution in the rock texture strongly influence the mechanical properties (Vernik and Nur, 1992 ; Hornby et al., 1994 ; Johnston and Christensen, 1995 ; Vernik and Liu, 1997 ; Sondergeld et al., 2000 ; Sondergeld et al., 2010 ; Sondergeld and Rai, 2011 ; Vernik and Milovac, 2011 ). Elastic stiffness of shales are strongly correlated to the soft component volume as well as deformational properties, including brittle strengths and ductile constitutive parameters (e.g., Sone and Zoback, 2013a , b ). The orientation distribution of clay minerals also determines the degree of mechanical anisotropy (e.g., Sone and Zoback, 2013b ; Vernik and Anantharamu, 2020 ). In addition, the use of nanoindentation in testing shale properties shows that the maturity of organic matter affects the elastic properties of organic-rich shales (Zargari et al., 2016 ; Abedi et al., 2016 ; Liu et al., 2018 ). Recent studies of producing shale reservoirs suggest that the creep behavior might lead to the closure of conductive fractures and lower reservoir productivity (e.g., Wen et al., 2007 ; Alramahi and Sundberg, 2012 ; Zhang et al., 2015 ; Li et al., 2017 ). Moreover, Sone and Zoback ( 2014a ), for instance, use creep constitutive parameters to infer the stress heterogeneities in the reservoir utilizing the viscous relaxation model. In various U.S. shale gas reservoirs, this model has proven to successfully estimate the intra-reservoir stress variation through observations of microseismicity during hydraulic fracturing (e.g., Yang et al., 2015 ; Xu et al., 2017 ; Ma and Zoback, 2020 ). Indonesian organic-rich shale potentials lie in relatively young active tectonic settings, different from the U.S. shale reservoirs located in older stable intraplate regions. The difference in age and tectonic setting may result in differences in the mechanical properties between Indonesian and U.S. shales. Therefore, a thorough mechanical characterization of the Indonesian organic-rich shales becomes a fundamental requirement in evaluating the resource potential of shales in Indonesia. Our study aims to characterize, through laboratory testing, the mechanical properties of potential organic-rich shales from two prolific basins in Indonesia. We will begin with a brief description of the geology of the sample location, followed by a description of the samples and laboratory procedures. The laboratory results presented include brittle properties in terms of rock strength, elastic property in the form of Young’s modulus and Poisson’s ratio, creep compliance, as well as power-law constitutive parameters that represent creep properties. Based on those laboratory results, several points were then discussed, including the theoretical bounds of Young’s modulus, the mechanical maturity of Indonesian shales, and the influences of the depositional environment of shale on the mechanical properties. 2 Geology of Sampling Locations The shale samples used in this study come from the Sumatra Island, located in the westernmost part of the Indonesian archipelago. The island has experienced a complex tectonic and depositional history. Based on its stratigraphic record, the oldest rocks found in the Sumatra Island are of the Devonian Period (~ 360–420 Ma) (Barber et al., 2005 ). Tectonically, the current Sumatra Island represents an active convergent setting, with an oblique subduction system at the southwest. The subduction of the Indo-Australian Plate to the north beneath the Sunda Plate has occurred since the middle Miocene age, with current convergence rate of 6.8 cm/year (Schluter et al., 2002). The subduction divides the physiography of Sumatra Island into several zones, from the southwest to the northeast, respectively: accretionary prisms, fore-arc, volcanic-arc, and back-arc zones. In addition to physiography, this oblique compression also creates a fault zone along Sumatra Island known as Semangko dextral strike-slip fault systems, mainly observed around the volcanic-arc area. Behind the volcanic-arc area, three main hydrocarbon-producing basins are located at the current back-arc location from the northwest to the southeast, known as the North, Central, and South Sumatra Basins (Fig. 1 a). In terms of tectonostratigraphic evolution, the three Sumatran Basins, as well as the Tertiary basins throughout SE Asia, share many characteristics (Doust and Noble, 2008 ). Their geological history evolved from early Tertiary synrift to late Tertiary postrift (Fig. 1 b). The early synrift period corresponds to the half-graben basin formation, followed by waning subsidence and amalgamation of individual graben, forming extensive lowlands in their late synrift period. The early postrift period corresponds to the marine transgression covering the synrift structure topography and tectonic quiescence. This was followed by regressive delta formation as a result of inversion and folding, which marked the late postrift period. In the North Sumatra Basin, the early synrift deposits were recorded as coarse-grain conglomerates filling the graben and bioclastic limestone on the adjacent high topography (Doust and Noble, 2008 ). Thick, deep marine mudstone deposits represent the late synrift deposits, which also act as the primary source rock in the basin. The sediment of the early postrift period comprises deep marine shale, carbonate buildup on the structural high, and sandy facies in the southern part of the basin. The late postrift regressive sequence started with argillaceous deposits with turbidite sand insert, followed by shallow water sands, silts, and shales. Deep marine deposits continue in the northwestern part, while regressive deltaic sands are deposited in the southeastern part of the basin. The Central Sumatra Basin, even showing similar tectonostratigraphic evolution, shows a slightly different depositional environment with only minor carbonate facies in its overall sediment sequence (Doust and Noble, 2008 ). The early synrift deposits in this basin comprised alluvial, lacustrine, and fluvial-deltaic deposits. This sequence was followed by the late synrift transgression, starting with fluvial deposits and then overlain by shallow marine sands and argillaceous facies. The distal marine sand and shale facies and maximum transgression shale and silt facies record the early postrift period. The later deposits, late postrift sediment, include marine sands and shales in the northwest and regressive delta and alluvial sediment deposits in the southeast of the basin. To characterize the mechanical properties of Indonesian organic-rich shales, this study collected samples from surface outcrops and subsurface cores of a tertiary source rock formation in Sumatra. The outcrop samples (the location is marked with star symbols in Fig. 1 a) come from the lacustrine environment deposits of the Central Sumatra Basin (CSB), while the core samples are marine shale deposits from the North Sumatra Basin (NSB). The position of the samples in the stratigraphic section is marked with star symbols in Fig. 1 b. 2.1 Surface-outcrop samples We took the lacustrine shale samples of the Central Sumatra Basin (CSB) from a coal quarry in the Kiliran Jao area and outcrops near the Sumatran highway in the Ombilin (Sawah Lunto) area (Fig. 2 ), both in West Sumatra Province administration area. Based on the sample characteristics and their location relative to the geological map of the area (Silitonga and Kastowo, 1995 ), both samples are Oligocene in age. The quarry samples belong to the Kiliran Jao/Pematang Formation of the Kiliran Jao Sub-basin (e.g., Iqbal et al., 2014 ; Sunardi, 2015 ; Widayat et al., 2016 ) and the Sumatran highway samples belong to the Sangkarewang Formation of the Ombilin Sub-basin (e.g., Koesoemadinata and Matasak, 1981 ). We classify samples of the Kiliran Jao Formation based on their lithofacies into mudstone (MDS), massive mudstone (MAS), papery laminated shale (PAP; Widayat et al., 2016 ), sandy mudstone (SDM), and sandstone (SST). Meanwhile, for the Sangkarewang Formation, we refer to them as SKR-1 and SKR-2 based on their location. Considering the composition, sedimentary structure, and fossil content (Sunardi, 2015 ; Koesoemadinata and Matasak, 1981 ), these two shale deposits can be broadly classified as fluvial-lacustrine facies association deposited in an overfilled lake basin (see classification by Carroll and Bohacs, 1999 ). 2.2 Subsurface-core samples The subsurface samples used in this study come from three conventional cores recovered in a well drilled in the North Sumatra Basin (NSB), referred to as BAO1, BAO2, and BLM samples. While detailed location and depth information are proprietary, BAO1 and BAO2 samples belong to the lower Baong Formation, while BLM come from the Belumai Formation (Pertamina, 2017 ). Baong formation deposited in a marine environment of the Middle-Late Miocene transgression condition. Its lithology is dominated by a thick shale layer with sandstone turbidite series of a fan lobe in the middle. Apart from its potential as a source rock, the Baong Formation is well-known as a formation that has undergone disequilibrium compaction (Syaiful et al., 2020 ) and hydrocarbon generation that led to its current hard-overpressured state. Belumai Formation, on the other hand, represents a minor source-rock potential with no overpressures. The formation represents an older age (Early Miocene) deep marine environment, where its lithology can broadly be divided into two sections. The upper section consists of an intercalation between shale and clastic limestone with calcareous sandstone, while the lower section is dominated by non-calcareous shale. The BLM samples studied here belong to the bottom-most of the upper Belumai Formation. 3 Material and Methods 3.1 Sample characterization We categorized the CSB shale samples from the Kiliran Jao outcrop according to their lithofacies. On the other hand, due to limited lithofacies variation at the outcrop, we named the Ombilin outcrop samples according to their location. Moreover, the naming for core samples from NSB referred to their depth and geological formation. We determine the mineralogical composition of the samples using powder X-Ray Diffraction (XRD) analysis, and the organic content (total organic carbon – TOC) and maturity through pyrolysis analysis. These analyses were conducted either on specimens coming from the same outcrop block samples and nearby conventional-core plugs or sidewall-core (SWC) in the case of subsurface samples. Drill cuttings were used for the XRD and pyrolysis analyses when nearby core materials were unavailable. The weight percent of minerals obtained from the analyses were converted into volumetric percentages using the empirical relation between organic material density and vitrinite reflectance (Alfred and Vernik, 2012 ; Vernik, 2016 ). We categorized the mineral fractions into QFP, carbonates, and clay components. The QFP represent stiff granular components consisting of mainly quartz, feldspar, and pyrite. The carbonates group consists of calcite, dolomite, and siderite. The clays are in the form of illite-smectite, illite, kaolinite, and chlorite. The volume fractions of the minerals and organic material are summarized in Table 1 and plotted in Fig. 3 . The volumetric percentages of QFP, carbonate, and clay from the analyzed samples ranged from 11–57%, 5–74%, and 8–52%, respectively, and the volumetric percentage of organic contents and their maturity ranged from 2–23% and 0.3–1.3% Ro, respectively. Considering that clays and organic matters have relatively similar compliant mechanical properties, different from the stiffer QFP and carbonates, we refer to these two components as soft components following Sone and Zoback ( 2013a ). Table 1 Summary of mineral compositions (vol%), organic (TOC) contents (vol% and wt%), and maturities (%Ro) Geological Formation Sample Code QFP [vol%] Carbonate [vol%] Clay [vol%] TOC [vol% (wt%)] Clay + TOC [vol %] Maturity [%Ro] Central Sumatra Basin Kiliran Jao (Pematang) MDS 56.6 12.8 23.2 7.4 (3.0) 30.6 0.39 MAS 14.0 62.4 12.0 11.7 (4.6) 23.6 0.30 PAP 15.0 45.9 16.3 22.8 (9.6) 39.1 0.29 SDM 18.2 61.5 12.3 8.0 (3.1) 20.3 0.32 SST 28.0 56.6 10.9 4.6 (1.8) 15.4 0.37 Sangka-rewang SKR1 11.1 74.5 7.9 6.5 (2.5) 14.4 0.30 SKR2 41.5 14.9 35.9 7.6 (3.3) 43.6 0.62 North Sumatra Basin Baong BAO1-1 45.1 8.1 43.7 3.1 (1.4) 46.8 0.77 BAO1-2 45.1 8.1 43.7 3.1 (1.4) 46.8 0.77 BAO2-1 47.7 4.6 44.8 2.8 (1.3) 47.7 0.86 BAO2-2 38.4 6.8 52.0 2.9 (1.3) 54.9 0.86 Belumai BLM-1 45.2 33.1 20.0 1.8 (0.9) 21.7 1.26 BLM-2 44.5 31.6 21.8 2.2 (1.1) 23.9 1.26 Owing to the difficulty in measuring porosity of shales by methods requiring fluid infiltration into the pore spaces (e.g., Sun et al., 2016 ), we estimated the porosity by comparing the bulk density of the room-dry samples with the average mineral densities determined from the composition and individual mineral density. Based on the estimation, the porosity of shale samples used in this study ranged from 4–31%. Figure 4 a shows the relationship between the estimated porosity and bulk density with the dashed lines representing grain densities of 2.4, 2.5, 2.6, 2.7, and 2.8 g/cm 3 . The low grain density of the PAP samples reflect the high TOC (23 vol%) of the PAP shales, whereas NSB (BAO1, BAO2, and BLM) samples with a TOC ≤ 3 vol% has the highest grain density. We also see an overall increase in porosity with soft-component content (Fig. 4 b), consistent with observations from U.S. shales (Sone and Zoback, 2013a ) that highlights the porosity residing within the aggregates of platy clay minerals and within the internal structures of porous organic matters. However, a comparison between the Indonesian and the U.S. shales shows that the Indonesian shales have higher porosities for a given soft-component content than U.S. shales, which are older in geological age. These data may suggest that geological age, and thus the associated duration of diagenesis, either affects the porosity within the soft components or there are other sources of porosity in the younger Indonesian shale samples. 3.2 Microscopic observation Figure 5 shows the microstructure of representative samples used in the experiments observed under the optical microscope with cross-polarized light. In general, thin section observations show that the shale samples are composed of silt-size fragments within a very fine-grained matrix whose grains are unresolvable in the optical microscope. Some samples show a homogeneous texture of clay, carbonate, or quartz matrices, such as MAS and SKR1 while other samples show heterogeneous grain sizes as seen in MDS, SDM, SKR2, BAO1, and BLM. The SST sample contain the coarsest grains consisting of very fine sands. In terms of texture, some shale samples exhibit fabric anisotropy, such as PAP, SKR2, BAO1, BAO2, and BLM. This fabric anisotropy is most evident in PAP samples, mainly due to the alignment of its lenticular calcareous mineral aggregates and the preferred orientation of the organic matter. The elongated organic materials also define fabric anisotropy in SKR2. However, the fabric anisotropy is different in BAO1 and BAO2, which has a relatively massive matrix texture, but the bedding-parallel cracks define their anisotropy. SKR2 and BLM samples also show the existence of bedding-parallel cracks, which dictate their anisotropy, but with intensity lower than BAO1 and BAO2. In addition, BLM contains calcareous fossils whose variability in abundance between laminae determines a weak layered fabric. 3.3 Laboratory procedures We start the laboratory procedures by preparing cylindrical samples of 2.54 cm diameter and 5.08 cm length whose axes are either parallel or perpendicular to the bedding plane, referred to as horizontal and vertical samples, respectively. While the sample diameter is less than recommended by the ISRM suggested methods (ISRM, 1983 ), we do not expect this to influence the results because the samples were homogenous due to their fine grain size. The samples were drilled using kerosine as the cooling fluid considering the reactivity of the clay minerals within the shale samples. Then the ends were cut in a precision saw using a low oil content cutting fluid. The cylindrical plugs were dried overnight at 70° C using a vacuum oven to remove any fluid remaining in the pore space that may cause poroelastic pressure buildup during the experiments. A pair of horizontal and vertical samples for all CSB outcrop and NSB subsurface samples were prepared to characterize the anisotropy in elastic and deformational properties. We conducted experiments in a triaxial apparatus equipped with independent servo-controls for the confining pressure and axial load. The deformation of the CSB samples were measured using a pair of 2-element cross-stacked strain gauges attached to the cylindrical surface separated by 90° in the horizontal cross-section. On the other hand, the deformation of the NSB samples were measured using a pair of the linear variable differential transformer (LVDT) in the axial direction and a pair of strain-gauge-based spring-loaded displacement transducers in the two lateral directions perpendicular to each other (Fig. 6 ). Multiple steps of confining pressure (P c ) and axial differential stress (P diff ) were applied to measure deformation under hydrostatic and triaxial stress conditions, respectively (Fig. 7 ). After each stress step, the stress was maintained constant for 3 hours to observe the creep deformation at each stress state. The stress was then partially unloaded and reloaded before moving to the next stage to obtain elastic constants. After the last creep stage, the sample was loaded in the axial direction under constant confining stress until the rock reached failure. At failure, the peak axial stress value (P axial = P c + P diff ) represents the brittle strength. Following the failure, further loading continued until the differential stress dropped and reached a constant value representing the residual strength, or the sliding frictional strength. At the final stage, before removing all applied stress, the differential stress was unloaded and reloaded again to re-slide the failure planes and confirm the residual strength. We performed most of the experiments at a maximum P c of 30 MPa, comparable to the effective vertical stress at 2 km depth under hydrostatic pore pressure conditions, in order to facilitate comparison of mechanical properties between all shale samples tested. Some additional experiments were conducted at minimum P c of 15 MPa for BAO1 and BAO2 samples and maximum P c of 45 MPa for BLM samples. We chose these P c in the additional experiments to reflect the effective in-situ stresses of where these samples come from, which vary due to differences in depth and how overpressured the formation is. Similar to the P c , P diff . was increased stepwise to a maximum of 15–60 MPa, depending on the sample types. The maximum P diff . were chosen so that it will not exceed 50% of the estimated rock strength. This was to prevent the creep behavior from transition into the tertiary creep regime facilitated by brittle-creep. 4 Laboratory Results 4.1 Rock strength The ultimate strength describes the maximum principal stress magnitude that a rock can withstand before failure. Comparison of the ultimate strengths at confining pressure of 30 MPa (Fig. 8 ) shows a negative correlation between ultimate strength and volume of soft components for both the U.S. and Indonesian shales. It also indicates that the Indonesian shales exhibit a lower strength for the same soft component content than the U.S. shales. The strength data plot is also consistent with observations made by Sone ( 2012 ) that shale strengths are slightly higher when loaded parallel than when loaded perpendicular to the bedding plane. Such trend has also been seen in other rock types with layered fabric including phyllite and slate (Paterson and Wong, 2005 ). The results of FEM modeling (Akl and Sone, 2016 ) have also supported these observations by showing that anisotropic shales will start yielding at higher stress when loaded parallel to the bedding, compared to when loading is perpendicular to the bedding, due to the difference in internal stress partitioning between the soft and stiff components. However, MDS and PAP samples are exceptions to this trend. 4.2 Static elastic properties Young’s modulus were determined as the best fitting linear slope of the stress-strain relationship during the triaxial loading steps. The Young’s moduli show that horizontal samples are always stiffer compared to vertical samples reflecting the elastic anisotropy. The Young’s moduli also vary with axial stress depending on the sample and sometimes increase or decrease with axial stress. Therefore, we report Young’s moduli obtained from triaxial steps whose average axial stress is closest to 45 MPa to facilitate comparison between different rock types and comparison with U.S. shale data from Sone and Zoback ( 2013a ). In Fig. 9 a, we plot the Young’s moduli of the Indonesia samples as a function of soft component volume. The plot shows a decreasing trend with increase in soft component volume, similar to that of the U.S. shales. However, the Young’s moduli of Indonesian shales are much lower than the U.S. shales for a given soft component volume. We note that BAO1 and BAO2 samples especially have low Young’s moduli below 10 GPa. Unlike Young’s modulus, we do not see any clear trends in Poisson’s ratio with soft component volume (Fig. 9 b). We do observe, however, that one of the Poisson ratios of the horizontal sample (ν13) is always greater than the other Poisson ratios (ν12 or 31) for all tested samples. This is consistent with the vertical transversely isotropic (VTI) nature of the shale samples where the symmetry axis (x3-axis) is in the direction normal to the bedding plane. This high value of Poisson’s ratio occurs because a VTI material is more compliant in the x3-axis direction than the x1- and x2-axis directions. The static anisotropy (Eh/Ev) calculated from the ratio of Young’s moduli of horizontal (Eh) and vertical (Ev) samples are shown in Fig. 10 . Compared to the U.S. shales, Indonesian shales roughly follow the same increasing anisotropy trend with soft component volume with static anisotropy values ranging between about 1 and 2.5. This trend is consistent with the textural anisotropy observed in the samples. The isotropic massive shale (MAS) represents a value of 1, while the papery laminated shale (PAP), with the strongest fabric anisotropy, as seen in Fig. 5 , represents a value of 2.1. Moreover, the crack parallel-bedding observed in PAP, SDM, SKR2, BAO1, BAO2, and BLM also contributes to the anisotropy. The anisotropy is most pronounced in BAO1 and BAO2 samples due to the frequent occurrence of bedding-parallel cracks leading to the highest mechanical anisotropy at about 2.5. The anisotropy difference between the two BLM sample groups is interpreted to be caused by the combination of variability in calcareous fossil abundance between laminae and crack intensity. In addition to the static elastic properties measured during the first loading, we also measured the static elastic properties while the axial stress was partially unloaded and reloaded. Figure 11 a shows the difference in static Young’s modulus between these two measurements, where the loading-reloading Young’s modulus is lower by about 15% compared to the first-loading Young’s modulus. These differences are consistent with the U.S. shale measurement results where Sone and Zoback ( 2013a ) attributes the difference to the hysteresis caused by inelastic deformation occurring during first loading. A comparison of first-loading versus unloading-reloading Poisson’s ratio does not show any trend (Fig. 11 b). 4.3 Dynamic elastic properties We also recorded ultrasonic velocities (Vp & Vs) to obtain dynamic elastic properties, in addition to the static elastic properties obtained from stress and strain measurements. As listed, for instance, by Fjær ( 2019 ), various mechanisms cause differences between static and dynamic moduli of sedimentary rocks such as the pore fluid flow occurring in response to the local strain gradient or the difference in strain amplitude involved in different types of measurements. The relation between static and dynamic elastic properties is beneficial for inferring static properties from dynamic properties and vice versa. For instance, application of lab data for problems such as borehole stability and tectonic stresses estimation require the use of static elastic properties. If dynamic data is only available, an empirical relationship between the static and dynamic properties can be used to estimate the required static properties. Figure 12 (a) Comparison between dynamic and static first-loading Young’s modulus. The solid line represents a one-to-one correlation between static and dynamic, while the dashed line represents a correlation where the dynamic is two times higher than the static Young’s modulus. (b) Comparison between dynamic and static first-loading Poisson’s ratio. The solid line represents a one-to-one correlation between static and dynamic, while the dashed line represents a correlation where the dynamic is two times higher or lower than the static Poisson’s ratio. All Indonesian data related to the above dynamic elastic properties plot are given in the Supplementary Information. 4.4 Creep compliance Creep deformation was observed by holding the differential stress constant for 3 hours. We note that we only report creep deformation from the triaxial stage in the axial direction because those during the hydrostatic stage were not reliable. In the hydrostatic stage, the sensor responses to changes in confining pressure and temperature were of comparable magnitude to the sample creep strain responses and could not be effectively de-trended. Lateral strain response is also difficult to analyze due to the non-monotonic behavior observed in some samples (Sone, 2012 ), which requires a more detailed analysis separating the isotropic and anisotropic components of the tensorial deformation (Trzeciak et al., 2018) and is reserved for future studies. Similar to Young’s modulus discussed above, we obtained the creep strain data at various differential stress magnitudes. Since the resulting creep strain is a function of the applied axial stress, we cannot use the strain magnitudes directly to quantify the ductility of the sample. In an attempt to allow comparison of creep behavior between different samples and different creep data collected at different stress levels, Sone and Zoback ( 2014a ) defined the 3-hr creep compliance which is defined as the linear slope between the cumulative axial creep strain at the end of the hold stage versus the cumulative differential stress, as shown in Fig. 13 . The 3-hr creep compliance does not change with the differential stress, and it is relatively insensitive to confining pressure, can be used as a proxy to represent the overall ductility of a sample. As seen in Fig. 13 , samples with more soft-component contents exhibit higher slopes than those with less soft component contents, which indicate greater creep compliance. The vertical samples also show higher 3-hr creep compliance than the horizontal samples. Compared with U.S. shales, most Indonesian shales have a similar 3-hr creep compliance values, except for the BAO1 and BAO2 samples of the Baong Formation, which show 3-hr creep compliance approximately an order of magnitude larger than the other Indonesian shale samples and U.S. shales. 4.5 Power-law Constitutive Parameters The quantitative characterization of shale time-dependent deformation (creep), in the framework of linear viscoelasticity, has also been studied by Sone and Zoback ( 2014a ). Their study shows that the creep compliance function, J(t), can be obtained from laboratory data by dividing the time-dependent strain response at each differential stress stage with the magnitude of the stress step. We cautiously note that the time-dependent strain response we use here to calculate J(t) in the context of linear viscoelasticity includes both elastic and creep strain measured relative to the beginning of the new load step, whereas in the previous section, only the creep strain recorded after the loading is considered. While this creep compliance can usually be described using various functions, including a power law, logarithmic, and prony series (Trzeciak et al., 2017), a power-law has been found to be suitable in describing the creep compliance in both the short term (3 hours) and long term (2 weeks) with minimal constitutive parameters (Sone and Zoback, 2014a ). Therefore, in this study, the creep compliance function, J(t), was chosen to be a power-law function of time, t, with B and n as the constitutive parameters. $$J\left(t\right)=B{t}^{n}$$ 1 A linear regression in the log-log plot of creep compliance, J(t), and time, t, provides the power-law constitutive parameters. The slope represents the power-law exponent (n), while the intercept with the vertical line at log(t) = 0 denotes the compliance constant (B). The compliance constant (B) is found to roughly correlate with the inverse of the first-loading Young’s modulus from U.S. shales (Sone and Zoback, 2014a ). The power-law exponent parameter, n, describes the relative degree to which creep deformation occurs beyond elastic deformation. Figure 14 summarizes the power-law parameters (B and n) of all samples obtained from the regression of Eq. 1 . Each sample is represented by a single plot, where the plot represents the average of all power-law parameters recovered from data at each stress levels. The plots show that the B and n parameters roughly exhibit a positive correlation, capturing the intuition that compliant rocks have more tendency to creep because pore spaces in the rock promote both elastic and creep compliance. Consistent with observations made for the 3-hr creep compliances in Fig. 13 , samples with more soft components and a vertical orientation generally have higher creep compliance parameters (B and n) than samples with less soft components and horizontal orientation. However, such trend is not observed for the BAO1 and BAO2 samples. Although the vertical samples show higher B values than the horizontal samples, their n values are similar or slightly lower. Compared to U.S. shales, the Indonesian sample have similar range of creep compliance parameters, except for the BAO1 and BAO2 samples taken from the over-pressured interval, which shows much higher values for both B and n. 5 Discussion 5.1 Upper and lower bound of elastic properties Sone and Zoback ( 2013a ) and Trezciak et al. (2018) has interpreted variation in elastic properties of organic-rich shales in terms of a binary mixture model consisting of soft components, in the form of clay minerals and organic matter, and stiff components, represented by quartz, feldspar, pyrite, carbonate, and other stiff minerals. The elastic properties of these end-member components are approximated by Hill’s average of the elastic properties of each component derived from dynamic laboratory measurements (Mavko et al., 2020 ), resulting in 86.9 GPa for E stiff and 10.8 GPa for E soft (Sone and Zoback, 2013a ). The soft and stiff component end members are then used to calculate the theoretical upper and lower bound using Voigt and Reuss averages, respectively. It is important to point out that the simplified shale model assumes that the elastic properties do not explicitly consider the influence of porosity since the soft component properties are considered to already take into account pore compliance. The U.S. and Polish shale data (Sone and Zoback, 2013a ; Trezciak et al., 2018) confirm the general validity of this model, where the upper and lower bounds limit the distribution of the elastic modulus. However, Sone and Zoback ( 2013a ) observed that the measured static Young’s moduli are slightly lower than the predicted theoretical bounds and suggested that the discrepancy reflects the difference between static and dynamic measurements. Therefore, compared to the dynamic measurements subject to small strain and less inelastic deformation, the static moduli of soft components shall be lower than inferred from dynamic measurements. Lowering the soft components value to half of its reference value, i.e., 5.4 GPa, successfully captured the variations in the static Young’s modulus of U.S. shales (Sone and Zoback, 2013a ). The Young’s modulus data of the Indonesian shales are first compared against the theoretical upper and lower bounds calculated using the same end member elastic properties as the U.S. shales (Fig. 15 ). Results show that the static Young’s moduli for Indonesian shale samples, except for BAO1 and BAO2 samples, mostly fall within the bounds consistent with U.S. shale data (Fig. 15 black lines). However, Indonesian shale data distribute much lower than the U.S. shale data, especially for horizontal samples, which is relatively close to the lower limit. This lower distribution is problematic because horizontal samples should plot closer to the Voigt upper limit because the loading condition is closer to the iso-strain condition of a Voigt average than the iso-stress condition of a Reuss average. This distribution suggests that we need to lower the end member moduli to lower the theoretical bounds and achieve consistency with the laboratory-measured elastic moduli. We notice that even if the soft-component modulus is lowered to zero, the moduli of the horizontal samples will plot closer to the Reuss lower bound rather than the Voigt upper bound. Therefore, since there is no specific reason to change the soft component modulus, we still use 5.4 GPa as the soft-component modulus for BLM and CSB samples. On the other hand, lowering the stiff component Young’s modulus helps to decrease the Voigt upper bound closer to the horizontal sample data. We reduce Young’s modulus of stiff components from its original value of 86.9 GPa used in Sone and Zoback ( 2013a ) to 50 GPa as a rough first order guess. This reduction successfully shifts the bounds to better capture the laboratory-measured Young’s modulus of the Indonesian shale (Fig. 15 blue lines), except for the BAO1 and BAO2 samples of the Baong Formation. The BAO1 and BAO2 samples of the Baong Formation show striking differences from other samples in terms of their elastic properties, brittle strength, and creep behavior. These samples also had much higher soft component contents (> 45%) as well as porosity (> 15%) compared to the U.S. shale and the other Indonesian samples. These physical properties result in the additional compliance of the BAO1 and BAO2 samples and their Young’s modulus being plotted below and outside the U.S. and Indonesian shale bounds. In search of a set of upper and lower bounds that is consistent with the Baong Formation samples, we first lower the soft-component modulus to 3.2 GPa, which is the lowest modulus observed for the BAO1 and BAO2 vertical samples. This is because the soft-component modulus marks the lower limit of Young’s modulus and thus must be no greater than 3.2 GPa. We then also lower the stiff-component Young’s modulus to 18 GPa to ensure that the BAO1 and BAO2 data lie below the Voigt upper bound. The upper and lower bounds drawn as such (Fig. 15 red line) roughly agrees with the BAO1 and BAO2 experimental data. The end-member moduli values found from this bound-matching exercise are summarized in Table 2 . Table 2 Summary of the Young modulus and Creep compliance of stiff and soft components for three different shales E soft E stiff S soft S stiff U.S. Shales 5.4 86.9 1.00E-04 1.50E-07 CSB and BLM Shales 5.4 50.0 1.18E-04 2.59E-06 BAO1 and BAO2 Shales 3.2 18.0 5.48E-04 5.36E-05 5.2 Creep properties In terms of creep properties, Sone and Zoback ( 2013b ) found that the tendency to creep (S creep ) for each shale sample correlated well with the elastic Young’s modulus (E), as shown in Fig. 16 . They explained the correlation through the internal stress partitioning between the soft and stiff components of the shale, as expressed in Eq. 2 below $${S}_{creep}=\frac{{A}_{1}}{E}+{A}_{2}$$ 2 Where \({A}_{1}=\frac{{E}_{stiff}{E}_{soft}}{{E}_{stiff}-{E}_{soft}}\left({S}_{soft}-{S}_{stiff}\right), {A}_{2}=\frac{{E}_{stiff}{S}_{stiff}-{E}_{soft}{S}_{soft}}{{E}_{stiff}-{E}_{soft}}\) E stiff and S stiff represent the Young’s modulus and 3-hr creep compliance of the stiff components, respectively. For the soft components, E soft and S soft describe those parameters, respectively. Since there are no direct measurement of S stiff and S soft , Sone and Zoback ( 2013b ) inferred these values by comparing lab-measured properties of their stiffest and most compliant samples with their analytical equations on the relation between elastic and creep properties of the individual components. From such comparison, they determined that S soft and S stiff for the studied U.S. shales are approximately 1x10 − 4 and < 1x10 − 7 MPa − 1 , respectively. Indonesia shales, however, have a lower elastic modulus than the U.S. shales. Since creep compliance is a function of Young’s modulus (Eq. 2 ), this suggests that Indonesian shale will follow a different relationship between creep and elastic properties. Here we utilize the same analytical equations from Sone and Zoback ( 2013b ) and compare them with our data to obtain appropriate S stiff and S soft for the Indonesian shales. For the case of CSB and BLM samples, the stiffest samples represented by the horizontal SKR1 sample had a S creep of 4.9x10 − 6 MPa − 1 , while the most compliant sample represented by the vertical PAP sample had a S creep of 4.32x10 − 5 MPa − 1 . Following the method suggested by Sone and Zoback ( 2013b ), we estimated the S stiff and S soft as 2.59x10 − 6 MPa − 1 and 1.18x10 − 4 MPa-1, respectively. For the case of BAO1 and BAO2 samples, we used data from BAO1 horizontal-2 having S creep of 2.10x10 − 4 MPa − 1 as the stiffest sample and BAO1 vertical-2 with S creep of 5.48x10 − 4 MPa − 1 as the most compliant sample. The resulting S stiff and S soft were estimated as 5.36x10 − 5 MPa − 1 and 5.48x10 − 4 MPa − 1 , respectively. We summarize the S stiff and S soft values recovered from the different datasets in Table 2 . New relations between S creep and E for CSB/BLM samples and BAO1/BAO2 samples are drawn in Fig. 16 using Eq. 2 and the values in Table 2 . As shown in Fig. 16 , in general, the CSB and BLM samples (solid blue curve) closely follow the U.S. shales trend (black solid curve). In contrast, the BAO1 and BAO2 shale samples show a higher 3-hr creep compliance for a given Young’s modulus, by approximately a factor of 2, compared to the trend of the U.S., CSB, and BLM shale samples (solid red curve). 5.3 Relation between burial history and mechanical maturity From the values in Table 2 , we see that it is the low stiffness and high creep compliance of the stiff components that makes the mechanical properties of the Indonesian shales distinct from US shales. In this section, we discuss the cause of this distinct mechanical properties in relation to the burial history of the Indonesian shales. We also suggest to introduce the idea of mechanical maturity to describe how burial history influence the progression of diagenesis and the resulting evolution of shale mechanical properties. Burial histories are an essential component of source rock evaluation, especially concerning the ability of the source rocks to produce oil and gas, commonly known as the thermal maturity. Burial history describes the change in depth of a formation after their deposition, which controls the stress and temperature that a rock experiences. Since diagenesis occurs as a result of stress and temperature increase, burial histories provide constraints in understanding the diagenetic state and thermal maturity of organic materials in sedimentary rocks. Meanwhile, compaction is a process that also occurs during diagenesis driven by stress and facilitated by physical processes such as frictional grain boundary sliding (Hagin, 2003 ; Karner, 2006 ) and pressure solution (Fowler and Yang, 1999 ). Laboratory data generally shows that a decrease in porosity leads to an increase in elastic modulus and decrease in creep compliance. Therefore, we expect a causal relationship between burial history and the mechanical properties of shale. To delineate the impact of burial history on mechanical properties of organic-rich shales, we compare some example burial histories of U.S. and Indonesian shale reservoirs. Figure 17 shows the 1D burial history of a well at Fort Worth Basin, USA (Curtis, 2002 ) and North Sumatra Basin, Indonesia (Ascaria, 2010 ). The Barnett Formation is a Carboniferous Period (359 − 299 Ma) deposit, buried to a depth of about 9000 ft (2750 m), from the Pennsylvanian to Late Cretaceous Epoch (323 − 100 Ma), and uplifted to its present depth around 4000 ft (1200 m) from Late Cretaceous to Miocene Epoch (100 − 23 Ma). The burial to its deepest position coincides with the early generation of petroleum from Late Permian Period (260 Ma). As a comparison, in NSB, the deposition of the Belumai Formation started at the early Miocene Epoch (23 Ma), followed by the lower Baong Formation at the middle Miocene Epoch (16 Ma), and the above formations until Pleistocene Epoch (Ascaria, 2010 ). In this presented example, which comes from a well drilled in a deeper area of the NSB compared to our study, the Belumai formation was buried to its present depth of about 2400 m from about 23 Ma to 5 Ma and started its oil expulsion from Pliocene Epoch (4 Ma). The well we studied likely has a slightly different burial history since it is located relatively near the Barisan mountains and hence affected by Barisan Orogeny (Ariyanto and Syarifuddin, 2018 ). Specifically, in addition to the general burial history shown in Fig. 17 b, the formations penetrated by our studied well have also been experiencing uplift since about Pleistocene Epoch (2 Ma) to its present depth. As seen in the comparison of the burial histories, the Belumai and Baong Formations are at slightly shallower depths compared to the Barnett Shale. Nevertheless, because of the higher heat flow in Indonesia, the Indonesian shales have experienced similar, or even higher, temperatures compared to the Barnett Shale. This higher heat flow leads to both U.S. and Indonesian shales having undergone early maturation and expulsion processes resulting in similar thermal maturity. On the other hand, there is a significant difference in mechanical properties despite the only slight difference in burial depths. Extrapolation of the consolidation theory from soil mechanics (Mitchell and Soga, 2005 ) suggest that the consolidation state (i.e., porosity) of a sedimentary rock is determined by the maximum overburden stress experienced during the burial history. However, the overburden stresses at the maximum burial depth of the Barnett Shale and the Belumai Formation are approximately 69 MPa and 60 MPa, respectively, assuming average rock density of 2500 kg/m 3 , only slightly different from each other. Therefore, we suggest that the vast difference in the age of deposition is the cause of difference in mechanical properties. Age controls the duration that the formations experience the maximum load and the duration of the time-dependent diagenetic processes. Although direct evidences are not available, time-dependent compaction of shales have been suggested to operate over geological time scales. Sone and Zoback ( 2014a , b ) extrapolates the power-law creep behavior of gas shales observed in the lab to geological times to show that such extrapolation may help explain intra-reservoir stress heterogeneities and would not lead to unrealistic predictions of porosity loss over geological time. If so, porosity loss due to diagenesis is also a function of time and results in mechanical properties that vary due to difference in geological age. We propose to describe this progression of mechanical properties with age as the process of mechanical maturation, and the degree to which this maturation has progressed as mechanical maturity. Mechanical maturity is a function of stress magnitude and time, potentially some integration of the stress history with respect to time, because compaction is a time-dependent process driven by stress, as opposed to thermal maturity which is mainly dependent on maximum temperature. The comparison of elastic moduli and creep compliance of the Indonesian shales with the U.S. shales has shown three distinct trends (Fig. 16 ): the U.S. trend, CSB/BLM trend, and BAO1/BAO2 trend. These trends mainly reflect the difference in the stiff component properties as shown in Table 2 . Because the minerals composing the stiff components in the binary mixture model should not change significantly during mechanical maturation, we interpret that this reflects, to the first order, the inter-granular porosity that resides between stiff grains and closes with mechanical maturation by compaction. If we take the U.S. Shales as the mature reference, CSB/BLM will represent a relatively early-mature state, whereas the BAO1/BAO2 are notably immature mechanically due to the overpressure that reduces the maximum effective stress experienced by the formations. Note that in Baong formation, significant disequilibrium compaction is suggested to have occurred (Syaiful et al., 2020 ) in addition to hydrocarbon generation which should lead to residual intergranular porosity. Indonesian shales are thermally mature but mechanically early-mature to immature compared to U.S. shales because the significantly younger age has limited the time needed for mechanical maturation. 5.4 Influence of shale depositional environment on the mechanical properties Shales deposit in very slow-moving water in various depositional environments ranging from terrestrial, transitional, to marine environments. Terrestrial environments include lacustrine, swamp, and river floodplains; transitional environments include marsh and delta; marine environments range from shallow to deep water. Shale can be found in various depositional ages, from Paleozoic to Cenozoic Era, and in extensive tectonic settings, from stable Craton to active convergent / divergent margins. The success of the U.S. in extracting gas from their marine source rocks has attracted other countries to search for potential shale gas reservoirs in shale deposits from similar marine environments first, potentially subordinating shale deposits from the terrestrial and transitional settings. It is reasonable to expect that the type of organic material found in shales are dependent on the particular depositional environments as previously suggested by Tissot and Welte ( 1984 ). However, in the case of kerogen type, Vandenbrouck and Largeau (2007) have shown that type of kerogen does not have to be associated with any specific environment. In addition, as is known in conventional petroleum systems, gas can be produced from mature source rocks of kerogen type 2 and 3 or even from over-mature source rocks of kerogen type 1. Thus, depositional environment may not be a determining factor for mature organic-rich shales to produce gas. Our laboratory analyses suggest no significant differences in the mechanical properties of shale deposited in the lacustrine (CSB samples) and marine environment (BLM samples), as both datasets lie within the same bounds and are described by the same binary mixture model. Even though our data in Table 1 show differences in composition between the two sample groups, where marine samples are more clay-rich, while lacustrine samples are more affluent in organic matters, treating their influence on mechanical properties to be equal by summing their volumes as the soft component volume appears to obscure the difference in composition (Fig. 3 ). Here, we treat their contribution as mutually complementary, although the specific contribution of each component in the shale is unknown and still requires further research. In addition, the relation between creep and elastic properties of CSB and NSB samples generally follow the same trend describing the progression of diagenesis, as shown in Fig. 16 . Therefore, our data do not show the influence of the depositional environment on the mechanical properties of the shale. 6 Conclusion We studied shale samples taken from outcrops of lacustrine deposit in the Central Sumatra Basin (CSB) and subsurface samples of marine deposits from the North Sumatra Basin (NSB), representing examples of Indonesian organic-rich shale potential. In general, we find that the Indonesian shales we studied showed higher porosity and creep compliance but lower ultimate strength and Young’s modulus compared to the U.S. shales. However, while Indonesian shales exhibit lower Young’s moduli, their static anisotropies (Eh/Ev) are within the same range as U.S. shales. Such information provides important first order constraints in geophysical exploration. The Indonesian shales we studied exhibit different mechanical properties (brittle strength, elastic moduli, and creep compliance) from U.S. shales. We see these differences as a difference in mechanical maturity and reflecting the progression of mechanical properties, from higher elastic moduli and lower creep compliance towards lower elastic moduli and higher creep compliance as diagenesis progress. In this context, U.S. shales can be referenced as a mechanically mature shale. In contrast, the Indonesian shales are relatively early-mature due to its young depositional age. The Baong formation shales, in particular, are further classified as immature due to the high porosity maintained by the hard-overpressure. The laboratory analyses results show no significant differences in the mechanical properties of shale deposited in the lacustrine (CSB samples) and marine environment (BLM samples). Both datasets lie within the same bounds and can be described using the same binary mixture model. Not only the soft component volumes, but also the mechanical maturity of the sample reflecting its diagenetic history determine the main difference in shale mechanical properties from different localities. Further comparison with data from basins with different diagenetic histories is recommended to investigate the influence of mechanical maturity on shale mechanical properties. Declarations Ethics approval Not applicable. Consent to publish All authors agree to publish this manuscript in journal of Geomechanics and Geophysics for Geo-Energy and Geo-Resources. Funding E.S.L. received a scholarship from the Ministry of Finance of the Republic of Indonesia through the Indonesia Endowment Fund for Education (LPDP, Grant No. 20160622016960) for conducting this study, as part of his doctoral research. Author Contribution E.S.L. and H.S. wrote the main manuscript text and E.S.L. prepared the figures and tables. All authors reviewed the manuscript. Acknowledgements We would like to acknowledge P.T. Pertamina for providing subsurface core data and P.T. Karbindo Abesyapradhi for permission to take surface outcrops data of the Kiliran Jao/Pematang Formation from their quarry for this study. E.S.L. expressed his gratitude for the scholarship from the Ministry of Finance of the Republic of Indonesia through the Indonesia Endowment Fund for Education (LPDP, Grant No. 20160622016960). Data availability The data used to support the findings of this study are available in the Supplementary Material. References Abedi S, Slim M, Hofmann R, Bryndzia T, Ulm FJ (2016) Nanochemo-mechanical signature of organic-rich shales: a coupled indentation–EDX analysis. 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Journal of Petroleum Science and Engineering 55:221–227. https://doi.org/10.1016/j.petrol.2006.08.010 Xu S, Rassouli FS, Zoback MD (2017) Utilizing a viscoplastic stress relaxation model to study vertical hydraulic fracture propagation in Permian Basin. In: Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, Austin, Texas. https://doi.org/10.15530/URTEC-2017-2669793 Yang Y, Sone H, Zoback MD (2015) Fracture gradient prediction using the viscous relaxation model and its relation to out-of-zone microseismicity. In: Paper presented at the SPE Annual Technical Conference and Exhibition, Houston, Texas. https://doi.org/10.2118/174782-MS Zargari S, Wilkinson TM, Packard CE, Prasad M (2016) Effect of thermal maturity on elastic properties of kerogen. Geophysics 81:M1–M6. https://doi.org/10.1190/geo2015-0194.1 Zhang J, Ouyang L, Zhu D, Hill AD (2015) Experimental and numerical studies of reduced fracture conductivity due to proppant embedment in the shale reservoir. Journal of Petroleum Science and Engineering 130:37–45. https://doi.org/10.1016/j.petrol.2015.04.004 Zoback MD (2007) Reservoir geomechanics. Cambridge University Press. Additional Declarations No competing interests reported. Supplementary Files 240503GGGGSupplementaryMaterial.xlsx Cite Share Download PDF Status: Published Journal Publication published 26 Mar, 2026 Read the published version in Geomechanics and Geophysics for Geo-Energy and Geo-Resources → Version 1 posted Editorial decision: Revision requested 16 Apr, 2025 Reviews received at journal 14 Apr, 2025 Reviews received at journal 23 Mar, 2025 Reviewers agreed at journal 07 Mar, 2025 Reviewers agreed at journal 07 Mar, 2025 Reviews received at journal 06 Sep, 2024 Reviewers agreed at journal 19 May, 2024 Reviewers invited by journal 18 May, 2024 Editor assigned by journal 18 May, 2024 Submission checks completed at journal 16 May, 2024 First submitted to journal 03 May, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4364214","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":306134359,"identity":"a9da1edf-4e91-4444-8545-e76227fa9f47","order_by":0,"name":"Eril Suhada Lanin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIie3QPwrCMBiH4V8o1EXsWlHwCnFz8M9VWgpOKoKL4mCK0C6iazev4OgY6eDS7o4VL9DewCYuTomjQ94x5OHLF8Bk+stIyLEEbFicEyZPmKshjIMKYnv89hsBJAGaFB8CKInTScWU8aLVOVRpdUXPYVb4UJH20RckWNnd/MJvGfoJJ/uBitBM7mL5kTuvSQRyAYmUD5t8yK4ms0KQiZbQpiSpIBDE1xJXTPHovSZTyvPMDZJUs4tzaDyLcr31z0nwKjfX4egUx0/lj8m8r6mApb1vMplMJl1vfUFN0ZdAtN4AAAAASUVORK5CYII=","orcid":"","institution":"Bandung Institute of Technology","correspondingAuthor":true,"prefix":"","firstName":"Eril","middleName":"Suhada","lastName":"Lanin","suffix":""},{"id":306134360,"identity":"794f2e6d-0731-43fc-96b3-da45206fb3c4","order_by":1,"name":"Hiroki Sone","email":"","orcid":"","institution":"University of Wisconsin Madison","correspondingAuthor":false,"prefix":"","firstName":"Hiroki","middleName":"","lastName":"Sone","suffix":""}],"badges":[],"createdAt":"2024-05-03 12:54:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4364214/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4364214/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s40948-025-01028-z","type":"published","date":"2026-03-26T16:10:26+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":57319599,"identity":"201b1fa7-98cb-472f-a12b-a3139fa880bd","added_by":"auto","created_at":"2024-05-29 05:51:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":906759,"visible":true,"origin":"","legend":"\u003cp\u003ea) Location map of samples used in this study. The surface outcrop samples come from two areas of Central Sumatra Basin (red and yellow stars) and subsurface core samples from well drilled in North Sumatra Basin (blue dashed area). b) Generalized stratigraphic sections of Sumatra Basins (modified from Doust and Noble, 2008). The surface outcrop samples are marked with red and green stars, while the subsurface cores are marked with blue stars.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4364214/v1/d3ec30e1e987ea796c1d729f.png"},{"id":57320267,"identity":"baf4e141-7d78-4967-a7f7-a7414d1750a4","added_by":"auto","created_at":"2024-05-29 05:59:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":821412,"visible":true,"origin":"","legend":"\u003cp\u003ePhotos of the outcrops from where samples were taken. Exposed lithofacies are also labeled in the Kiliran Jao outcrop.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4364214/v1/9d4ee545f370d3a21b7eb546.png"},{"id":57319218,"identity":"70332e4e-ca90-49dc-83e0-790d216cbdd9","added_by":"auto","created_at":"2024-05-29 05:43:27","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":55736,"visible":true,"origin":"","legend":"\u003cp\u003eTernary plot of sample compositions (MDS = mudstone, MAS = massive mudstone, PAP = papery laminated shale, SDM = sandy mudstone, SST = sandstone, SKR1 = Sangkarewang-1 (carbonate dominated), SKR2 = Sangkarewang-2 (QFP dominated), BAO1 = Baong-1 (Core-1 from NSB well), BAO2 = Baong-2 (Core-2 from NSB well), BLM = Belumai (Core-3 from NSB well), U.S. Shales = U.S. Shales data from Sone and Zoback, 2013a and Villamor Lora et al., 2016)\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4364214/v1/d4dd2b1eeb4bf92b81249aed.png"},{"id":57320268,"identity":"fb0458ae-aaf2-401a-aece-9ae765a84fa8","added_by":"auto","created_at":"2024-05-29 05:59:28","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":210182,"visible":true,"origin":"","legend":"\u003cp\u003ePorosity as a function of (a) bulk density and (b) soft components (clay minerals and organic matters). All Indonesian data related to the above porosity plot are given in the Supplementary Information.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-4364214/v1/2095f3050c223c0846ef6fb9.png"},{"id":57319604,"identity":"1142e65f-2365-42a6-b10a-db77df46d364","added_by":"auto","created_at":"2024-05-29 05:51:27","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":4356044,"visible":true,"origin":"","legend":"\u003cp\u003eCross-polarized light image of representative samples used in the experiment (MDS = mudstone, MAS = massive mudstone, PAP = papery laminated shale, SDM = sandy mudstone, SST = sandstone, SKR1 = Sangkarewang-1 (carbonate dominated), SKR2 = Sangkarewang-2 (QFP dominated), BAO1 = Baong-1, BAO2 = Baong-2, BLM = Belumai\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-4364214/v1/2136b09dc5b88cd416193aed.png"},{"id":57319600,"identity":"982fcdfd-632c-484a-a185-a5d69c34a748","added_by":"auto","created_at":"2024-05-29 05:51:27","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":43349,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic of the equipment annotating different components\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-4364214/v1/61e181156c65e1c4ec19928f.png"},{"id":57319603,"identity":"06850c0d-dfc8-444d-b9da-424bb66f99c0","added_by":"auto","created_at":"2024-05-29 05:51:27","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":176646,"visible":true,"origin":"","legend":"\u003cp\u003eIllustration of multi-step confining pressures (P\u003csub\u003ec\u003c/sub\u003e) and axial differential stresses (P\u003csub\u003ediff\u003c/sub\u003e) test\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-4364214/v1/5d160e1d09e8376a90fd4160.png"},{"id":57319225,"identity":"986fc70e-fea0-4e5b-8944-54d057dd691b","added_by":"auto","created_at":"2024-05-29 05:43:27","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":89170,"visible":true,"origin":"","legend":"\u003cp\u003eUltimate strength measured at confining pressure 30 Mpa. All Indonesian data related to the above strength plot are given in the Supplementary Information.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-4364214/v1/84286de8d9b9dea9f6003cee.png"},{"id":57319228,"identity":"c76f374e-97e0-4c0a-888d-5a20e791d98c","added_by":"auto","created_at":"2024-05-29 05:43:28","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":185118,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Static Young’s modulus and (b) Poisson’s ratio as a function of clay + O.M. All Indonesian data related to the above elastic (loading) properties plot are given in the Supplementary Information.\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-4364214/v1/9552569975b8fd040acc8339.png"},{"id":57319234,"identity":"813f8ded-d89c-46a9-9757-7d9f7fa24753","added_by":"auto","created_at":"2024-05-29 05:43:28","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":30728,"visible":true,"origin":"","legend":"\u003cp\u003eStatic anisotropy (Eh/Ev) as a function of clay + O.M.\u003c/p\u003e","description":"","filename":"floatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-4364214/v1/406037cf37bcce92f1f78598.png"},{"id":57319235,"identity":"76655f26-aefb-4252-a726-b9cc95c056b7","added_by":"auto","created_at":"2024-05-29 05:43:28","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":223432,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Comparison between first-loading and unloading-reloading Young’s modulus. The solid line represents a one-to-one correlation between first-loading and unloading-reloading, while the dashed line represents the correlation where the unloading-reloading modulus is 15% lower than the first-loading Young’s modulus. (b) Comparison between first-loading and unloading-reloading Poisson’s ratio. The solid line represents a one-to-one correlation between first-loading and unloading-reloading, while the dashed line represents a correlation where the load/reload is 50% higher and lower than the first-loading Poisson’s ratio. All Indonesian data related to the above elastic (unloading-reloading) properties plot are given in the Supplementary Information.\u003c/p\u003e","description":"","filename":"floatimage11.png","url":"https://assets-eu.researchsquare.com/files/rs-4364214/v1/068b1be7cbf0445126474312.png"},{"id":57319227,"identity":"c6083e39-b205-43c8-a505-091e50cef1c5","added_by":"auto","created_at":"2024-05-29 05:43:27","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":209083,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Comparison between dynamic and static first-loading Young’s modulus. The solid line represents a one-to-one correlation between static and dynamic, while the dashed line represents a correlation where the dynamic is two times higher than the static Young’s modulus. (b) Comparison between dynamic and static first-loading Poisson’s ratio. The solid line represents a one-to-one correlation between static and dynamic, while the dashed line represents a correlation where the dynamic is two times higher or lower than the static Poisson’s ratio. All Indonesian data related to the above dynamic elastic properties plot are given in the Supplementary Information.\u003c/p\u003e","description":"","filename":"floatimage12.png","url":"https://assets-eu.researchsquare.com/files/rs-4364214/v1/502de5447d0f0316d9c09c05.png"},{"id":57319230,"identity":"53cde415-5397-4a76-8c08-2786b96b52d7","added_by":"auto","created_at":"2024-05-29 05:43:28","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":142572,"visible":true,"origin":"","legend":"\u003cp\u003eDetermination of 3-h creep compliance based on the plot of cumulative axial strain against cumulative differential stress from 3-h hold data. All Indonesian data related to the above creep compliance properties plot are given in the Supplementary Information.\u003c/p\u003e","description":"","filename":"floatimage13.png","url":"https://assets-eu.researchsquare.com/files/rs-4364214/v1/48f1efff6060509c9fc20ab4.png"},{"id":57319233,"identity":"e5f585e9-6ebb-40af-b4c1-8f1b2800630b","added_by":"auto","created_at":"2024-05-29 05:43:28","extension":"png","order_by":14,"title":"Figure 14","display":"","copyAsset":false,"role":"figure","size":39897,"visible":true,"origin":"","legend":"\u003cp\u003eSummary of the power-law constitutive parameters. All Indonesian data related to the above creep parameters plot are given in the Supplementary Information.\u003c/p\u003e","description":"","filename":"floatimage14.png","url":"https://assets-eu.researchsquare.com/files/rs-4364214/v1/250920e72e97208928a4a3b4.png"},{"id":57319232,"identity":"1994ae08-b443-490b-b48b-1ed3cbe7dbdd","added_by":"auto","created_at":"2024-05-29 05:43:28","extension":"png","order_by":15,"title":"Figure 15","display":"","copyAsset":false,"role":"figure","size":136946,"visible":true,"origin":"","legend":"\u003cp\u003eStatic Young’s modulus as a function of clay + O.M. The black curves represent the Voigt upper, and Reuss lower bound of U.S. shales from Sone and Zoback (2013a), blue curves represent bounds for CSB and BLM shales, and red curves represent bounds for BAO1 and BAO2 shales\u003c/p\u003e","description":"","filename":"floatimage15.png","url":"https://assets-eu.researchsquare.com/files/rs-4364214/v1/ff5c34b470e78d71ca15eec3.png"},{"id":57319223,"identity":"a66601c2-5bfc-4b68-a60d-93859fd14c5c","added_by":"auto","created_at":"2024-05-29 05:43:27","extension":"png","order_by":16,"title":"Figure 16","display":"","copyAsset":false,"role":"figure","size":53715,"visible":true,"origin":"","legend":"\u003cp\u003e3-h creep compliance data plotted against Young modulus semi-log scale. The black curve represents the trend of U.S. shales from Sone and Zoback (2014b), the blue curve represents the trend for CSB and BLM shales, and the red curve represents the trend for BAO1and BAO2 shales\u003c/p\u003e","description":"","filename":"floatimage16.png","url":"https://assets-eu.researchsquare.com/files/rs-4364214/v1/613c83e35495ecb49f73fec8.png"},{"id":57319605,"identity":"a92f978e-83de-49e1-bb4e-13277795f084","added_by":"auto","created_at":"2024-05-29 05:51:28","extension":"png","order_by":17,"title":"Figure 17","display":"","copyAsset":false,"role":"figure","size":112653,"visible":true,"origin":"","legend":"\u003cp\u003eBurial history of (a) Fort Worth Basin (modified from Curtis, 2002) and (b) well at North Sumatra Basin (modified from Ascaria, 2010)\u003c/p\u003e","description":"","filename":"floatimage17.png","url":"https://assets-eu.researchsquare.com/files/rs-4364214/v1/9797294cd4ca75488ed8f643.png"},{"id":105756096,"identity":"a4b800bc-dfa2-40c4-9696-6e422c53dd6d","added_by":"auto","created_at":"2026-03-30 16:35:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":9853719,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4364214/v1/59d4f043-f97e-41a9-af40-c097305cbcd0.pdf"},{"id":57319220,"identity":"0509e823-79b9-4b0d-b61c-a0bc797fe46d","added_by":"auto","created_at":"2024-05-29 05:43:27","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":44122,"visible":true,"origin":"","legend":"","description":"","filename":"240503GGGGSupplementaryMaterial.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4364214/v1/c5a8237698ae9f8fa77effae.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Mechanical properties of Indonesian organic-rich shales from the Central Sumatra and North Sumatra Basin, and comparison with US shales","fulltext":[{"header":"Highlights","content":"\u003cul\u003e\n \u003cli\u003eLaboratory-measured mechanical properties (rock strength, elastic properties, creep compliance) of Indonesian shales located within Tertiary basins in an active margin setting.\u003c/li\u003e\n \u003cli\u003eIndonesian shales are generally more compliant than Mesozoic/Paleozoic U.S. shales reported in the literature despite similar porosity, thermal maturity, and burial depth.\u003c/li\u003e\n \u003cli\u003eThe difference is attributed to the difference in mechanical maturity, the extent to which mechanical properties have evolved due to diagenesis, mainly influenced by the age of the shales.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"1 Introduction","content":"\u003cp\u003eOrganic-rich shales exhibit a wide range of organic and mineral compositions, fabric anisotropy, and organic maturity. Studying how this leads to varying petrophysical properties and affect reservoir mechanical properties which are critical information in optimizing reservoir development and production. For instance, elastic properties control the propagation of seismic waves, which is important in locating reservoirs and obtaining early information on reservoir properties. Brittle strength is essential in planning and managing parameters necessary for stable drilling and reservoir stimulation (Zoback, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Elastic and ductile properties are necessary to obtain prior estimates of the stress distribution inside reservoirs (Eaton, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1969\u003c/span\u003e; Thiercelin and Plumb, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Blanton and Olson. 1999; Sone and Zoback, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2014b\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLaboratory studies of organic-rich shales have shown that the volume of soft components (i.e., clay minerals and organic matters) and their distribution in the rock texture strongly influence the mechanical properties (Vernik and Nur, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Hornby et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Johnston and Christensen, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Vernik and Liu, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Sondergeld et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Sondergeld et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Sondergeld and Rai, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Vernik and Milovac, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Elastic stiffness of shales are strongly correlated to the soft component volume as well as deformational properties, including brittle strengths and ductile constitutive parameters (e.g., Sone and Zoback, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2013a\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003eb\u003c/span\u003e). The orientation distribution of clay minerals also determines the degree of mechanical anisotropy (e.g., Sone and Zoback, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2013b\u003c/span\u003e; Vernik and Anantharamu, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In addition, the use of nanoindentation in testing shale properties shows that the maturity of organic matter affects the elastic properties of organic-rich shales (Zargari et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Abedi et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRecent studies of producing shale reservoirs suggest that the creep behavior might lead to the closure of conductive fractures and lower reservoir productivity (e.g., Wen et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Alramahi and Sundberg, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Moreover, Sone and Zoback (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2014a\u003c/span\u003e), for instance, use creep constitutive parameters to infer the stress heterogeneities in the reservoir utilizing the viscous relaxation model. In various U.S. shale gas reservoirs, this model has proven to successfully estimate the intra-reservoir stress variation through observations of microseismicity during hydraulic fracturing (e.g., Yang et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Xu et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Ma and Zoback, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIndonesian organic-rich shale potentials lie in relatively young active tectonic settings, different from the U.S. shale reservoirs located in older stable intraplate regions. The difference in age and tectonic setting may result in differences in the mechanical properties between Indonesian and U.S. shales. Therefore, a thorough mechanical characterization of the Indonesian organic-rich shales becomes a fundamental requirement in evaluating the resource potential of shales in Indonesia. Our study aims to characterize, through laboratory testing, the mechanical properties of potential organic-rich shales from two prolific basins in Indonesia. We will begin with a brief description of the geology of the sample location, followed by a description of the samples and laboratory procedures. The laboratory results presented include brittle properties in terms of rock strength, elastic property in the form of Young\u0026rsquo;s modulus and Poisson\u0026rsquo;s ratio, creep compliance, as well as power-law constitutive parameters that represent creep properties. Based on those laboratory results, several points were then discussed, including the theoretical bounds of Young\u0026rsquo;s modulus, the mechanical maturity of Indonesian shales, and the influences of the depositional environment of shale on the mechanical properties.\u003c/p\u003e"},{"header":"2 Geology of Sampling Locations","content":"\u003cp\u003eThe shale samples used in this study come from the Sumatra Island, located in the westernmost part of the Indonesian archipelago. The island has experienced a complex tectonic and depositional history. Based on its stratigraphic record, the oldest rocks found in the Sumatra Island are of the Devonian Period (~\u0026thinsp;360\u0026ndash;420 Ma) (Barber et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Tectonically, the current Sumatra Island represents an active convergent setting, with an oblique subduction system at the southwest. The subduction of the Indo-Australian Plate to the north beneath the Sunda Plate has occurred since the middle Miocene age, with current convergence rate of 6.8 cm/year (Schluter et al., 2002). The subduction divides the physiography of Sumatra Island into several zones, from the southwest to the northeast, respectively: accretionary prisms, fore-arc, volcanic-arc, and back-arc zones. In addition to physiography, this oblique compression also creates a fault zone along Sumatra Island known as Semangko dextral strike-slip fault systems, mainly observed around the volcanic-arc area. Behind the volcanic-arc area, three main hydrocarbon-producing basins are located at the current back-arc location from the northwest to the southeast, known as the North, Central, and South Sumatra Basins (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003eIn terms of tectonostratigraphic evolution, the three Sumatran Basins, as well as the Tertiary basins throughout SE Asia, share many characteristics (Doust and Noble, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Their geological history evolved from early Tertiary synrift to late Tertiary postrift (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). The early synrift period corresponds to the half-graben basin formation, followed by waning subsidence and amalgamation of individual graben, forming extensive lowlands in their late synrift period. The early postrift period corresponds to the marine transgression covering the synrift structure topography and tectonic quiescence. This was followed by regressive delta formation as a result of inversion and folding, which marked the late postrift period.\u003c/p\u003e \u003cp\u003eIn the North Sumatra Basin, the early synrift deposits were recorded as coarse-grain conglomerates filling the graben and bioclastic limestone on the adjacent high topography (Doust and Noble, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Thick, deep marine mudstone deposits represent the late synrift deposits, which also act as the primary source rock in the basin. The sediment of the early postrift period comprises deep marine shale, carbonate buildup on the structural high, and sandy facies in the southern part of the basin. The late postrift regressive sequence started with argillaceous deposits with turbidite sand insert, followed by shallow water sands, silts, and shales. Deep marine deposits continue in the northwestern part, while regressive deltaic sands are deposited in the southeastern part of the basin.\u003c/p\u003e \u003cp\u003eThe Central Sumatra Basin, even showing similar tectonostratigraphic evolution, shows a slightly different depositional environment with only minor carbonate facies in its overall sediment sequence (Doust and Noble, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The early synrift deposits in this basin comprised alluvial, lacustrine, and fluvial-deltaic deposits. This sequence was followed by the late synrift transgression, starting with fluvial deposits and then overlain by shallow marine sands and argillaceous facies. The distal marine sand and shale facies and maximum transgression shale and silt facies record the early postrift period. The later deposits, late postrift sediment, include marine sands and shales in the northwest and regressive delta and alluvial sediment deposits in the southeast of the basin.\u003c/p\u003e \u003cp\u003eTo characterize the mechanical properties of Indonesian organic-rich shales, this study collected samples from surface outcrops and subsurface cores of a tertiary source rock formation in Sumatra. The outcrop samples (the location is marked with star symbols in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea) come from the lacustrine environment deposits of the Central Sumatra Basin (CSB), while the core samples are marine shale deposits from the North Sumatra Basin (NSB). The position of the samples in the stratigraphic section is marked with star symbols in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Surface-outcrop samples\u003c/h2\u003e \u003cp\u003eWe took the lacustrine shale samples of the Central Sumatra Basin (CSB) from a coal quarry in the Kiliran Jao area and outcrops near the Sumatran highway in the Ombilin (Sawah Lunto) area (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), both in West Sumatra Province administration area. Based on the sample characteristics and their location relative to the geological map of the area (Silitonga and Kastowo, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1995\u003c/span\u003e), both samples are Oligocene in age.\u003c/p\u003e \u003cp\u003eThe quarry samples belong to the Kiliran Jao/Pematang Formation of the Kiliran Jao Sub-basin (e.g., Iqbal et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Sunardi, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Widayat et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and the Sumatran highway samples belong to the Sangkarewang Formation of the Ombilin Sub-basin (e.g., Koesoemadinata and Matasak, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1981\u003c/span\u003e). We classify samples of the Kiliran Jao Formation based on their lithofacies into mudstone (MDS), massive mudstone (MAS), papery laminated shale (PAP; Widayat et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), sandy mudstone (SDM), and sandstone (SST). Meanwhile, for the Sangkarewang Formation, we refer to them as SKR-1 and SKR-2 based on their location. Considering the composition, sedimentary structure, and fossil content (Sunardi, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Koesoemadinata and Matasak, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1981\u003c/span\u003e), these two shale deposits can be broadly classified as fluvial-lacustrine facies association deposited in an overfilled lake basin (see classification by Carroll and Bohacs, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1999\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Subsurface-core samples\u003c/h2\u003e \u003cp\u003eThe subsurface samples used in this study come from three conventional cores recovered in a well drilled in the North Sumatra Basin (NSB), referred to as BAO1, BAO2, and BLM samples. While detailed location and depth information are proprietary, BAO1 and BAO2 samples belong to the lower Baong Formation, while BLM come from the Belumai Formation (Pertamina, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBaong formation deposited in a marine environment of the Middle-Late Miocene transgression condition. Its lithology is dominated by a thick shale layer with sandstone turbidite series of a fan lobe in the middle. Apart from its potential as a source rock, the Baong Formation is well-known as a formation that has undergone disequilibrium compaction (Syaiful et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and hydrocarbon generation that led to its current hard-overpressured state.\u003c/p\u003e \u003cp\u003eBelumai Formation, on the other hand, represents a minor source-rock potential with no overpressures. The formation represents an older age (Early Miocene) deep marine environment, where its lithology can broadly be divided into two sections. The upper section consists of an intercalation between shale and clastic limestone with calcareous sandstone, while the lower section is dominated by non-calcareous shale. The BLM samples studied here belong to the bottom-most of the upper Belumai Formation.\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Material and Methods","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Sample characterization\u003c/h2\u003e \u003cp\u003eWe categorized the CSB shale samples from the Kiliran Jao outcrop according to their lithofacies. On the other hand, due to limited lithofacies variation at the outcrop, we named the Ombilin outcrop samples according to their location. Moreover, the naming for core samples from NSB referred to their depth and geological formation. We determine the mineralogical composition of the samples using powder X-Ray Diffraction (XRD) analysis, and the organic content (total organic carbon \u0026ndash; TOC) and maturity through pyrolysis analysis. These analyses were conducted either on specimens coming from the same outcrop block samples and nearby conventional-core plugs or sidewall-core (SWC) in the case of subsurface samples. Drill cuttings were used for the XRD and pyrolysis analyses when nearby core materials were unavailable.\u003c/p\u003e \u003cp\u003eThe weight percent of minerals obtained from the analyses were converted into volumetric percentages using the empirical relation between organic material density and vitrinite reflectance (Alfred and Vernik, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Vernik, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). We categorized the mineral fractions into QFP, carbonates, and clay components. The QFP represent stiff granular components consisting of mainly quartz, feldspar, and pyrite. The carbonates group consists of calcite, dolomite, and siderite. The clays are in the form of illite-smectite, illite, kaolinite, and chlorite. The volume fractions of the minerals and organic material are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and plotted in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The volumetric percentages of QFP, carbonate, and clay from the analyzed samples ranged from 11\u0026ndash;57%, 5\u0026ndash;74%, and 8\u0026ndash;52%, respectively, and the volumetric percentage of organic contents and their maturity ranged from 2\u0026ndash;23% and 0.3\u0026ndash;1.3% Ro, respectively. Considering that clays and organic matters have relatively similar compliant mechanical properties, different from the stiffer QFP and carbonates, we refer to these two components as soft components following Sone and Zoback (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2013a\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of mineral compositions (vol%), organic (TOC) contents (vol% and wt%), and maturities (%Ro)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGeological\u003c/p\u003e \u003cp\u003eFormation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003cp\u003eCode\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eQFP\u003c/p\u003e \u003cp\u003e[vol%]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCarbonate\u003c/p\u003e \u003cp\u003e[vol%]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eClay\u003c/p\u003e \u003cp\u003e[vol%]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTOC\u003c/p\u003e \u003cp\u003e[vol% (wt%)]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eClay\u0026thinsp;+\u0026thinsp;TOC\u003c/p\u003e \u003cp\u003e[vol %]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eMaturity\u003c/p\u003e \u003cp\u003e[%Ro]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eCentral Sumatra Basin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eKiliran Jao (Pematang)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e56.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e23.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7.4 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e30.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMAS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e62.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e11.7 (4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e23.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePAP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e45.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e22.8 (9.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e39.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSDM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e61.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8.0 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e20.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e56.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.6 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e15.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSangka-rewang\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSKR1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e74.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6.5 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e14.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSKR2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e35.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7.6 (3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e43.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eNorth Sumatra Basin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eBaong\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBAO1-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e43.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.1 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e46.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBAO1-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e43.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.1 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e46.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBAO2-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e47.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e44.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.8 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e47.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBAO2-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e52.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.9 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e54.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBelumai\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBLM-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e33.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e20.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.8 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e21.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBLM-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e21.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.2 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e23.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOwing to the difficulty in measuring porosity of shales by methods requiring fluid infiltration into the pore spaces (e.g., Sun et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), we estimated the porosity by comparing the bulk density of the room-dry samples with the average mineral densities determined from the composition and individual mineral density. Based on the estimation, the porosity of shale samples used in this study ranged from 4\u0026ndash;31%.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea shows the relationship between the estimated porosity and bulk density with the dashed lines representing grain densities of 2.4, 2.5, 2.6, 2.7, and 2.8 g/cm\u003csup\u003e3\u003c/sup\u003e. The low grain density of the PAP samples reflect the high TOC (23 vol%) of the PAP shales, whereas NSB (BAO1, BAO2, and BLM) samples with a TOC\u0026thinsp;\u0026le;\u0026thinsp;3 vol% has the highest grain density. We also see an overall increase in porosity with soft-component content (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb), consistent with observations from U.S. shales (Sone and Zoback, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2013a\u003c/span\u003e) that highlights the porosity residing within the aggregates of platy clay minerals and within the internal structures of porous organic matters. However, a comparison between the Indonesian and the U.S. shales shows that the Indonesian shales have higher porosities for a given soft-component content than U.S. shales, which are older in geological age. These data may suggest that geological age, and thus the associated duration of diagenesis, either affects the porosity within the soft components or there are other sources of porosity in the younger Indonesian shale samples.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Microscopic observation\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the microstructure of representative samples used in the experiments observed under the optical microscope with cross-polarized light. In general, thin section observations show that the shale samples are composed of silt-size fragments within a very fine-grained matrix whose grains are unresolvable in the optical microscope. Some samples show a homogeneous texture of clay, carbonate, or quartz matrices, such as MAS and SKR1 while other samples show heterogeneous grain sizes as seen in MDS, SDM, SKR2, BAO1, and BLM. The SST sample contain the coarsest grains consisting of very fine sands.\u003c/p\u003e \u003cp\u003eIn terms of texture, some shale samples exhibit fabric anisotropy, such as PAP, SKR2, BAO1, BAO2, and BLM. This fabric anisotropy is most evident in PAP samples, mainly due to the alignment of its lenticular calcareous mineral aggregates and the preferred orientation of the organic matter. The elongated organic materials also define fabric anisotropy in SKR2. However, the fabric anisotropy is different in BAO1 and BAO2, which has a relatively massive matrix texture, but the bedding-parallel cracks define their anisotropy. SKR2 and BLM samples also show the existence of bedding-parallel cracks, which dictate their anisotropy, but with intensity lower than BAO1 and BAO2. In addition, BLM contains calcareous fossils whose variability in abundance between laminae determines a weak layered fabric.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Laboratory procedures\u003c/h2\u003e \u003cp\u003eWe start the laboratory procedures by preparing cylindrical samples of 2.54 cm diameter and 5.08 cm length whose axes are either parallel or perpendicular to the bedding plane, referred to as horizontal and vertical samples, respectively. While the sample diameter is less than recommended by the ISRM suggested methods (ISRM, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1983\u003c/span\u003e), we do not expect this to influence the results because the samples were homogenous due to their fine grain size. The samples were drilled using kerosine as the cooling fluid considering the reactivity of the clay minerals within the shale samples. Then the ends were cut in a precision saw using a low oil content cutting fluid. The cylindrical plugs were dried overnight at 70\u0026deg; C using a vacuum oven to remove any fluid remaining in the pore space that may cause poroelastic pressure buildup during the experiments. A pair of horizontal and vertical samples for all CSB outcrop and NSB subsurface samples were prepared to characterize the anisotropy in elastic and deformational properties.\u003c/p\u003e \u003cp\u003eWe conducted experiments in a triaxial apparatus equipped with independent servo-controls for the confining pressure and axial load. The deformation of the CSB samples were measured using a pair of 2-element cross-stacked strain gauges attached to the cylindrical surface separated by 90\u0026deg; in the horizontal cross-section. On the other hand, the deformation of the NSB samples were measured using a pair of the linear variable differential transformer (LVDT) in the axial direction and a pair of strain-gauge-based spring-loaded displacement transducers in the two lateral directions perpendicular to each other (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMultiple steps of confining pressure (P\u003csub\u003ec\u003c/sub\u003e) and axial differential stress (P\u003csub\u003ediff\u003c/sub\u003e) were applied to measure deformation under hydrostatic and triaxial stress conditions, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). After each stress step, the stress was maintained constant for 3 hours to observe the creep deformation at each stress state. The stress was then partially unloaded and reloaded before moving to the next stage to obtain elastic constants. After the last creep stage, the sample was loaded in the axial direction under constant confining stress until the rock reached failure. At failure, the peak axial stress value (P\u003csub\u003eaxial\u003c/sub\u003e = P\u003csub\u003ec\u003c/sub\u003e + P\u003csub\u003ediff\u003c/sub\u003e) represents the brittle strength. Following the failure, further loading continued until the differential stress dropped and reached a constant value representing the residual strength, or the sliding frictional strength. At the final stage, before removing all applied stress, the differential stress was unloaded and reloaded again to re-slide the failure planes and confirm the residual strength.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe performed most of the experiments at a maximum P\u003csub\u003ec\u003c/sub\u003e of 30 MPa, comparable to the effective vertical stress at 2 km depth under hydrostatic pore pressure conditions, in order to facilitate comparison of mechanical properties between all shale samples tested. Some additional experiments were conducted at minimum P\u003csub\u003ec\u003c/sub\u003e of 15 MPa for BAO1 and BAO2 samples and maximum P\u003csub\u003ec\u003c/sub\u003e of 45 MPa for BLM samples. We chose these P\u003csub\u003ec\u003c/sub\u003e in the additional experiments to reflect the effective in-situ stresses of where these samples come from, which vary due to differences in depth and how overpressured the formation is. Similar to the P\u003csub\u003ec\u003c/sub\u003e, P\u003csub\u003ediff\u003c/sub\u003e. was increased stepwise to a maximum of 15\u0026ndash;60 MPa, depending on the sample types. The maximum P\u003csub\u003ediff\u003c/sub\u003e. were chosen so that it will not exceed 50% of the estimated rock strength. This was to prevent the creep behavior from transition into the tertiary creep regime facilitated by brittle-creep.\u003c/p\u003e \u003c/div\u003e"},{"header":"4 Laboratory Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Rock strength\u003c/h2\u003e \u003cp\u003eThe ultimate strength describes the maximum principal stress magnitude that a rock can withstand before failure. Comparison of the ultimate strengths at confining pressure of 30 MPa (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e) shows a negative correlation between ultimate strength and volume of soft components for both the U.S. and Indonesian shales. It also indicates that the Indonesian shales exhibit a lower strength for the same soft component content than the U.S. shales. The strength data plot is also consistent with observations made by Sone (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) that shale strengths are slightly higher when loaded parallel than when loaded perpendicular to the bedding plane. Such trend has also been seen in other rock types with layered fabric including phyllite and slate (Paterson and Wong, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). The results of FEM modeling (Akl and Sone, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) have also supported these observations by showing that anisotropic shales will start yielding at higher stress when loaded parallel to the bedding, compared to when loading is perpendicular to the bedding, due to the difference in internal stress partitioning between the soft and stiff components. However, MDS and PAP samples are exceptions to this trend.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Static elastic properties\u003c/h2\u003e \u003cp\u003eYoung\u0026rsquo;s modulus were determined as the best fitting linear slope of the stress-strain relationship during the triaxial loading steps. The Young\u0026rsquo;s moduli show that horizontal samples are always stiffer compared to vertical samples reflecting the elastic anisotropy. The Young\u0026rsquo;s moduli also vary with axial stress depending on the sample and sometimes increase or decrease with axial stress. Therefore, we report Young\u0026rsquo;s moduli obtained from triaxial steps whose average axial stress is closest to 45 MPa to facilitate comparison between different rock types and comparison with U.S. shale data from Sone and Zoback (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2013a\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ea, we plot the Young\u0026rsquo;s moduli of the Indonesia samples as a function of soft component volume. The plot shows a decreasing trend with increase in soft component volume, similar to that of the U.S. shales. However, the Young\u0026rsquo;s moduli of Indonesian shales are much lower than the U.S. shales for a given soft component volume. We note that BAO1 and BAO2 samples especially have low Young\u0026rsquo;s moduli below 10 GPa.\u003c/p\u003e \u003cp\u003eUnlike Young\u0026rsquo;s modulus, we do not see any clear trends in Poisson\u0026rsquo;s ratio with soft component volume (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eb). We do observe, however, that one of the Poisson ratios of the horizontal sample (ν13) is always greater than the other Poisson ratios (ν12 or 31) for all tested samples. This is consistent with the vertical transversely isotropic (VTI) nature of the shale samples where the symmetry axis (x3-axis) is in the direction normal to the bedding plane. This high value of Poisson\u0026rsquo;s ratio occurs because a VTI material is more compliant in the x3-axis direction than the x1- and x2-axis directions.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe static anisotropy (Eh/Ev) calculated from the ratio of Young\u0026rsquo;s moduli of horizontal (Eh) and vertical (Ev) samples are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e. Compared to the U.S. shales, Indonesian shales roughly follow the same increasing anisotropy trend with soft component volume with static anisotropy values ranging between about 1 and 2.5. This trend is consistent with the textural anisotropy observed in the samples. The isotropic massive shale (MAS) represents a value of 1, while the papery laminated shale (PAP), with the strongest fabric anisotropy, as seen in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, represents a value of 2.1. Moreover, the crack parallel-bedding observed in PAP, SDM, SKR2, BAO1, BAO2, and BLM also contributes to the anisotropy. The anisotropy is most pronounced in BAO1 and BAO2 samples due to the frequent occurrence of bedding-parallel cracks leading to the highest mechanical anisotropy at about 2.5. The anisotropy difference between the two BLM sample groups is interpreted to be caused by the combination of variability in calcareous fossil abundance between laminae and crack intensity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn addition to the static elastic properties measured during the first loading, we also measured the static elastic properties while the axial stress was partially unloaded and reloaded. Figure\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003ea shows the difference in static Young\u0026rsquo;s modulus between these two measurements, where the loading-reloading Young\u0026rsquo;s modulus is lower by about 15% compared to the first-loading Young\u0026rsquo;s modulus. These differences are consistent with the U.S. shale measurement results where Sone and Zoback (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2013a\u003c/span\u003e) attributes the difference to the hysteresis caused by inelastic deformation occurring during first loading. A comparison of first-loading versus unloading-reloading Poisson\u0026rsquo;s ratio does not show any trend (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Dynamic elastic properties\u003c/h2\u003e \u003cp\u003eWe also recorded ultrasonic velocities (Vp \u0026amp; Vs) to obtain dynamic elastic properties, in addition to the static elastic properties obtained from stress and strain measurements. As listed, for instance, by Fj\u0026aelig;r (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), various mechanisms cause differences between static and dynamic moduli of sedimentary rocks such as the pore fluid flow occurring in response to the local strain gradient or the difference in strain amplitude involved in different types of measurements. The relation between static and dynamic elastic properties is beneficial for inferring static properties from dynamic properties and vice versa. For instance, application of lab data for problems such as borehole stability and tectonic stresses estimation require the use of static elastic properties. If dynamic data is only available, an empirical relationship between the static and dynamic properties can be used to estimate the required static properties.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e (a) Comparison between dynamic and static first-loading Young\u0026rsquo;s modulus. The solid line represents a one-to-one correlation between static and dynamic, while the dashed line represents a correlation where the dynamic is two times higher than the static Young\u0026rsquo;s modulus. (b) Comparison between dynamic and static first-loading Poisson\u0026rsquo;s ratio. The solid line represents a one-to-one correlation between static and dynamic, while the dashed line represents a correlation where the dynamic is two times higher or lower than the static Poisson\u0026rsquo;s ratio. All Indonesian data related to the above dynamic elastic properties plot are given in the Supplementary Information.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Creep compliance\u003c/h2\u003e \u003cp\u003eCreep deformation was observed by holding the differential stress constant for 3 hours. We note that we only report creep deformation from the triaxial stage in the axial direction because those during the hydrostatic stage were not reliable. In the hydrostatic stage, the sensor responses to changes in confining pressure and temperature were of comparable magnitude to the sample creep strain responses and could not be effectively de-trended. Lateral strain response is also difficult to analyze due to the non-monotonic behavior observed in some samples (Sone, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), which requires a more detailed analysis separating the isotropic and anisotropic components of the tensorial deformation (Trzeciak et al., 2018) and is reserved for future studies.\u003c/p\u003e \u003cp\u003eSimilar to Young\u0026rsquo;s modulus discussed above, we obtained the creep strain data at various differential stress magnitudes. Since the resulting creep strain is a function of the applied axial stress, we cannot use the strain magnitudes directly to quantify the ductility of the sample. In an attempt to allow comparison of creep behavior between different samples and different creep data collected at different stress levels, Sone and Zoback (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2014a\u003c/span\u003e) defined the 3-hr creep compliance which is defined as the linear slope between the cumulative axial creep strain at the end of the hold stage versus the cumulative differential stress, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e. The 3-hr creep compliance does not change with the differential stress, and it is relatively insensitive to confining pressure, can be used as a proxy to represent the overall ductility of a sample.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs seen in Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e, samples with more soft-component contents exhibit higher slopes than those with less soft component contents, which indicate greater creep compliance. The vertical samples also show higher 3-hr creep compliance than the horizontal samples. Compared with U.S. shales, most Indonesian shales have a similar 3-hr creep compliance values, except for the BAO1 and BAO2 samples of the Baong Formation, which show 3-hr creep compliance approximately an order of magnitude larger than the other Indonesian shale samples and U.S. shales.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Power-law Constitutive Parameters\u003c/h2\u003e \u003cp\u003eThe quantitative characterization of shale time-dependent deformation (creep), in the framework of linear viscoelasticity, has also been studied by Sone and Zoback (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2014a\u003c/span\u003e). Their study shows that the creep compliance function, J(t), can be obtained from laboratory data by dividing the time-dependent strain response at each differential stress stage with the magnitude of the stress step. We cautiously note that the time-dependent strain response we use here to calculate J(t) in the context of linear viscoelasticity includes both elastic and creep strain measured relative to the beginning of the new load step, whereas in the previous section, only the creep strain recorded after the loading is considered. While this creep compliance can usually be described using various functions, including a power law, logarithmic, and prony series (Trzeciak et al., 2017), a power-law has been found to be suitable in describing the creep compliance in both the short term (3 hours) and long term (2 weeks) with minimal constitutive parameters (Sone and Zoback, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2014a\u003c/span\u003e). Therefore, in this study, the creep compliance function, J(t), was chosen to be a power-law function of time, t, with B and n as the constitutive parameters.\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$J\\left(t\\right)=B{t}^{n}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eA linear regression in the log-log plot of creep compliance, J(t), and time, t, provides the power-law constitutive parameters. The slope represents the power-law exponent (n), while the intercept with the vertical line at log(t)\u0026thinsp;=\u0026thinsp;0 denotes the compliance constant (B). The compliance constant (B) is found to roughly correlate with the inverse of the first-loading Young\u0026rsquo;s modulus from U.S. shales (Sone and Zoback, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2014a\u003c/span\u003e). The power-law exponent parameter, n, describes the relative degree to which creep deformation occurs beyond elastic deformation.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e14\u003c/span\u003e summarizes the power-law parameters (B and n) of all samples obtained from the regression of Eq.\u0026nbsp;\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Each sample is represented by a single plot, where the plot represents the average of all power-law parameters recovered from data at each stress levels. The plots show that the B and n parameters roughly exhibit a positive correlation, capturing the intuition that compliant rocks have more tendency to creep because pore spaces in the rock promote both elastic and creep compliance. Consistent with observations made for the 3-hr creep compliances in Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e, samples with more soft components and a vertical orientation generally have higher creep compliance parameters (B and n) than samples with less soft components and horizontal orientation. However, such trend is not observed for the BAO1 and BAO2 samples. Although the vertical samples show higher B values than the horizontal samples, their n values are similar or slightly lower. Compared to U.S. shales, the Indonesian sample have similar range of creep compliance parameters, except for the BAO1 and BAO2 samples taken from the over-pressured interval, which shows much higher values for both B and n.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"5 Discussion","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e5.1 Upper and lower bound of elastic properties\u003c/h2\u003e \u003cp\u003eSone and Zoback (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2013a\u003c/span\u003e) and Trezciak et al. (2018) has interpreted variation in elastic properties of organic-rich shales in terms of a binary mixture model consisting of soft components, in the form of clay minerals and organic matter, and stiff components, represented by quartz, feldspar, pyrite, carbonate, and other stiff minerals. The elastic properties of these end-member components are approximated by Hill\u0026rsquo;s average of the elastic properties of each component derived from dynamic laboratory measurements (Mavko et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), resulting in 86.9 GPa for E\u003csub\u003estiff\u003c/sub\u003e and 10.8 GPa for E\u003csub\u003esoft\u003c/sub\u003e (Sone and Zoback, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2013a\u003c/span\u003e). The soft and stiff component end members are then used to calculate the theoretical upper and lower bound using Voigt and Reuss averages, respectively. It is important to point out that the simplified shale model assumes that the elastic properties do not explicitly consider the influence of porosity since the soft component properties are considered to already take into account pore compliance. The U.S. and Polish shale data (Sone and Zoback, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2013a\u003c/span\u003e; Trezciak et al., 2018) confirm the general validity of this model, where the upper and lower bounds limit the distribution of the elastic modulus. However, Sone and Zoback (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2013a\u003c/span\u003e) observed that the measured static Young\u0026rsquo;s moduli are slightly lower than the predicted theoretical bounds and suggested that the discrepancy reflects the difference between static and dynamic measurements. Therefore, compared to the dynamic measurements subject to small strain and less inelastic deformation, the static moduli of soft components shall be lower than inferred from dynamic measurements. Lowering the soft components value to half of its reference value, i.e., 5.4 GPa, successfully captured the variations in the static Young\u0026rsquo;s modulus of U.S. shales (Sone and Zoback, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2013a\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe Young\u0026rsquo;s modulus data of the Indonesian shales are first compared against the theoretical upper and lower bounds calculated using the same end member elastic properties as the U.S. shales (Fig.\u0026nbsp;\u003cspan refid=\"Fig15\" class=\"InternalRef\"\u003e15\u003c/span\u003e). Results show that the static Young\u0026rsquo;s moduli for Indonesian shale samples, except for BAO1 and BAO2 samples, mostly fall within the bounds consistent with U.S. shale data (Fig.\u0026nbsp;\u003cspan refid=\"Fig15\" class=\"InternalRef\"\u003e15\u003c/span\u003e black lines). However, Indonesian shale data distribute much lower than the U.S. shale data, especially for horizontal samples, which is relatively close to the lower limit. This lower distribution is problematic because horizontal samples should plot closer to the Voigt upper limit because the loading condition is closer to the iso-strain condition of a Voigt average than the iso-stress condition of a Reuss average. This distribution suggests that we need to lower the end member moduli to lower the theoretical bounds and achieve consistency with the laboratory-measured elastic moduli.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe notice that even if the soft-component modulus is lowered to zero, the moduli of the horizontal samples will plot closer to the Reuss lower bound rather than the Voigt upper bound. Therefore, since there is no specific reason to change the soft component modulus, we still use 5.4 GPa as the soft-component modulus for BLM and CSB samples. On the other hand, lowering the stiff component Young\u0026rsquo;s modulus helps to decrease the Voigt upper bound closer to the horizontal sample data. We reduce Young\u0026rsquo;s modulus of stiff components from its original value of 86.9 GPa used in Sone and Zoback (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2013a\u003c/span\u003e) to 50 GPa as a rough first order guess. This reduction successfully shifts the bounds to better capture the laboratory-measured Young\u0026rsquo;s modulus of the Indonesian shale (Fig.\u0026nbsp;\u003cspan refid=\"Fig15\" class=\"InternalRef\"\u003e15\u003c/span\u003e blue lines), except for the BAO1 and BAO2 samples of the Baong Formation.\u003c/p\u003e \u003cp\u003eThe BAO1 and BAO2 samples of the Baong Formation show striking differences from other samples in terms of their elastic properties, brittle strength, and creep behavior. These samples also had much higher soft component contents (\u0026gt;\u0026thinsp;45%) as well as porosity (\u0026gt;\u0026thinsp;15%) compared to the U.S. shale and the other Indonesian samples. These physical properties result in the additional compliance of the BAO1 and BAO2 samples and their Young\u0026rsquo;s modulus being plotted below and outside the U.S. and Indonesian shale bounds. In search of a set of upper and lower bounds that is consistent with the Baong Formation samples, we first lower the soft-component modulus to 3.2 GPa, which is the lowest modulus observed for the BAO1 and BAO2 vertical samples. This is because the soft-component modulus marks the lower limit of Young\u0026rsquo;s modulus and thus must be no greater than 3.2 GPa. We then also lower the stiff-component Young\u0026rsquo;s modulus to 18 GPa to ensure that the BAO1 and BAO2 data lie below the Voigt upper bound. The upper and lower bounds drawn as such (Fig.\u0026nbsp;\u003cspan refid=\"Fig15\" class=\"InternalRef\"\u003e15\u003c/span\u003e red line) roughly agrees with the BAO1 and BAO2 experimental data. The end-member moduli values found from this bound-matching exercise are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of the Young modulus and Creep compliance of stiff and soft components for three different shales\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eE\u003csub\u003esoft\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eE\u003csub\u003estiff\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS\u003csub\u003esoft\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eS\u003csub\u003estiff\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eU.S. Shales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e86.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.50E-07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCSB and BLM Shales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.18E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.59E-06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBAO1 and BAO2 Shales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.48E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.36E-05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e5.2 Creep properties\u003c/h2\u003e \u003cp\u003eIn terms of creep properties, Sone and Zoback (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2013b\u003c/span\u003e) found that the tendency to creep (S\u003csub\u003ecreep\u003c/sub\u003e) for each shale sample correlated well with the elastic Young\u0026rsquo;s modulus (E), as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig16\" class=\"InternalRef\"\u003e16\u003c/span\u003e. They explained the correlation through the internal stress partitioning between the soft and stiff components of the shale, as expressed in Eq.\u0026nbsp;\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e2\u003c/span\u003e below\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$${S}_{creep}=\\frac{{A}_{1}}{E}+{A}_{2}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({A}_{1}=\\frac{{E}_{stiff}{E}_{soft}}{{E}_{stiff}-{E}_{soft}}\\left({S}_{soft}-{S}_{stiff}\\right), {A}_{2}=\\frac{{E}_{stiff}{S}_{stiff}-{E}_{soft}{S}_{soft}}{{E}_{stiff}-{E}_{soft}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003eE\u003csub\u003estiff\u003c/sub\u003e and S\u003csub\u003estiff\u003c/sub\u003e represent the Young\u0026rsquo;s modulus and 3-hr creep compliance of the stiff components, respectively. For the soft components, E\u003csub\u003esoft\u003c/sub\u003e and S\u003csub\u003esoft\u003c/sub\u003e describe those parameters, respectively. Since there are no direct measurement of S\u003csub\u003estiff\u003c/sub\u003e and S\u003csub\u003esoft\u003c/sub\u003e, Sone and Zoback (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2013b\u003c/span\u003e) inferred these values by comparing lab-measured properties of their stiffest and most compliant samples with their analytical equations on the relation between elastic and creep properties of the individual components. From such comparison, they determined that S\u003csub\u003esoft\u003c/sub\u003e and S\u003csub\u003estiff\u003c/sub\u003e for the studied U.S. shales are approximately 1x10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e and \u0026lt;\u0026thinsp;1x10\u003csup\u003e\u0026minus;\u0026thinsp;7\u003c/sup\u003e MPa\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIndonesia shales, however, have a lower elastic modulus than the U.S. shales. Since creep compliance is a function of Young\u0026rsquo;s modulus (Eq.\u0026nbsp;\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), this suggests that Indonesian shale will follow a different relationship between creep and elastic properties. Here we utilize the same analytical equations from Sone and Zoback (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2013b\u003c/span\u003e) and compare them with our data to obtain appropriate S\u003csub\u003estiff\u003c/sub\u003e and S\u003csub\u003esoft\u003c/sub\u003e for the Indonesian shales. For the case of CSB and BLM samples, the stiffest samples represented by the horizontal SKR1 sample had a S\u003csub\u003ecreep\u003c/sub\u003e of 4.9x10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e MPa\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, while the most compliant sample represented by the vertical PAP sample had a S\u003csub\u003ecreep\u003c/sub\u003e of 4.32x10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e MPa\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Following the method suggested by Sone and Zoback (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2013b\u003c/span\u003e), we estimated the S\u003csub\u003estiff\u003c/sub\u003e and S\u003csub\u003esoft\u003c/sub\u003e as 2.59x10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e MPa\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 1.18x10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e MPa-1, respectively. For the case of BAO1 and BAO2 samples, we used data from BAO1 horizontal-2 having S\u003csub\u003ecreep\u003c/sub\u003e of 2.10x10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e MPa\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e as the stiffest sample and BAO1 vertical-2 with S\u003csub\u003ecreep\u003c/sub\u003e of 5.48x10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e MPa\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e as the most compliant sample. The resulting S\u003csub\u003estiff\u003c/sub\u003e and S\u003csub\u003esoft\u003c/sub\u003e were estimated as 5.36x10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e MPa\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 5.48x10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e MPa\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, respectively. We summarize the S\u003csub\u003estiff\u003c/sub\u003e and S\u003csub\u003esoft\u003c/sub\u003e values recovered from the different datasets in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. New relations between S\u003csub\u003ecreep\u003c/sub\u003e and E for CSB/BLM samples and BAO1/BAO2 samples are drawn in Fig.\u0026nbsp;\u003cspan refid=\"Fig16\" class=\"InternalRef\"\u003e16\u003c/span\u003e using Eq.\u0026nbsp;\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and the values in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig16\" class=\"InternalRef\"\u003e16\u003c/span\u003e, in general, the CSB and BLM samples (solid blue curve) closely follow the U.S. shales trend (black solid curve). In contrast, the BAO1 and BAO2 shale samples show a higher 3-hr creep compliance for a given Young\u0026rsquo;s modulus, by approximately a factor of 2, compared to the trend of the U.S., CSB, and BLM shale samples (solid red curve).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e5.3 Relation between burial history and mechanical maturity\u003c/h2\u003e \u003cp\u003eFrom the values in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, we see that it is the low stiffness and high creep compliance of the stiff components that makes the mechanical properties of the Indonesian shales distinct from US shales. In this section, we discuss the cause of this distinct mechanical properties in relation to the burial history of the Indonesian shales. We also suggest to introduce the idea of mechanical maturity to describe how burial history influence the progression of diagenesis and the resulting evolution of shale mechanical properties.\u003c/p\u003e \u003cp\u003eBurial histories are an essential component of source rock evaluation, especially concerning the ability of the source rocks to produce oil and gas, commonly known as the thermal maturity. Burial history describes the change in depth of a formation after their deposition, which controls the stress and temperature that a rock experiences. Since diagenesis occurs as a result of stress and temperature increase, burial histories provide constraints in understanding the diagenetic state and thermal maturity of organic materials in sedimentary rocks. Meanwhile, compaction is a process that also occurs during diagenesis driven by stress and facilitated by physical processes such as frictional grain boundary sliding (Hagin, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Karner, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) and pressure solution (Fowler and Yang, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Laboratory data generally shows that a decrease in porosity leads to an increase in elastic modulus and decrease in creep compliance. Therefore, we expect a causal relationship between burial history and the mechanical properties of shale.\u003c/p\u003e \u003cp\u003eTo delineate the impact of burial history on mechanical properties of organic-rich shales, we compare some example burial histories of U.S. and Indonesian shale reservoirs. Figure\u0026nbsp;\u003cspan refid=\"Fig17\" class=\"InternalRef\"\u003e17\u003c/span\u003e shows the 1D burial history of a well at Fort Worth Basin, USA (Curtis, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) and North Sumatra Basin, Indonesia (Ascaria, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The Barnett Formation is a Carboniferous Period (359\u0026thinsp;\u0026minus;\u0026thinsp;299 Ma) deposit, buried to a depth of about 9000 ft (2750 m), from the Pennsylvanian to Late Cretaceous Epoch (323\u0026thinsp;\u0026minus;\u0026thinsp;100 Ma), and uplifted to its present depth around 4000 ft (1200 m) from Late Cretaceous to Miocene Epoch (100\u0026thinsp;\u0026minus;\u0026thinsp;23 Ma). The burial to its deepest position coincides with the early generation of petroleum from Late Permian Period (260 Ma).\u003c/p\u003e \u003cp\u003eAs a comparison, in NSB, the deposition of the Belumai Formation started at the early Miocene Epoch (23 Ma), followed by the lower Baong Formation at the middle Miocene Epoch (16 Ma), and the above formations until Pleistocene Epoch (Ascaria, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). In this presented example, which comes from a well drilled in a deeper area of the NSB compared to our study, the Belumai formation was buried to its present depth of about 2400 m from about 23 Ma to 5 Ma and started its oil expulsion from Pliocene Epoch (4 Ma). The well we studied likely has a slightly different burial history since it is located relatively near the Barisan mountains and hence affected by Barisan Orogeny (Ariyanto and Syarifuddin, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Specifically, in addition to the general burial history shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig17\" class=\"InternalRef\"\u003e17\u003c/span\u003eb, the formations penetrated by our studied well have also been experiencing uplift since about Pleistocene Epoch (2 Ma) to its present depth.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs seen in the comparison of the burial histories, the Belumai and Baong Formations are at slightly shallower depths compared to the Barnett Shale. Nevertheless, because of the higher heat flow in Indonesia, the Indonesian shales have experienced similar, or even higher, temperatures compared to the Barnett Shale. This higher heat flow leads to both U.S. and Indonesian shales having undergone early maturation and expulsion processes resulting in similar thermal maturity.\u003c/p\u003e \u003cp\u003eOn the other hand, there is a significant difference in mechanical properties despite the only slight difference in burial depths. Extrapolation of the consolidation theory from soil mechanics (Mitchell and Soga, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) suggest that the consolidation state (i.e., porosity) of a sedimentary rock is determined by the maximum overburden stress experienced during the burial history. However, the overburden stresses at the maximum burial depth of the Barnett Shale and the Belumai Formation are approximately 69 MPa and 60 MPa, respectively, assuming average rock density of 2500 kg/m\u003csup\u003e3\u003c/sup\u003e, only slightly different from each other. Therefore, we suggest that the vast difference in the age of deposition is the cause of difference in mechanical properties. Age controls the duration that the formations experience the maximum load and the duration of the time-dependent diagenetic processes.\u003c/p\u003e \u003cp\u003eAlthough direct evidences are not available, time-dependent compaction of shales have been suggested to operate over geological time scales. Sone and Zoback (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2014a\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003eb\u003c/span\u003e) extrapolates the power-law creep behavior of gas shales observed in the lab to geological times to show that such extrapolation may help explain intra-reservoir stress heterogeneities and would not lead to unrealistic predictions of porosity loss over geological time. If so, porosity loss due to diagenesis is also a function of time and results in mechanical properties that vary due to difference in geological age. We propose to describe this progression of mechanical properties with age as the process of mechanical maturation, and the degree to which this maturation has progressed as mechanical maturity. Mechanical maturity is a function of stress magnitude and time, potentially some integration of the stress history with respect to time, because compaction is a time-dependent process driven by stress, as opposed to thermal maturity which is mainly dependent on maximum temperature.\u003c/p\u003e \u003cp\u003eThe comparison of elastic moduli and creep compliance of the Indonesian shales with the U.S. shales has shown three distinct trends (Fig.\u0026nbsp;\u003cspan refid=\"Fig16\" class=\"InternalRef\"\u003e16\u003c/span\u003e): the U.S. trend, CSB/BLM trend, and BAO1/BAO2 trend. These trends mainly reflect the difference in the stiff component properties as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Because the minerals composing the stiff components in the binary mixture model should not change significantly during mechanical maturation, we interpret that this reflects, to the first order, the inter-granular porosity that resides between stiff grains and closes with mechanical maturation by compaction. If we take the U.S. Shales as the mature reference, CSB/BLM will represent a relatively early-mature state, whereas the BAO1/BAO2 are notably immature mechanically due to the overpressure that reduces the maximum effective stress experienced by the formations. Note that in Baong formation, significant disequilibrium compaction is suggested to have occurred (Syaiful et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) in addition to hydrocarbon generation which should lead to residual intergranular porosity. Indonesian shales are thermally mature but mechanically early-mature to immature compared to U.S. shales because the significantly younger age has limited the time needed for mechanical maturation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e5.4 Influence of shale depositional environment on the mechanical properties\u003c/h2\u003e \u003cp\u003eShales deposit in very slow-moving water in various depositional environments ranging from terrestrial, transitional, to marine environments. Terrestrial environments include lacustrine, swamp, and river floodplains; transitional environments include marsh and delta; marine environments range from shallow to deep water. Shale can be found in various depositional ages, from Paleozoic to Cenozoic Era, and in extensive tectonic settings, from stable Craton to active convergent / divergent margins.\u003c/p\u003e \u003cp\u003eThe success of the U.S. in extracting gas from their marine source rocks has attracted other countries to search for potential shale gas reservoirs in shale deposits from similar marine environments first, potentially subordinating shale deposits from the terrestrial and transitional settings. It is reasonable to expect that the type of organic material found in shales are dependent on the particular depositional environments as previously suggested by Tissot and Welte (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e1984\u003c/span\u003e). However, in the case of kerogen type, Vandenbrouck and Largeau (2007) have shown that type of kerogen does not have to be associated with any specific environment. In addition, as is known in conventional petroleum systems, gas can be produced from mature source rocks of kerogen type 2 and 3 or even from over-mature source rocks of kerogen type 1. Thus, depositional environment may not be a determining factor for mature organic-rich shales to produce gas.\u003c/p\u003e \u003cp\u003eOur laboratory analyses suggest no significant differences in the mechanical properties of shale deposited in the lacustrine (CSB samples) and marine environment (BLM samples), as both datasets lie within the same bounds and are described by the same binary mixture model. Even though our data in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e show differences in composition between the two sample groups, where marine samples are more clay-rich, while lacustrine samples are more affluent in organic matters, treating their influence on mechanical properties to be equal by summing their volumes as the soft component volume appears to obscure the difference in composition (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Here, we treat their contribution as mutually complementary, although the specific contribution of each component in the shale is unknown and still requires further research. In addition, the relation between creep and elastic properties of CSB and NSB samples generally follow the same trend describing the progression of diagenesis, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig16\" class=\"InternalRef\"\u003e16\u003c/span\u003e. Therefore, our data do not show the influence of the depositional environment on the mechanical properties of the shale.\u003c/p\u003e \u003c/div\u003e"},{"header":"6 Conclusion","content":"\u003cp\u003eWe studied shale samples taken from outcrops of lacustrine deposit in the Central Sumatra Basin (CSB) and subsurface samples of marine deposits from the North Sumatra Basin (NSB), representing examples of Indonesian organic-rich shale potential. In general, we find that the Indonesian shales we studied showed higher porosity and creep compliance but lower ultimate strength and Young\u0026rsquo;s modulus compared to the U.S. shales. However, while Indonesian shales exhibit lower Young\u0026rsquo;s moduli, their static anisotropies (Eh/Ev) are within the same range as U.S. shales. Such information provides important first order constraints in geophysical exploration.\u003c/p\u003e \u003cp\u003eThe Indonesian shales we studied exhibit different mechanical properties (brittle strength, elastic moduli, and creep compliance) from U.S. shales. We see these differences as a difference in mechanical maturity and reflecting the progression of mechanical properties, from higher elastic moduli and lower creep compliance towards lower elastic moduli and higher creep compliance as diagenesis progress. In this context, U.S. shales can be referenced as a mechanically mature shale. In contrast, the Indonesian shales are relatively early-mature due to its young depositional age. The Baong formation shales, in particular, are further classified as immature due to the high porosity maintained by the hard-overpressure.\u003c/p\u003e \u003cp\u003eThe laboratory analyses results show no significant differences in the mechanical properties of shale deposited in the lacustrine (CSB samples) and marine environment (BLM samples). Both datasets lie within the same bounds and can be described using the same binary mixture model. Not only the soft component volumes, but also the mechanical maturity of the sample reflecting its diagenetic history determine the main difference in shale mechanical properties from different localities. Further comparison with data from basins with different diagenetic histories is recommended to investigate the influence of mechanical maturity on shale mechanical properties.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eEthics approval\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent to publish\u003c/strong\u003e \u003cp\u003e All authors agree to publish this manuscript in journal of Geomechanics and Geophysics for Geo-Energy and Geo-Resources.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eE.S.L. received a scholarship from the Ministry of Finance of the Republic of Indonesia through the Indonesia Endowment Fund for Education (LPDP, Grant No. 20160622016960) for conducting this study, as part of his doctoral research.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eE.S.L. and H.S. wrote the main manuscript text and E.S.L. prepared the figures and tables. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eWe would like to acknowledge P.T. Pertamina for providing subsurface core data and P.T. Karbindo Abesyapradhi for permission to take surface outcrops data of the Kiliran Jao/Pematang Formation from their quarry for this study. E.S.L. expressed his gratitude for the scholarship from the Ministry of Finance of the Republic of Indonesia through the Indonesia Endowment Fund for Education (LPDP, Grant No. 20160622016960).\u003c/p\u003e\u003ch2\u003eData availability\u003c/h2\u003e \u003cp\u003eThe data used to support the findings of this study are available in the Supplementary Material.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbedi S, Slim M, Hofmann R, Bryndzia T, Ulm FJ (2016) Nanochemo-mechanical signature of organic-rich shales: a coupled indentation\u0026ndash;EDX analysis. 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Cambridge University Press.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"geomechanics-and-geophysics-for-geo-energy-and-geo-resources","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gggg","sideBox":"Learn more about [Geomechanics and Geophysics for Geo-Energy and Geo-Resources](http://link.springer.com/journal/40948)","snPcode":"40948","submissionUrl":"https://submission.nature.com/new-submission/40948/3","title":"Geomechanics and Geophysics for Geo-Energy and Geo-Resources","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Indonesian shale, elastic modulus, creep compliance, strength, anisotropy, mechanical maturity","lastPublishedDoi":"10.21203/rs.3.rs-4364214/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4364214/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMechanical characterization of shales is a fundamental requirement in optimizing shale resource development and transferring development strategies between shale plays. Here we report the laboratory-based mechanical properties of Indonesian shale potentials located within Tertiary basins in active margin settings. Samples from surface-outcrops of lacustrine sediments in the Central Sumatra Basin (CSB) and subsurface-cores of marine deposits in the North Sumatra Basin (NSB) were examined in a series of experiments for their mechanical properties including rock strength, elastic properties, and creep compliance. Results show that the Indonesian shales studied here are generally more compliant than Mesozoic/Paleozoic U.S. shales reported in the literature. Within the context of a binary mixture model (stiff and soft components) used to explain shale elastic properties, these differences in mechanical properties imply that the soft and stiff end-members are more compliant in Indonesian shales. We interpret these differences as the difference in mechanical maturity, which reflects the degree to which mechanical properties have evolved due diagenesis. CSB and NSB samples are considered to be early mature, mechanically, compared to the mechanically mature U.S. shales. Particularly, the Baong Formation samples from the NSB studied here come from a hard-overpressured interval and are mechanically immature, despite their moderate thermal maturity based on vitrinite reflectance. Laboratory results also show no significant differences in mechanical properties between shales deposited in lacustrine (CSB samples) and marine (NSB samples) environments.\u003c/p\u003e","manuscriptTitle":"Mechanical properties of Indonesian organic-rich shales from the Central Sumatra and North Sumatra Basin, and comparison with US shales","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-29 05:43:22","doi":"10.21203/rs.3.rs-4364214/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-17T01:46:28+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-14T17:47:03+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-23T18:03:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"308834429580025087952763856542451227142","date":"2025-03-07T18:45:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"308737798305642651301661110671613062015","date":"2025-03-07T14:30:55+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-06T10:21:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"323951393257103450642605744700627994633","date":"2024-05-20T02:09:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-18T23:28:45+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-18T23:27:38+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-17T01:47:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"Geomechanics and Geophysics for Geo-Energy and Geo-Resources","date":"2024-05-03T12:52:42+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"geomechanics-and-geophysics-for-geo-energy-and-geo-resources","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gggg","sideBox":"Learn more about [Geomechanics and Geophysics for Geo-Energy and Geo-Resources](http://link.springer.com/journal/40948)","snPcode":"40948","submissionUrl":"https://submission.nature.com/new-submission/40948/3","title":"Geomechanics and Geophysics for Geo-Energy and Geo-Resources","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"14766456-c787-420f-87c4-791cb55f6064","owner":[],"postedDate":"May 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-30T16:33:54+00:00","versionOfRecord":{"articleIdentity":"rs-4364214","link":"https://doi.org/10.1007/s40948-025-01028-z","journal":{"identity":"geomechanics-and-geophysics-for-geo-energy-and-geo-resources","isVorOnly":false,"title":"Geomechanics and Geophysics for Geo-Energy and Geo-Resources"},"publishedOn":"2026-03-26 16:10:26","publishedOnDateReadable":"March 26th, 2026"},"versionCreatedAt":"2024-05-29 05:43:22","video":"","vorDoi":"10.1007/s40948-025-01028-z","vorDoiUrl":"https://doi.org/10.1007/s40948-025-01028-z","workflowStages":[]},"version":"v1","identity":"rs-4364214","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4364214","identity":"rs-4364214","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}