Subsurface Structures of the 2016 Mihoub Earthquake Sequence in North-Central Algeria Using Local Earthquake Tomography

Subsurface Structures of the 2016 Mihoub Earthquake Sequence in North-Central Algeria Using Local Earthquake Tomography | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Subsurface Structures of the 2016 Mihoub Earthquake Sequence in North-Central Algeria Using Local Earthquake Tomography kheireddine kameche, beldjoudi hammoud, abacha issam, dabouz ghania This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4455324/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study investigates the Mihoub region within the Blida Mountains of the Tellian Atlas(Abacha et al., 2014), an area prone to earthquakes due to the Africa-Eurasia plate convergence since the Late Cretaceous. We present both the 1910 Aumale earthquake (Ms 6.6 and I0=VIII) and the 2016 seismic sequence (Mw 5.3). Using local seismic tomography (LET) with Local Tomography Software in its twelfth version (LOTOS 12), we analyze velocity anomaly patterns and their correlation with subsurface structures in the Mihoub area. Our dataset includes 503 well-localized aftershocks from the 2016 seismic sequence. Results show consistent patterns, with positive anomalies associated with rigid block structures and negative anomalies associated with basins, recent formations, and tectonic structures. In particular, a NE-SW corridor of low-velocity anomalies aligns with Miocene and Oligocene formations. Mainshock and aftershock epicenters from the 2016 sequence align with the boundary between low and high-velocity anomalies, indicating the Mihoub Fault zone. Fault depth analysis suggests a maximum depth of 8 km, consistent with previous research. Vertical sections confirm similar azimuths and dips of fault segments involved in the 2016 and 2014 mainshocks. This study provides valuable insights into velocity anomaly patterns and their relationship to fault structures, enhancing the understanding of fault systems and seismic hazards in the Mihoub area. Mihoub sequence Blida Mountains Tellian Atlas LOTOS LET Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. Introduction Northern Algeria is located in a seismically active zone due to the convergence of the African and Eurasian tectonic plates, resulting in frequent seismic activity (Fig. 1 a). Recent notable events include the offshore Boumerdes earthquake in 2003 with a magnitude of 6.8(Yelles et al., 2004 ) and a series of earthquakes along the coastline, such as the Algiers earthquake in 2014 Mw 5.5(Benfedda et al., 2017 , Yelles-Chaouche et al., 2017 ), the Aïn Benian earthquake in 1996 M D 5.7(Harbi et al., 2004 ), and the Chenoua earthquake in 1989 ML 6.0(Bounif et al., 2003 ) ( Fig. 1 b ) . In the Blida Mountain range, located between the Mitidja and Beni-Slimane basins (Fig. 1 b), significant earthquakes have also occurred, including the Oued Djer earthquake in 2018 Ml 5.0 (Mohammedi et al., 2020 ) and the Hammam Meloune seismic sequence from 2013 Mw 5.0, 2014 Mw 4.9 to 2016 Ml 4.8(Yelles-Chaouche et al., 2017 ). Of particular interest is the 2016 Mihoub earthquake sequence(Khelif et al., 2018 ), which occurred two mainshocks, the first with a magnitude of M D 4.9 and the second with a magnitude of Mw 5.4, occurring on April 10 and May 28, 2016, respectively. The sequence was triggered by two fault segments. The first fault segment trends E-W and exhibits a strike-slip movement, hosting the initial mainshock of the sequence. The second fault segment, where the largest event of the sequence (Mw 5.4) occurred, is a reverse fault with a small strike-slip component, dipping to the southeast and striking NE-SW(Khelif et al., 2018 ). In addition to these recent events, the region surrounding the Mihoub area has experienced a historically destructive earthquake in Aumale in 1910, with a maximum intensity of I 0 = VIII and Ms 6.6 (Benouar, 1994 ). This event, located near the Mihoub region, highlights the seismic hazard potential of the area and underscores the importance of understanding the subsurface structures in this region. Southeast of Algiers.On May 28, 2016, at 23:54 (UTC), a seismic sequence occurred in the area of Mihoub, situated 60 km southeast of Algiers (Fig. 1 b ) . This sequence was characterized by To provide a unique perspective on the Mihoub region, our research takes a distinct approach by employing local tomography with the LOTOS software (Koulakov, 2009 ). This code has been successfully applied in various geological and tectonic studies in Algeria, including the El Asnam earthquake in 1980 (Bellalem et al., 2015 ), the Boumerdes earthquake in 2003(Kherroubi et al., 2017 ), and the Beni-Ilmane earthquake sequence(Abacha et al., 2014 , Abacha et al., 2023 ). Additionally, LOTOS has been employed globally, such as in volcano structure analysis(Koulakov et al., 2013 ), crustal structure imaging(Totaro et al., 2014 ), transition from seamount to ridge subduction (Dinc et al., 2010 ), velocity and attenuation studies (Koulakov et al., 2010 ), and identification of anomalies in the East African Rift (Jakovlev et al., 2011 ). While other seismotectonic studies have focused on various aspects of the Mihoub region, such as fault analysis or seismicity patterns, our research uses local earthquake tomography to investigate the underlying structures. By using LOTOS, we can clarify the fault zones mentioned in (Semmane et al., 2017 , Khelif et al., 2018 ) and have a more thorough knowledge of the crustal characteristics in the Mihoub region. This alternative approach using local earthquake tomography with a challenging dataset of 500 aftershocks allows us to uncover valuable insights specifically within the study area, thereby enhancing our understanding of the seismology and tectonics of the Mihoub region. 2. Geological settings The Tellian Atlas, situated in northern Algeria, is characterized by its association with the alpine orogeny, a complex geological event. This region exhibits a prominent belt of folds and thrusts, primarily resulting from the ongoing convergence of the African and Eurasian plates at a rate of 4–5 mm per year (Bougrine et al., 2019 ). Importantly, the Tellian Atlas stands out as one of the most seismically active regions in the northern part of the country. When considering the North African segment of the orogeny, two distinct domains are commonly recognized: the internal and external domains. The internal domain, located in the north, encompasses Precambrian and Paleozoic schistose basement rocks, as well as the Cretaceous Flysch nappes (Mauretanian and Massylian) extending towards the coast. On the other hand, the external domain, situated further south, comprises a complex assemblage of thrusts and folds spanning from the Triassic to the Eocene. In our study, we focus on the Mihoub region within the southern part of the Blida Mountains. This area is characterized by ENE-WSW trending folds, along with reverse and thrust faults, as documented by (Bonneton, 1977 , Meghraoui, 1988 ). These geological structures are associated with the series of nappes within the external domain. The geological composition of the Mihoub region includes Paleozoic basement rocks, granites, and mica schists (Delga, 1969 , Bonneton, 1977 ). Notably, the Mihoub region is situated between two basins, namely the Quaternary Mitidja basin to the north and the Beni Slimane basin to the south (Fig. 2 ). The northern boundary of the Beni Slimane basin, where the Mihoub series is located, has long been a point of contention for being the epicenter of the catastrophic 1910 earthquake,(Khelif et al., 2018 ) suggested that 1910 and 2016 events took place on the same northern border of the basin. Thus, the goal of our research is to examine the fundamental structure of the fault zone in the Mihoub region that gave rise to the 2016 seismic series, with a specific focus on the northern boundary of the Beni Slimane basin, which is thought to have been the site of both the 1910 and 2016 events. 3. Data and Methodology 3.1 Data acquisition The seismic events in the Mihoub region were recorded using a combination of eight portable stations and the Algerian Digital Seismic Network (ADSN) permanent stations. The portable stations, equipped with three-component Mark Products L22-3D (f0 = 2.0 Hz) passive short-period sensors, were operational from 30th March to 11th July 2016. The permanent stations employed two types of equipment: a Q330 digitizer paired with either a Kinemetrics SS-1 short-period sensor (f0 = 1.0 Hz) or a Streckeisen STS-2 very broadband sensor, as well as a Geodevice EDAS-24 IP digitizer coupled with a GeoDevice BBVS-60 broadband sensor. Continuous recordings were made at a sampling rate of 100 Hz. The dataset consisted of 550 events, manually picked using the SEISAN GUI interface. Out of these, 475 events with magnitudes ranging from 1.0 to 4.9 (MD) were accurately located using the HYPOINVERSE program (Klein, 2002 ). The location estimates had a root mean square origin time error of less than 0.15 s, horizontal and vertical errors of 1.0 km and 1.5 km respectively, with an azimuthal gap of less than 180°, and a minimum of five recorded arrival times. 3.2 Inversion Parameters The LOTOS code developed by (Koulakov, 2009 ) was used to perform the inversion process. The source location was initialized using a predetermined starting velocity model. The source location was determined using a grid search approach, even when the initial estimate deviated significantly from the actual location. Travel times for the grid search were computed quickly using an interpolation method based on a reference table that included focal depths and epicentral distances. The iterative tomographic inversion process was then initiated, which included source relocation and inversion within the updated 3D velocity model. The source location was determined using 3D ray tracing based on bending, as proposed by (Um and Thurber, 1987 ). The velocity distribution was configured using nodes distributed throughout the study area. Node placement was determined by ray density, with nodes placed closer together in regions of high ray density. The minimum distance between nodes was set at 1 km. Special smoothing equations were employed to connect these nodes during the inversion process. Multiple inversions were performed using different grids with various orientations, such as 0°, 22°, 45°, and 67°. The results were then averaged to minimize the impact of node distribution on the final outcomes. The P and S velocity anomalies, source parameters (four parameters for each source), and station corrections were simultaneously inverted during the inversion process. The sparse matrix inversion was performed using the LSQR technique (Paige and Saunders, 1982 , Nolet, 1987 ). Weights and damping parameters were estimated based on synthetic modeling experiments. It is noteworthy that changing the weights of the source parameters had no significant effect on the velocity model obtained in this study, unlike in other studies. An important tuning parameter in the model smoothing process, controlling variations in recovered velocity values between neighboring nodes, was determined through checkerboard tests. For our study, we adopted the starting velocity model used in the work of (Khelif et al., 2018 ), which utilized a five-layer tabular velocity model. We selected elements with a minimum of five recorded peaks for the inversion analysis. In total, we recorded 475 events, with 3057P peaks and 2301 S peaks. Table 1 provides details on the estimated residual values and variance reduction across the five iterations. Table 1 Values of standard deviation variance reduction for the P and S data after the step of source locations at different iterations Iteration P-residual deviation, s P-residual reduction, % S-residual deviation, s S-residual reduction, % 1 0.135 0.190 0 0 2 0.112 0.144 17.03 24.02 3 0.103 0.136 23.46 28.21 4 0.100 0.134 25.69 29.37 5 0.090 0.133 26.39 29.40 3.3 Synthetic Tests To assess the resolution of the recovered velocity distribution and determine the values of the inversion parameters, multiple synthetic tests were conducted. The synthetic model used in these tests consisted of anomalies superimposed on a "real" reference model. Various types of anomalies, including checkerboards and free-form anomalies defined in both map view and vertical sections, were created. Synthetic data were computed using the same ray path configurations as the observed data, employing 3D ray tracing techniques. Synthetic times were then perturbed with random noise to achieve a similar variance reduction as observed in the inversion of the actual data. It is crucial to note that the sources were not established when developing the synthetic model. Therefore, instances with significant synthetic anomalies may have resulted in substantial skewing of the initial source locations compared to the actual locations. Furthermore, the parameterization chosen for the inversion had no impact on how the synthetic model was specified in this study. Several artificial tests using checkerboard anomalies were conducted to evaluate horizontal resolution. The reconstruction results for three different models with varying pattern sizes and spacing (6+5 km, 4+4 km, and 3+3 km) are presented in Fig. 3 . These anomalies remained consistent across depths, with amplitudes of ±5%. Synthetic data were computed using 3D ray tracing based on the bending algorithm (Um and Thurber, 1987). After generating the synthetic dataset, the source locations were disregarded, and the reconstruction of the synthetic model was carried out using the same procedures as in the case of processing the observed data, including the estimation of the initial source location using the starting 1D model. The values of free parameters (damping, smoothing, grid spacing, etc.) used in these tests were similar to those used for computing the main model. The results of the reconstructed P and S anomalies at a depth of 1 km indicate that the (6+5) checkerboard test (Model_01) yielded good results, as the different anomalies for both P and S waves could be identified. The (4+4) checkerboard test (Model_02) remained coherent, with only a few instances of non-conforming results. However, the (3+3) checkerboard test (Model_03) showed less coherence and had several boundary irregularities. This variability can be explained by the absence of rays at the boundaries of the map outside the aftershock zone. Additionally, the tests demonstrate the limit of our model to solve small anomalies. Vertical resolution was also tested by defining three anomalies of 4×2 km in size located at depth intervals of 0–3 km along section 1 ( Fig. 4 ). The amplitudes of these anomalies were ±5%. The test showed acceptable results for the left and central anomalies, while indicating low resolution for the right anomaly. To investigate the impact of smearing, six different tests were conducted involving single synthetic anomalies measuring 5×5 km in lateral size placed at various locations within the study area. The amplitude of these anomalies was consistent at 5%, and they extended without limitation in depth. Examples of reconstructions for these six models are displayed in Fig. 5. When the pattern was positioned within the aftershock area (referred to as model "Single_2"), the reconstruction accurately delineated the boundaries of the anomaly. However, for all other cases where the patterns were placed outside the central area, the reconstructed anomalies exhibited significant smearing in the radial directions corresponding to the ray path ( Fig. 6 ). It is important to consider this smearing effect when interpreting the results of data inversion. 4. Results and Discussion The velocity anomaly patterns within our study area are shown in horizontal and vertical sections ( Figs. 7 and 8 ). Three horizontal sections were selected at depths of 2 km, 4 km, and 8 km, covering the study area with nodes based on ray density. While our model extends to a depth of 20 km, we focused on the first 10 km, where the majority of events occur and discernible structures are present, with velocity anomalies of about 20%. The horizontal sections in Fig. 7 show coherent patterns at different depths, indicating a correlation between velocity anomalies and underlying geological formations. Positive anomalies (high anomalies) correspond to rigid block structures, while negative anomalies (low anomalies) correspond to basins, younger formations, and maybe some tectonic structures. Specific anomalies are noteworthy; for example, low-velocity P- and S-wave anomalies (1) and (5) form an NE-SW corridor coincident with Miocene and Oligocene formations. An additional low-velocity anomaly, probably corresponding to the Beni-Slimane basin, is observed further south. The E-W trending anomaly (2) aligns with the 2014 earthquake, suggesting that it represents the fault zone responsible for this event. The distinct high-anomaly (3), which marks a boundary between low anomalies (2) and (1) and (5), is visible at depths of 2 km and 4 km, but disappears at 8 km. Other high-velocity anomalies can be attributed to hard rock formations in the Blida mountain range that are not influenced by regional stresses. Mainshock and aftershock epicenters from the 2016 Mihoub earthquake sequence are concentrated along the boundary between low-velocity anomalies (1) and (5) partially intersecting high-velocity anomaly (3) and low-velocity anomaly (1) ( Fig. 7) . This boundary coincides with the geological contact between Miocene (anomaly 1) and Campanian (anomalies 3) formations, interpreted as the Mihoub fault. Anomaly (2) intersects anomaly (1) at a depth of 8 km, indicating the depth limit of the fault, consistent with previous research Khelif et al. (2018). The 2014 earthquake (blue star) occurred at the boundary between anomalies (2) and (3), consistent with the fault segment associated with this event (Semmane et al., 2017). Vertical sections highlight key features ( Fig. 8 ). The first profile (BB') trends southeast to northwest, nearly perpendicular to the folded structures of the Tellian Atlas. The second profile (AA') runs north-south, intersecting anomalies 1, 2 and 3, as well as the concentrated area of the aftershock cluster (see Fig. 8 ). Section BB' reveals two V-shaped fault segments. The first segment corresponds to the Mw=5.4 shock of May 28, 2016, which dips at an angle of 40° in the ENE-WSW direction. The following segment corresponds to the second main shock, which occurred on April 10, 2016, with a magnitude of Mw=4.9, dipping at a 90° angle in an east-west direction. Section AA' shows a north-south profile intersecting the main shock of November 15, 2014. This section illustrates the same fault segments observed in profile BB', along with the fault segment that hosted the 2014 earthquake, which dips at an angle of 55° in a roughly east-west direction. Our results are consistent with previous studies and confirm the fault segments identified by (Semmane et al., 2017, Khelif et al., 2018). However, some anomalies remain unidentified due to limited resolution and ray coverage, and the smearing effect of ray paths to seismic stations should be considered. Additional information is provided by the ray path, shown in Fig. 6 , compared to the anomaly maps. 4. Conclusion This study provides insight into velocity anomaly models in the Mihoub area, focusing on both horizontal and vertical sections. The results show consistent patterns and correlations between velocity anomalies and underlying geological formations. Horizontal sections show distinct characteristics with positive anomalies associated with rigid block structures and negative anomalies corresponding to basins and younger geological formations. In particular, the NE-SW corridor formed by low-velocity anomalies (1) and (5) aligns perfectly with relatively recent Miocene and Oligocene formations. The presence of high-velocity anomalies in the Blida Mountains supports these observations. The epicenters of the mainshocks and aftershocks of the 2016 Mihoub earthquake sequence are located along the boundary between the low-velocity and high-velocity anomalies. This boundary coincides with a geological contact between Miocene and Campanian formations, leading to the identification of the Mihoub fault. Depth analysis suggests that the fault does not extend beyond 8 km, consistent with previous research. Vertical sections provide further insight into the fault segments, with profile BB' revealing two V-shaped fault segments corresponding to the main shocks of the 2016 sequence. Profile AA' intersects several fault segments, including the one that hosted the 2014 earthquake. These results are consistent with previous studies in the Mihoub area, confirming the presence of fault segments with similar azimuths and dips. Our study sheds light on velocity anomaly models and their relationship to the underlying geological formations in the study area. These results improve the understanding of the fault system and seismic activity, and provide a basis for future research and seismic hazard assessment. Declarations Author Contribution K.K. A.I. and B.H. wrote the main manuscript textA.I. prepared figure 1 K.K. prepared other figuresAll authors reviewed the manuscript. References ABACHA, I., BENDJAMA, H., BOULAHIA, O., YELLES-CHAOUCHE, A., ROUBECHE, K., RAHMANI, S. T.-E., MELAIM, M. A. & TIKHAMARINE, E.-M. 2023. Fluid-driven processes triggering the 2010 Beni-Ilmane earthquake sequence (Algeria): evidence from local earthquake tomography and 4D Vp/Vs models. Journal of Seismology, 27 , 77-94. ABACHA, I., KOULAKOV, I., SEMMANE, F. & YELLES-CHAOUCHE, A. K. 2014. 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Pure and Applied Geophysics, 174 , 1601-1614. YELLES, A., DOMZIG, A., DÉVERCHÈRE, J., BRACÈNE, R., DE LÉPINAY, B. M., STRZERZYNSKI, P., BERTRAND, G., BOUDIAF, A., WINTER, T. & KHERROUBI, A. 2009. Plio-Quaternary reactivation of the Neogene margin off NW Algiers, Algeria: the Khayr al Din bank. Tectonophysics, 475 , 98-116. YELLES, K., LAMMALI, K., MAHSAS, A., CALAIS, E. & BRIOLE, P. 2004. Coseismic deformation of the May 21st, 2003, Mw= 6.8 Boumerdes earthquake, Algeria, from GPS measurements. Geophysical Research Letters, 31. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-4455324","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":308435963,"identity":"e5cbc237-85cf-4d0f-a675-9956a6dcdf3e","order_by":0,"name":"kheireddine kameche","email":"data:image/png;base64,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","orcid":"","institution":"Centre de Recherche en Astronomie Astrophysique et Géophysique","correspondingAuthor":true,"prefix":"","firstName":"kheireddine","middleName":"","lastName":"kameche","suffix":""},{"id":308435967,"identity":"f7b41bf2-9946-430e-925d-031759af21d7","order_by":1,"name":"beldjoudi hammoud","email":"","orcid":"","institution":"Centre de Recherche en Astronomie Astrophysique et Géophysique","correspondingAuthor":false,"prefix":"","firstName":"beldjoudi","middleName":"","lastName":"hammoud","suffix":""},{"id":308435968,"identity":"f8202b6c-6471-4ed0-99b7-6df4fb0a9349","order_by":2,"name":"abacha issam","email":"","orcid":"","institution":"Centre de Recherche en Astronomie Astrophysique et Géophysique","correspondingAuthor":false,"prefix":"","firstName":"abacha","middleName":"","lastName":"issam","suffix":""},{"id":308435974,"identity":"9c170c32-59a0-41f6-8f12-75431c84f637","order_by":3,"name":"dabouz ghania","email":"","orcid":"","institution":"Centre de Recherche en Astronomie Astrophysique et Géophysique","correspondingAuthor":false,"prefix":"","firstName":"dabouz","middleName":"","lastName":"ghania","suffix":""}],"badges":[],"createdAt":"2024-05-21 13:51:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4455324/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4455324/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":57642949,"identity":"ef6a8287-d056-4b71-abfa-10045b010202","added_by":"auto","created_at":"2024-06-03 18:06:31","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":3568645,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(a) \u003c/strong\u003eConvergence velocities of the Eurasia-Africa plate (depicted by black arrows) are derived from (Bougrine et al., 2019) . The red box outlines the north-central part of Algeria (Algiers seismotectonic zone). \u003cstrong\u003e(b)\u003c/strong\u003eSeismtectonic map of the Algiers region displaying recent seismicity (2007-2016) recorded by the ADSN network, including the focal mechanisms of the main earthquakes that occurred over a 30-year period from 1988. The focal mechanisms associated with the 2016 Mihoub seismic sequence (the focus of this study) are highlighted in red. The red line represents the coastline, and the black lines depict the main active faults(Meghraoui, 1988, Boudiaf, 1996, Yelles et al., 2009).\u003c/p\u003e","description":"","filename":"fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4455324/v1/7009d2c80eb58f58766e81d4.jpg"},{"id":57642540,"identity":"71f8fe4b-f148-436b-9f41-df0cb495676a","added_by":"auto","created_at":"2024-06-03 17:58:31","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2316803,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003egeological map of study area. \u003c/strong\u003eDigitalized from geological map Ain Bessam region (Repal, 1969)\u003c/p\u003e","description":"","filename":"fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4455324/v1/ea5a3d22e112b8efd781ff45.jpg"},{"id":57642543,"identity":"41ccfe0c-6703-48f3-92c2-2142232885a8","added_by":"auto","created_at":"2024-06-03 17:58:31","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":3033316,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eResults of the checkerboard tests for three models with different sizes of anomalies. \u003c/strong\u003eThe configurations of the synthetic patterns are indicated with black contour lines. The amplitudes of anomalies for all models are ±5%. The reconstruction results are shown for the depth of 6 km. Triangles indicate seismic stations.\u003c/p\u003e","description":"","filename":"fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4455324/v1/a411d3791eb871884318f4aa.jpg"},{"id":57642545,"identity":"c7c16a6b-5db4-497d-818a-32351c9f9089","added_by":"auto","created_at":"2024-06-03 17:58:31","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1028881,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eResults of vertical checkerboard apply in section AA’. \u003c/strong\u003eGray contour line indicates the shape of the true model. The amplitudes of the anomalies are ±5%\u003c/p\u003e","description":"","filename":"fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4455324/v1/50a687a33e98e7fe69c0fdf6.jpg"},{"id":57642541,"identity":"879a82b9-6970-4c87-b6ba-70fcfa722dcf","added_by":"auto","created_at":"2024-06-03 17:58:31","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2801406,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ereconstruction for six models with single synthetic anomaly 5+5 placed in different parts of study region to learn more about the impact of smearing. \u003c/strong\u003eThe configurations of the synthetic patterns are indicated with black contour lines. The amplitudes of the anomaly are ±5%.\u003c/p\u003e","description":"","filename":"fig5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4455324/v1/68f0b6c1a460a086f7ba2b5f.jpg"},{"id":57642544,"identity":"f88de92a-4b75-4890-aff9-62461fcc3c0a","added_by":"auto","created_at":"2024-06-03 17:58:31","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":969173,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePath of the P and S rays for the source locations after five iterations of tomographic inversion.\u003c/strong\u003e green triangles are the stations; red dots are the events.\u003c/p\u003e","description":"","filename":"fig6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4455324/v1/b71d68192587ee72f1f995a2.jpg"},{"id":57642547,"identity":"b4b17c6a-8514-4ea1-8582-e9d964e0736a","added_by":"auto","created_at":"2024-06-03 17:58:31","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":2670400,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eP- and S-velocity anomalies in horizontal sections at 2, 4 and 8 km depth. \u003c/strong\u003eDots represent the locations of events near the corresponding section. Triangles show the stations, red stars are the epicenters of main shocks 2016 and red star indicate main shock 2014.\u003c/p\u003e","description":"","filename":"fig7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4455324/v1/654807915f1abcd34ca94251.jpg"},{"id":57642546,"identity":"e3431590-8a9f-4750-8215-3834fcf6f966","added_by":"auto","created_at":"2024-06-03 17:58:31","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":1791661,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistributions of P- wave anomalies in the vertical sections\u003c/strong\u003e. Source locations at distances of less than 5 km from the profiles are shown with black dots. Locations of the profiles are shown in Fig.7. Possible locations of faults based on the distributions of seismicity and seismic anomalies are shown with green lines. Red stars are the epicenters of main shocks 2016 and red star indicate main shock 2014.\u003c/p\u003e","description":"","filename":"fig8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4455324/v1/d070b2067afd93dffb3b0ad1.jpg"},{"id":68203896,"identity":"d763248d-f25d-4f31-b774-5c1044302577","added_by":"auto","created_at":"2024-11-04 16:02:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":18728198,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4455324/v1/93eda200-34b5-451a-9149-f5a3afb027df.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Subsurface Structures of the 2016 Mihoub Earthquake Sequence in North-Central Algeria Using Local Earthquake Tomography","fulltext":[{"header":"1. Introduction","content":"\u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eNorthern Algeria is located in a seismically active zone due to the convergence of the African and Eurasian tectonic plates, resulting in frequent seismic activity (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ea). Recent notable events include the offshore Boumerdes earthquake in 2003 with a magnitude of 6.8(Yelles et al., \u003cspan class=\"CitationRef\"\u003e2004\u003c/span\u003e) and a series of earthquakes along the coastline, such as the Algiers earthquake in 2014 Mw 5.5(Benfedda et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e, Yelles-Chaouche et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e), the A\u0026iuml;n Benian earthquake in 1996 M\u003csub\u003eD\u003c/sub\u003e 5.7(Harbi et al., \u003cspan class=\"CitationRef\"\u003e2004\u003c/span\u003e), and the Chenoua earthquake in 1989 ML 6.0(Bounif et al., \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e) \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eb\u003cstrong\u003e)\u003c/strong\u003e. In the Blida Mountain range, located between the Mitidja and Beni-Slimane basins (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eb), significant earthquakes have also occurred, including the Oued Djer earthquake in 2018 Ml 5.0 (Mohammedi et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e) and the Hammam Meloune seismic sequence from 2013 Mw 5.0, 2014 Mw 4.9 to 2016 Ml 4.8(Yelles-Chaouche et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e). Of particular interest is the 2016 Mihoub earthquake sequence(Khelif et al., \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e), which occurred two mainshocks, the first with a magnitude of M\u003csub\u003eD\u003c/sub\u003e 4.9 and the second with a magnitude of Mw 5.4, occurring on April 10 and May 28, 2016, respectively. The sequence was triggered by two fault segments. The first fault segment trends E-W and exhibits a strike-slip movement, hosting the initial mainshock of the sequence. The second fault segment, where the largest event of the sequence (Mw 5.4) occurred, is a reverse fault with a small strike-slip component, dipping to the southeast and striking NE-SW(Khelif et al., \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e). In addition to these recent events, the region surrounding the Mihoub area has experienced a historically destructive earthquake in Aumale in 1910, with a maximum intensity of I\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;VIII and Ms 6.6 (Benouar, \u003cspan class=\"CitationRef\"\u003e1994\u003c/span\u003e). This event, located near the Mihoub region, highlights the seismic hazard potential of the area and underscores the importance of understanding the subsurface structures in this region. Southeast of Algiers.On May 28, 2016, at 23:54 (UTC), a seismic sequence occurred in the area of Mihoub, situated 60 km southeast of Algiers (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eb\u003cstrong\u003e)\u003c/strong\u003e. This sequence was characterized by To provide a unique perspective on the Mihoub region, our research takes a distinct approach by employing local tomography with the LOTOS software (Koulakov, \u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e). This code has been successfully applied in various geological and tectonic studies in Algeria, including the El Asnam earthquake in 1980 (Bellalem et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e), the Boumerdes earthquake in 2003(Kherroubi et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e), and the Beni-Ilmane earthquake sequence(Abacha et al., \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e, Abacha et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). Additionally, LOTOS has been employed globally, such as in volcano structure analysis(Koulakov et al., \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e), crustal structure imaging(Totaro et al., \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e), transition from seamount to ridge subduction (Dinc et al., \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e), velocity and attenuation studies (Koulakov et al., \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e), and identification of anomalies in the East African Rift (Jakovlev et al., \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eWhile other seismotectonic studies have focused on various aspects of the Mihoub region, such as fault analysis or seismicity patterns, our research uses local earthquake tomography to investigate the underlying structures. By using LOTOS, we can clarify the fault zones mentioned in (Semmane et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e, Khelif et al., \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e) and have a more thorough knowledge of the crustal characteristics in the Mihoub region. This alternative approach using local earthquake tomography with a challenging dataset of 500 aftershocks allows us to uncover valuable insights specifically within the study area, thereby enhancing our understanding of the seismology and tectonics of the Mihoub region.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"2. Geological settings","content":"\u003cp\u003eThe Tellian Atlas, situated in northern Algeria, is characterized by its association with the alpine orogeny, a complex geological event. This region exhibits a prominent belt of folds and thrusts, primarily resulting from the ongoing convergence of the African and Eurasian plates at a rate of 4\u0026ndash;5 mm per year (Bougrine et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Importantly, the Tellian Atlas stands out as one of the most seismically active regions in the northern part of the country.\u003c/p\u003e \u003cp\u003eWhen considering the North African segment of the orogeny, two distinct domains are commonly recognized: the internal and external domains. The internal domain, located in the north, encompasses Precambrian and Paleozoic schistose basement rocks, as well as the Cretaceous Flysch nappes (Mauretanian and Massylian) extending towards the coast. On the other hand, the external domain, situated further south, comprises a complex assemblage of thrusts and folds spanning from the Triassic to the Eocene.\u003c/p\u003e \u003cp\u003eIn our study, we focus on the Mihoub region within the southern part of the Blida Mountains. This area is characterized by ENE-WSW trending folds, along with reverse and thrust faults, as documented by (Bonneton, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1977\u003c/span\u003e, Meghraoui, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1988\u003c/span\u003e). These geological structures are associated with the series of nappes within the external domain. The geological composition of the Mihoub region includes Paleozoic basement rocks, granites, and mica schists (Delga, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1969\u003c/span\u003e, Bonneton, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1977\u003c/span\u003e). Notably, the Mihoub region is situated between two basins, namely the Quaternary Mitidja basin to the north and the Beni Slimane basin to the south (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The northern boundary of the Beni Slimane basin, where the Mihoub series is located, has long been a point of contention for being the epicenter of the catastrophic 1910 earthquake,(Khelif et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) suggested that 1910 and 2016 events took place on the same northern border of the basin. Thus, the goal of our research is to examine the fundamental structure of the fault zone in the Mihoub region that gave rise to the 2016 seismic series, with a specific focus on the northern boundary of the Beni Slimane basin, which is thought to have been the site of both the 1910 and 2016 events.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"3. Data and Methodology","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Data acquisition\u003c/h2\u003e \u003cp\u003eThe seismic events in the Mihoub region were recorded using a combination of eight portable stations and the Algerian Digital Seismic Network (ADSN) permanent stations. The portable stations, equipped with three-component Mark Products L22-3D (f0\u0026thinsp;=\u0026thinsp;2.0 Hz) passive short-period sensors, were operational from 30th March to 11th July 2016. The permanent stations employed two types of equipment: a Q330 digitizer paired with either a Kinemetrics SS-1 short-period sensor (f0\u0026thinsp;=\u0026thinsp;1.0 Hz) or a Streckeisen STS-2 very broadband sensor, as well as a Geodevice EDAS-24 IP digitizer coupled with a GeoDevice BBVS-60 broadband sensor. Continuous recordings were made at a sampling rate of 100 Hz.\u003c/p\u003e \u003cp\u003eThe dataset consisted of 550 events, manually picked using the SEISAN GUI interface. Out of these, 475 events with magnitudes ranging from 1.0 to 4.9 (MD) were accurately located using the HYPOINVERSE program (Klein, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). The location estimates had a root mean square origin time error of less than 0.15 s, horizontal and vertical errors of 1.0 km and 1.5 km respectively, with an azimuthal gap of less than 180\u0026deg;, and a minimum of five recorded arrival times.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Inversion Parameters\u003c/h2\u003e \u003cp\u003eThe LOTOS code developed by (Koulakov, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) was used to perform the inversion process. The source location was initialized using a predetermined starting velocity model. The source location was determined using a grid search approach, even when the initial estimate deviated significantly from the actual location. Travel times for the grid search were computed quickly using an interpolation method based on a reference table that included focal depths and epicentral distances. The iterative tomographic inversion process was then initiated, which included source relocation and inversion within the updated 3D velocity model.\u003c/p\u003e \u003cp\u003eThe source location was determined using 3D ray tracing based on bending, as proposed by (Um and Thurber, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1987\u003c/span\u003e). The velocity distribution was configured using nodes distributed throughout the study area. Node placement was determined by ray density, with nodes placed closer together in regions of high ray density. The minimum distance between nodes was set at 1 km. Special smoothing equations were employed to connect these nodes during the inversion process. Multiple inversions were performed using different grids with various orientations, such as 0\u0026deg;, 22\u0026deg;, 45\u0026deg;, and 67\u0026deg;. The results were then averaged to minimize the impact of node distribution on the final outcomes.\u003c/p\u003e \u003cp\u003eThe P and S velocity anomalies, source parameters (four parameters for each source), and station corrections were simultaneously inverted during the inversion process. The sparse matrix inversion was performed using the LSQR technique (Paige and Saunders, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1982\u003c/span\u003e, Nolet, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1987\u003c/span\u003e). Weights and damping parameters were estimated based on synthetic modeling experiments. It is noteworthy that changing the weights of the source parameters had no significant effect on the velocity model obtained in this study, unlike in other studies. An important tuning parameter in the model smoothing process, controlling variations in recovered velocity values between neighboring nodes, was determined through checkerboard tests.\u003c/p\u003e \u003cp\u003eFor our study, we adopted the starting velocity model used in the work of (Khelif et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), which utilized a five-layer tabular velocity model. We selected elements with a minimum of five recorded peaks for the inversion analysis. In total, we recorded 475 events, with 3057P peaks and 2301 S peaks. \u003cb\u003eTable\u0026nbsp;1\u003c/b\u003e provides details on the estimated residual values and variance reduction across the five iterations.\u003c/p\u003e \u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e Values of standard deviation variance reduction for the P and S data after the step of source locations at different iterations\u003c/p\u003e\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\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 \u003cp\u003eIteration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP-residual deviation, s\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP-residual\u003c/p\u003e \u003cp\u003ereduction, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS-residual deviation, s\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eS-residual\u003c/p\u003e \u003cp\u003ereduction, %\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.135\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.190\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.112\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.144\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e17.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e24.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.103\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.136\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e23.46\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e28.21\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.100\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.134\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e25.69\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e29.37\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.090\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.133\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e26.39\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e29.40\u003c/b\u003e\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\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Synthetic Tests\u003c/h2\u003e \u003cp\u003eTo assess the resolution of the recovered velocity distribution and determine the values of the inversion parameters, multiple synthetic tests were conducted. The synthetic model used in these tests consisted of anomalies superimposed on a \"real\" reference model. Various types of anomalies, including checkerboards and free-form anomalies defined in both map view and vertical sections, were created. Synthetic data were computed using the same ray path configurations as the observed data, employing 3D ray tracing techniques. Synthetic times were then perturbed with random noise to achieve a similar variance reduction as observed in the inversion of the actual data.\u003c/p\u003e \u003cp\u003eIt is crucial to note that the sources were not established when developing the synthetic model. Therefore, instances with significant synthetic anomalies may have resulted in substantial skewing of the initial source locations compared to the actual locations. Furthermore, the parameterization chosen for the inversion had no impact on how the synthetic model was specified in this study.\u003c/p\u003e \u003cp\u003eSeveral artificial tests using checkerboard anomalies were conducted to evaluate horizontal resolution. The reconstruction results for three different models with varying pattern sizes and spacing (6+5 km, 4+4 km, and 3+3 km) are presented in \u003cstrong\u003eFig. 3\u003c/strong\u003e. These anomalies remained consistent across depths, with amplitudes of \u0026plusmn;5%. Synthetic data were computed using 3D ray tracing based on the bending algorithm (Um and Thurber, 1987). After generating the synthetic dataset, the source locations were disregarded, and the reconstruction of the synthetic model was carried out using the same procedures as in the case of processing the observed data, including the estimation of the initial source location using the starting 1D model. The values of free parameters (damping, smoothing, grid spacing, etc.) used in these tests were similar to those used for computing the main model.\u003c/p\u003e\n\u003cp\u003eThe results of the reconstructed P and S anomalies at a depth of 1 km indicate that the (6+5) checkerboard test (Model_01) yielded good results, as the different anomalies for both P and S waves could be identified. The (4+4) checkerboard test (Model_02) remained coherent, with only a few instances of non-conforming results. However, the (3+3) checkerboard test (Model_03) showed less coherence and had several boundary irregularities. This variability can be explained by the absence of rays at the boundaries of the map outside the aftershock zone. Additionally, the tests demonstrate the limit of our model to solve small anomalies. Vertical resolution was also tested by defining three anomalies of 4\u0026times;2 km in size located at depth intervals of 0\u0026ndash;3 km along section 1 (\u003cstrong\u003eFig. 4\u003c/strong\u003e). The amplitudes of these anomalies were \u0026plusmn;5%. The test showed acceptable results for the left and central anomalies, while indicating low resolution for the right anomaly.\u003c/p\u003e\n\u003cp\u003eTo investigate the impact of smearing, six different tests were conducted involving single synthetic anomalies measuring 5\u0026times;5 km in lateral size placed at various locations within the study area. The amplitude of these anomalies was consistent at 5%, and they extended without limitation in depth. Examples of reconstructions for these six models are displayed in \u003cstrong\u003eFig. 5.\u003c/strong\u003e When the pattern was positioned within the aftershock area (referred to as model \u0026quot;Single_2\u0026quot;), the reconstruction accurately delineated the boundaries of the anomaly. However, for all other cases where the patterns were placed outside the central area, the reconstructed anomalies exhibited significant smearing in the radial directions corresponding to the ray path (\u003cstrong\u003eFig. 6\u003c/strong\u003e). It is important to consider this smearing effect when interpreting the results of data inversion.\u003c/p\u003e"},{"header":"4. Results and Discussion","content":"\u003cp\u003eThe velocity anomaly patterns within our study area are shown in horizontal and vertical sections (\u003cstrong\u003eFigs. 7 and 8\u003c/strong\u003e). Three horizontal sections were selected at depths of 2 km, 4 km, and 8 km, covering the study area with nodes based on ray density. While our model extends to a depth of 20 km, we focused on the first 10 km, where the majority of events occur and discernible structures are present, with velocity anomalies of about 20%.\u003c/p\u003e\n\u003cp\u003eThe horizontal sections in \u003cstrong\u003eFig. 7\u003c/strong\u003e show coherent patterns at different depths, indicating a correlation between velocity anomalies and underlying geological formations. Positive anomalies (high anomalies) correspond to rigid block structures, while negative anomalies (low anomalies) correspond to basins, younger formations, and maybe some tectonic structures. Specific anomalies are noteworthy; for example, low-velocity P- and S-wave anomalies (1) and (5) form an NE-SW corridor coincident with Miocene and Oligocene formations. An additional low-velocity anomaly, probably corresponding to the Beni-Slimane basin, is observed further south. The E-W trending anomaly (2) aligns with the 2014 earthquake, suggesting that it represents the fault zone responsible for this event. The distinct high-anomaly (3), which marks a boundary between low anomalies (2) and (1) and (5), is visible at depths of 2 km and 4 km, but disappears at 8 km. Other high-velocity anomalies can be attributed to hard rock formations in the Blida mountain range that are not influenced by regional stresses.\u003c/p\u003e\n\u003cp\u003eMainshock and aftershock epicenters from the 2016 Mihoub earthquake sequence are concentrated along the boundary between low-velocity anomalies (1) and (5) partially intersecting high-velocity anomaly (3) and low-velocity anomaly (1) (\u003cstrong\u003eFig. 7)\u003c/strong\u003e. This boundary coincides with the geological contact between Miocene (anomaly 1) and Campanian (anomalies 3) formations, interpreted as the Mihoub fault. Anomaly (2) intersects anomaly (1) at a depth of 8 km, indicating the depth limit of the fault, consistent with previous research Khelif et al. (2018). The 2014 earthquake (blue star) occurred at the boundary between anomalies (2) and (3), consistent with the fault segment associated with this event (Semmane et al., 2017).\u003c/p\u003e\n\u003cp\u003eVertical sections highlight key features (\u003cstrong\u003eFig. 8\u003c/strong\u003e). The first profile (BB\u0026apos;) trends southeast to northwest, nearly perpendicular to the folded structures of the Tellian Atlas. The second profile (AA\u0026apos;) runs north-south, intersecting anomalies 1, 2 and 3, as well as the concentrated area of the aftershock cluster (see \u003cstrong\u003eFig. 8\u003c/strong\u003e). Section BB\u0026apos; reveals two V-shaped fault segments. The first segment corresponds to the Mw=5.4 shock of May 28, 2016, which dips at an angle of 40\u0026deg; in the ENE-WSW direction. The following segment corresponds to the second main shock, which occurred on April 10, 2016, with a magnitude of Mw=4.9, dipping at a 90\u0026deg; angle in an east-west direction. Section AA\u0026apos; shows a north-south profile intersecting the main shock of November 15, 2014. This section illustrates the same fault segments observed in profile BB\u0026apos;, along with the fault segment that hosted the 2014 earthquake, which dips at an angle of 55\u0026deg; in a roughly east-west direction.\u003c/p\u003e\n\u003cp\u003eOur results are consistent with previous studies and confirm the fault segments identified by (Semmane et al., 2017, Khelif et al., 2018). However, some anomalies remain unidentified due to limited resolution and ray coverage, and the smearing effect of ray paths to seismic stations should be considered. Additional information is provided by the ray path, shown in \u003cstrong\u003eFig. 6\u003c/strong\u003e, compared to the anomaly maps.\u003c/p\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eThis study provides insight into velocity anomaly models in the Mihoub area, focusing on both horizontal and vertical sections. The results show consistent patterns and correlations between velocity anomalies and underlying geological formations.\u003c/p\u003e \u003cp\u003eHorizontal sections show distinct characteristics with positive anomalies associated with rigid block structures and negative anomalies corresponding to basins and younger geological formations. In particular, the NE-SW corridor formed by low-velocity anomalies (1) and (5) aligns perfectly with relatively recent Miocene and Oligocene formations. The presence of high-velocity anomalies in the Blida Mountains supports these observations.\u003c/p\u003e \u003cp\u003eThe epicenters of the mainshocks and aftershocks of the 2016 Mihoub earthquake sequence are located along the boundary between the low-velocity and high-velocity anomalies. This boundary coincides with a geological contact between Miocene and Campanian formations, leading to the identification of the Mihoub fault. Depth analysis suggests that the fault does not extend beyond 8 km, consistent with previous research.\u003c/p\u003e \u003cp\u003eVertical sections provide further insight into the fault segments, with profile BB' revealing two V-shaped fault segments corresponding to the main shocks of the 2016 sequence. Profile AA' intersects several fault segments, including the one that hosted the 2014 earthquake. These results are consistent with previous studies in the Mihoub area, confirming the presence of fault segments with similar azimuths and dips.\u003c/p\u003e \u003cp\u003eOur study sheds light on velocity anomaly models and their relationship to the underlying geological formations in the study area. These results improve the understanding of the fault system and seismic activity, and provide a basis for future research and seismic hazard assessment.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eK.K. A.I. and B.H. wrote the main manuscript textA.I. prepared figure 1 K.K. prepared other figuresAll authors reviewed the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eABACHA, I., BENDJAMA, H., BOULAHIA, O., YELLES-CHAOUCHE, A., ROUBECHE, K., RAHMANI, S. T.-E., MELAIM, M. A. \u0026amp; TIKHAMARINE, E.-M. 2023. 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Coseismic deformation of the May 21st, 2003, Mw= 6.8 Boumerdes earthquake, Algeria, from GPS measurements. \u003cem\u003eGeophysical Research Letters,\u003c/em\u003e 31.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Mihoub sequence, Blida Mountains, Tellian Atlas, LOTOS, LET","lastPublishedDoi":"10.21203/rs.3.rs-4455324/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4455324/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study investigates the Mihoub region within the Blida Mountains of the Tellian Atlas(Abacha et al., 2014), an area prone to earthquakes due to the Africa-Eurasia plate convergence since the Late Cretaceous. We present both the 1910 Aumale earthquake (Ms 6.6 and I0=VIII) and the 2016 seismic sequence (Mw 5.3). Using local seismic tomography (LET) with Local Tomography Software in its twelfth version (LOTOS 12), we analyze velocity anomaly patterns and their correlation with subsurface structures in the Mihoub area. Our dataset includes 503 well-localized aftershocks from the 2016 seismic sequence. Results show consistent patterns, with positive anomalies associated with rigid block structures and negative anomalies associated with basins, recent formations, and tectonic structures. In particular, a NE-SW corridor of low-velocity anomalies aligns with Miocene and Oligocene formations. Mainshock and aftershock epicenters from the 2016 sequence align with the boundary between low and high-velocity anomalies, indicating the Mihoub Fault zone. Fault depth analysis suggests a maximum depth of 8 km, consistent with previous research. Vertical sections confirm similar azimuths and dips of fault segments involved in the 2016 and 2014 mainshocks. This study provides valuable insights into velocity anomaly patterns and their relationship to fault structures, enhancing the understanding of fault systems and seismic hazards in the Mihoub area.\u003c/p\u003e","manuscriptTitle":"Subsurface Structures of the 2016 Mihoub Earthquake Sequence in North-Central Algeria Using Local Earthquake Tomography","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-03 17:58:26","doi":"10.21203/rs.3.rs-4455324/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"30f6e64f-4494-4945-bcf0-0b26159dc2dd","owner":[],"postedDate":"June 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-11-04T15:54:19+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-03 17:58:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4455324","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4455324","identity":"rs-4455324","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}