Advancing Geothermal Exploration With 2D Magnetotelluric and 3D Modeling: Case Study From Mount Parakasak, Banten, Indonesia

Advancing Geothermal Exploration With 2D Magnetotelluric and 3D Modeling: Case Study From Mount Parakasak, Banten, Indonesia | 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 Advancing Geothermal Exploration With 2D Magnetotelluric and 3D Modeling: Case Study From Mount Parakasak, Banten, Indonesia Eko Minarto, Fatony Zepanya This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8506977/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 Mount Parakasak in Banten hosts promising yet underexplored geothermal resources. This study integrates two-dimensional magnetotelluric (MT) and time-domain electromagnetic (TDEM) surveys with three-dimensional inversion modeling to delineate subsurface resistivity structures and characterize the geothermal system. Thirty-six MT soundings, corrected for static shift using TDEM data, were inverted to generate 2D resistivity sections and interpolated into a 3D resistivity volume constrained by geological and geochemical datasets. Results reveal a conductive clay cap (~100 Ω·m) and an upflow zone near the Kaipohan manifestation, associated with reservoir temperatures of 240–260 °C. The Batukuwung hot spring marks an outflow zone at 52–75 °C. Integrated modeling supports the presence of an active geothermal system with drilling targets at ~1500 m depth. These findings provide quantitative guidance for exploration and resource assessment, advancing geothermal development in Banten Province. Magnetotelluric TDEM resistivity inversion upflow–outflow zones geothermal modeling ‎Mount Parakasak ‎ Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Introduction Indonesia, located within the Pacific Ring of Fire, is one of the most tectonically dynamic regions on Earth. The convergence of the Indo-Australian, Eurasian, and Pacific plates has produced 129 active volcanoes (Hidayat et al. 2023 ), frequent seismicity, and abundant geothermal potential. This tectonic setting provides a unique combination of high heat flow, magmatic intrusions, and structurally controlled fluid pathways, all of which are favorable for geothermal system development (Letelier et al. 2021 ). Despite these advantages, Indonesia’s utilization of geothermal energy remains limited. Although the country ranks third globally in geothermal electricity production, with an installed capacity of 1,197 MWe, it currently exploits only ~ 5% of its estimated 27 GWe potential (Suharmanto et al. 2015 ; Yudha et al. 2022 ). This underutilization reflects both technical and non-technical challenges. Exploration and drilling costs remain high, while uncertainties in subsurface characterization often delay project development (Szklarz et al. 2024 ). Regulatory frameworks and community acceptance also influence the pace of geothermal expansion (Wahid et al. 2025 ). As a result, vast reserves—representing nearly 40% of the world’s geothermal resources—remain untapped beneath Indonesia’s volcanic terrain (Nasruddin et al. 2016). Unlocking this potential requires advanced geophysical and geochemical approaches that can reduce exploration risk, improve resource estimates, and guide sustainable development strategies. Within this national context, Banten Province, and specifically Mount Parakasak, emerges as a promising but underexplored geothermal prospect, where integrated geophysical modeling can provide critical insights into reservoir structure and fluid dynamics (Tripathi et al. 2025 ). Unlike solar and wind, geothermal energy provides continuous baseload capacity (Kassem and Moscariello 2025 ), making it a critical component of long-term energy security strategies. Indonesia’s exploration history began at Kamojang in 1918, with systematic development only commencing in 1972 (Hochstein and Sudarman 2008 ). Since then, geothermal projects have expanded across Java, Sumatra, and Sulawesi, yet many promising volcanic systems remain underexplored. Mount Parakasak in Banten Province is one such prospect, where surface manifestations—including hot springs, fumaroles, and hydrothermal alteration zones—are accompanied by geophysical anomalies indicative of a hydrothermal system. Previous magnetotelluric (MT) and time‑domain electromagnetic (TDEM) surveys in the area successfully delineated low‑resistivity zones, suggesting the presence of conductive clay caps and potential reservoirs (Wamalwa and Serpa 2013 ). However, interpretations of upflow and outflow processes have remained largely qualitative, with limited integration of geological structures and geochemical signatures. This disconnect reduces confidence in subsurface models and increases exploration risk. Furthermore, volumetric resource assessments have often relied on generic parameters rather than site‑specific constraints, limiting accuracy and comparability across geothermal fields (Elshehabi and Alfehaid 2025 ). These limitations underscore the need for a comprehensive, multidisciplinary approach that quantitatively integrates MT and TDEM data with geological and geochemical evidence (Giambiagi et al. 2019 ). Such integration can improve the delineation of subsurface resistivity structures, enhance the characterization of fluid pathways, and provide verifiable resource estimates. In the case of Mount Parakasak, this approach is essential for reducing uncertainty, identifying drilling targets, and supporting sustainable geothermal development in Banten Province. This study addresses these gaps by quantitatively integrating magnetotelluric (MT) and time‑domain electromagnetic (TDEM) data with geological and geochemical constraints to produce a robust characterization of the Mount Parakasak geothermal system. The combined workflow enables the delineation of upflow and outflow zones, which are critical for understanding reservoir dynamics and fluid migration pathways (Kurnianto 2025 ). Unlike previous qualitative interpretations, the present study applies a locally justified volumetric approach that adheres to the Indonesian National Standard for geothermal resource assessment (SNI 6169:2018), thereby ensuring methodological consistency and comparability with other geothermal fields. Resistivity–temperature correlations are employed to strengthen the interpretation of conductive clay caps, reservoir boundaries, and hydrothermal alteration zones (Savitri et al. 2021 ), allowing drilling targets to be proposed at depths where geophysical anomalies coincide with geochemical evidence of high‑temperature fluids (Fig. 1 ). By integrating multidisciplinary datasets into a unified inversion and modeling framework, this study produces accurate and verifiable resource estimates. These results not only reduce exploration risk but also provide quantitative guidance for future drilling and development strategies, thereby advancing geothermal resource utilization in Banten Province and contributing to Indonesia’s broader energy security goals. Methodology To address these limitations, this study integrates magnetotelluric (MT) and time‑domain electromagnetic (TDEM) data with geological and geochemical constraints, applying both two‑dimensional inversion and three‑dimensional modeling to delineate upflow and outflow zones, quantify reservoir parameters, and identify drilling targets in accordance with national standards (SNI 6169:2018). This integrated approach is designed to overcome the shortcomings of earlier qualitative interpretations and generic volumetric assessments (Muñoz 2014 ), thereby providing a more reliable and site‑specific evaluation of geothermal resources. Building on the need for integrated and quantitative analysis, the research employs a multidisciplinary workflow tailored to characterize the geothermal system at Mount Parakasak. The approach combines geophysical surveys (MT and TDEM), geological mapping, and geochemical investigations within a unified inversion and modeling framework. This ensures that geophysical anomalies are interpreted in direct relation to lithological units, structural features, and hydrothermal alteration zones, thereby reducing ambiguity and enhancing confidence in resource estimates (Belyakov 2019 ). By explicitly linking resistivity anomalies to geochemical signatures and geological structures, the workflow strengthens the correlation between subsurface models and observable manifestations, which is critical for reducing exploration risk (Kremer et al. 2025 ). The methodology adopted in this study was structured into three interconnected stages. First, data acquisition involved the systematic collection of magnetotelluric (MT) soundings and time‑domain electromagnetic (TDEM) measurements, complemented by geological field mapping and geochemical sampling of hot springs and fumaroles. These multidisciplinary datasets provided complementary constraints on subsurface resistivity, lithology, and fluid chemistry, ensuring that electrical anomalies were interpreted within a robust geological and geochemical framework (Alvarado et al. 2025 ). In the second stage, data processing and inversion were carried out by correcting static shift effects using TDEM near‑surface resistivity, followed by one‑dimensional and two‑dimensional inversion to validate resistivity–depth profiles. The resulting 2D sections were subsequently assembled into a coherent three‑dimensional resistivity volume through spatial interpolation and inversion, constrained by geological structures and geochemical indicators (Ren and Kalscheuer 2020 ). This integration ensured that the final resistivity model honored both geophysical measurements and independent geological evidence, thereby improving model fidelity. Finally, interpretation and resource assessment focused on delineating conductive clay caps, upflow and outflow zones, and reservoir boundaries. Resistivity anomalies were correlated with geochemical signatures to estimate reservoir temperature and thickness (Lichoro et al. 2017 ), while volumetric calculations of geothermal potential were performed in accordance with SNI 6169:2018. This stage provided quantitative guidance for drilling target selection and resource evaluation, ensuring methodological consistency and comparability with other Indonesian geothermal fields. This integrated workflow provides a reproducible framework for geothermal exploration, ensuring that resistivity anomalies are interpreted within their geological and geochemical context. By combining multiple datasets into a single inversion and modeling process, the study reduces uncertainty, improves the reliability of resource estimates, and offers practical guidance (Cao et al. 2024 ) for exploration drilling strategies in Banten Province. More broadly, the methodology demonstrates how multidisciplinary integration can enhance geothermal resource assessments in complex volcanic terrains, contributing to Indonesia’s national energy security and advancing global best practices in geothermal exploration. Study area The study area is located within the Mount Parakasak region of Banten Province (Fig. 2 ), approximately 100 km west of Jakarta, and spans the administrative boundaries of Pandeglang and Serang Regencies (6°20′–6°30′ S, 105°50′–106°00′ E). The terrain is characterized by undulating hills with elevations ranging from 970 to 1050 m above sea level and slope gradients of 20°–45°, reflecting the influence of volcanic morphology and erosional processes. Land use varies according to topography, with dense forest cover on the upper slopes, rice fields and agricultural plots on gentler terrain, and settlements concentrated in valley areas. This distribution highlights the interaction between geomorphology and human activity, which is typical of volcanic landscapes in western Java. Hydrothermal manifestations provide direct evidence of geothermal activity in the region (Ishitsuka et al. 2022 ). The Kaipohan mofette, located on the northern flank, releases carbon dioxide gas through diffuse soil degassing, while the Batukuwung hot spring emerges along fault‑controlled zones in the southern sector (Fig. 3 ). These features indicate active fluid circulation within the subsurface and suggest the presence of permeable structures that may serve as conduits for geothermal upflow (Chavanidis et al. 2025 ). The spatial association of surface manifestations with structural lineaments further supports the interpretation of Mount Parakasak as a hydrothermal system (Rafiq et al. 2025 ). Together, the geomorphological setting, land use patterns, and hydrothermal features establish the study area as a promising target for integrated geophysical and geochemical investigations aimed at delineating subsurface reservoirs and assessing geothermal potential. Geological Setting The Mount Parakasak region forms part of the western Java volcanic arc, which developed in response to the ongoing subduction of the Indo‑Australian Plate beneath the Eurasian Plate (Fig. 4 ). The area is dominated by Quaternary volcanic deposits, including andesitic to basaltic lava flows, pyroclastic sequences, and reworked volcaniclastic sediments (Susilohadi et al. 2024 ). These lithologies are interbedded with older Tertiary formations, such as sandstones and shales, which locally act as impermeable barriers to fluid migration. The volcanic stratigraphy is characterized by alternating permeable and impermeable horizons, creating favorable conditions for geothermal reservoir development. Figure 4 illustrates the distribution of Quaternary volcanic deposits (andesitic–basaltic lava flows, pyroclastic sequences, and volcaniclastic sediments) interbedded with older Tertiary formations. Major NW–SE and NE–SW fault systems are highlighted, showing their spatial association with hydrothermal manifestations such as the Kaipohan mofette and Batukuwung hot spring. Areas of hydrothermal alteration (argillic and propylitic zones) are indicated, delineating conductive clay caps that overlie potential geothermal reservoirs (Stimac et al. 2019 ). Elevation contours (970–1050 m) and land-use patterns (forest, agriculture, settlements) are included to provide geomorphological context. This map forms the basis for integrating geophysical and geochemical datasets in the delineation of reservoir boundaries and fluid pathways. Structurally, the region is dissected by NW–SE and NE–SW trending faults, which are consistent with regional tectonic stress orientations. These faults and associated fracture zones provide pathways for hydrothermal fluids, as evidenced by the alignment of surface manifestations such as the Kaipohan mofette and Batukuwung hot spring. Hydrothermal alteration, including argillic and propylitic assemblages, is observed along fault zones and in areas of intense fumarolic activity, further supporting the presence of active fluid circulation (Kereszturi et al. 2020 ). The conductive clay caps identified in geophysical surveys are interpreted as alteration products of volcanic rocks, which overlie potential geothermal reservoirs at depth. Together, the lithological framework, stratigraphic variability, and structural controls define a complex volcanic‑hydrothermal system at Mount Parakasak. This geological setting provides the basis for integrating geophysical and geochemical data, enabling the delineation of reservoir boundaries and the identification of upflow and outflow zones critical to geothermal resource assessment. Data Acquisition Geophysical, geological, and geochemical datasets were acquired to support the integrated characterization of the Mount Parakasak geothermal system. Magnetotelluric (MT) surveys were conducted along six profiles, yielding a total of 36 EDI‑formatted soundings (Fig. 5 ). These soundings provided deep resistivity information essential for delineating subsurface structures, including clay caps, reservoir zones, and fault‑controlled fluid pathways. To enhance near‑surface resolution and correct for static shift effects inherent in MT data, time‑domain electromagnetic (TDEM) measurements were performed at each MT station (Krivochieva and Chouteau 2003 ). The TDEM data enabled calibration of shallow resistivity values and improved the accuracy of inversion results, particularly in areas with complex topography and heterogeneous surface conditions (Wang et al. 2023 ). Geological mapping was carried out in parallel, focusing on lithological boundaries, structural lineaments, and zones of hydrothermal alteration. Field observations documented the distribution of volcanic and sedimentary units, fault orientations, and surface manifestations such as fumaroles and hot springs. These geological features were used to constrain geophysical models and interpret resistivity anomalies in relation to known lithologies and structural controls. Geochemical investigations included fluid sampling from the Kaipohan mofette and Batukuwung hot spring. Samples were analyzed for major ions, stable isotopes (δ¹⁸O, δD), and gas compositions (CO₂, H₂S, CH₄), with geothermometric calculations applied to estimate subsurface temperatures. These geochemical signatures provided independent validation of reservoir conditions inferred from resistivity models and helped identify zones of active upflow. All datasets were provided by PT. Sintesa Banten Geothermal and the National Nuclear Energy Agency of Indonesia (BATAN), ensuring consistency in acquisition protocols and data quality. The integration of these multidisciplinary datasets forms the foundation for subsequent inversion, modeling, and resource assessment workflows. Data Processing and Inversion Following acquisition, geophysical datasets were processed to enhance signal quality and prepare for inversion modeling. Magnetotelluric (MT) data were first examined for noise, and static shift corrections were applied using co‑located time‑domain electromagnetic (TDEM) measurements. The TDEM data provided near‑surface resistivity values that served as calibration points, ensuring that shallow MT responses were accurately anchored and minimizing distortion caused by lateral resistivity contrasts. Inversion was conducted in two stages. One‑dimensional (1D) inversion was applied to individual MT soundings to generate preliminary resistivity–depth profiles and identify anomalous zones. These results informed the setup of two‑dimensional (2D) inversion along each survey line, using a smooth‑occam algorithm to resolve lateral and vertical resistivity variations. The 2D resistivity sections revealed conductive zones interpreted as clay caps, resistive cores associated with potential reservoirs, and fault‑controlled discontinuities indicative of fluid pathways. To construct a comprehensive subsurface model, multiple 2D profiles were interpolated and assembled into a three‑dimensional (3D) resistivity volume. This 3D model was constrained by geological mapping and geochemical indicators, including the spatial distribution of surface manifestations and isotopic geothermometry results. Integration of these datasets ensured that the resistivity model honored both geophysical measurements and independent geological evidence, thereby improving model fidelity and interpretive confidence. The final resistivity volume served as the basis for delineating upflow and outflow zones, estimating reservoir geometry, and guiding volumetric resource calculations. All inversion procedures were performed using industry‑standard software and validated through sensitivity testing and cross‑profile correlation. Interpretation and Resource Assessment The integrated resistivity models, constrained by geological and geochemical datasets, were interpreted to delineate key features of the Mount Parakasak geothermal system. Conductive zones identified in the three‑dimensional resistivity volume were correlated with hydrothermal alteration assemblages observed in the field, confirming their role as clay caps that seal underlying reservoirs. Beneath these conductive layers, resistive anomalies were interpreted as potential reservoir zones, consistent with elevated subsurface temperatures inferred from isotopic and gas geothermometer analyses of hot spring and fumarole fluids. Upflow zones were characterized by steeply dipping resistive structures aligned with NW–SE and NE–SW fault systems, which coincide spatially with surface manifestations such as the Kaipohan mofette and Batukuwung hot spring. These structural corridors are interpreted as permeable conduits facilitating the ascent of geothermal fluids. Outflow zones, in contrast, were delineated by lateral extensions of conductive anomalies, reflecting the dispersal of cooled fluids into surrounding formations. The integration of geochemical signatures with resistivity anomalies strengthened the interpretation of reservoir boundaries and fluid pathways, reducing uncertainty in subsurface characterization. Volumetric resource assessment was conducted in accordance with SNI 6169:2018, applying locally justified parameters derived from geophysical and geochemical constraints rather than generic values. Reservoir thickness, porosity, and temperature estimates were extracted directly from the integrated models, ensuring methodological consistency and comparability with other Indonesian geothermal fields. The resulting resource estimates provide quantitative guidance for drilling target selection, highlighting zones where resistivity anomalies, structural permeability, and geochemical evidence converge. This multidisciplinary interpretation demonstrates the value of integrating MT and TDEM surveys with geological and geochemical data. By reducing reliance on qualitative assumptions and generic parameters, the study produces verifiable resource estimates that strengthen exploration strategies and support sustainable geothermal development in Banten Province. Results Static Shift Correction Static shift is a common distortion in magnetotelluric (MT) data, arising from near‑surface heterogeneities and galvanic effects that cause vertical offsets in apparent resistivity curves. If uncorrected, these distortions can lead to erroneous interpretations of subsurface resistivity structures. To address this issue, time‑domain electromagnetic (TDEM) measurements were acquired at each MT station and used to calibrate shallow resistivity values. The TDEM data provided independent near‑surface constraints, enabling correction of static shift and alignment of transverse electric (TE) and transverse magnetic (TM) curves. As illustrated in Figs. 6 – 7 , the application of TDEM corrections successfully eliminated static offsets, producing consistent TE and TM responses across multiple profiles. This alignment improved the accuracy of resistivity estimates and enhanced confidence in the reliability of the dataset. Following correction, one‑dimensional (1D) inversions were performed for each MT sounding to validate resistivity–depth trends. The 1D inversion results confirmed the presence of conductive layers at shallow depths, interpreted as clay caps, underlain by resistive zones associated with potential geothermal reservoirs (Fig. 8 ). The consistency of corrected resistivity–depth profiles across stations demonstrates the robustness of the static shift correction procedure. By integrating TDEM calibration, the study ensures that resistivity anomalies reflect true subsurface conditions rather than artifacts of surface heterogeneity. This methodological refinement reduces uncertainty in reservoir delineation, strengthens the correlation between geophysical models and geological–geochemical evidence, and provides a reliable foundation for subsequent two‑dimensional (2D) and three‑dimensional (3D) inversion and resource assessment. Resistivity Structure The two‑dimensional (2D) resistivity sections derived from magnetotelluric (MT) inversion provide the first level of subsurface characterization along individual survey lines. Each profile consistently reveals a shallow conductive horizon with resistivity values of ~ 100 Ω·m, interpreted as a smectite‑rich clay cap. Such alteration products are typical of high‑enthalpy geothermal systems, where circulating acidic fluids transform primary volcanic minerals into low‑resistivity clays. The lateral continuity of this horizon across multiple lines confirms its role as a regional cap rock, restricting vertical fluid migration and maintaining reservoir pressure. Figures 9 present representative two‑dimensional (2D) resistivity cross‑sections along each survey trajectory. The profiles consistently delineate a shallow conductive horizon (~ 100 Ω·m), interpreted as a smectite‑rich clay cap, together with underlying resistive anomalies associated with high‑temperature reservoir zones. This visualization reinforces the interpretation of a laterally continuous alteration zone that effectively seals the reservoir, restricts vertical fluid migration, and maintains subsurface pressure conditions essential for geothermal system integrity. Beneath the clay cap, resistive anomalies are concentrated near the Kaipohan sector. These zones are interpreted as upflow regions where geothermal fluids ascend through fault‑controlled conduits. The resistivity signature reflects relatively unaltered volcanic rocks saturated with high‑temperature fluids. Geochemical analyses of fumarolic gases and hot spring fluids indicate reservoir temperatures of 240–260°C, consistent with the resistivity anomalies observed. The spatial correlation between resistive structures, NW–SE fault lineaments, and geochemical geothermometers strengthens the interpretation of Kaipohan as the principal upflow zone. In contrast, the Batukuwung hot spring is characterized by lateral conductive extensions trending away from the reservoir core. These features are interpreted as outflow zones where geothermal fluids migrate laterally beneath the clay cap before discharging at the surface. Measured discharge temperatures of 52–75°C reflect the thermal decline associated with outflow processes. The conductive anomalies in this sector validate the geophysical interpretation of cooled fluid dispersal into surrounding formations. Interpolation of multiple 2D sections into a three‑dimensional (3D) resistivity volume yields a coherent model of the Mount Parakasak geothermal system. Figure 10 presents the integrated 3D resistivity model, delineating three principal components: (i) a shallow conductive clay cap (~ 100 Ω·m) consistent with smectite alteration, (ii) a resistive upflow zone near Kaipohan associated with reservoir temperatures of 240–260°C, and (iii) an outflow zone at Batukuwung hot spring, expressed as conductive extensions linked to discharge temperatures of 52–75°C. Structural lineaments constrain the geometry of these zones, highlighting fault‑controlled permeability pathways. The integration of 2D and 3D resistivity models with geological and geochemical datasets reduces interpretive uncertainty and provides quantitative guidance for drilling target selection. This multidisciplinary approach demonstrates the effectiveness of static‑shift‑corrected MT data in producing reliable subsurface models and establishes a robust framework for reservoir characterization and resource assessment in accordance with SNI 6169:2018. Drilling Targets The integrated resistivity–geochemical model provides quantitative guidance for the selection of drilling targets within the Mount Parakasak geothermal system. Resistivity anomalies identified at depths of approximately 1500 m coincide spatially with geochemical evidence of high‑temperature fluids, including gas geothermometer estimates of 240–260°C in the Kaipohan sector. These resistive zones are interpreted as permeable reservoir rocks saturated with geothermal fluids, bounded above by a smectite‑rich clay cap. The convergence of geophysical anomalies, structural permeability, and geochemical signatures strengthens confidence in the reliability of these targets and reduces uncertainty in reservoir delineation. The proposed drilling depth of ~ 1500 m is consistent with the vertical extent of resistive anomalies observed in the three‑dimensional model and aligns with reservoir thickness estimates derived from volumetric calculations. This depth is expected to intersect the high‑enthalpy reservoir zone while remaining below the conductive clay cap, thereby maximizing the likelihood of encountering productive fluid pathways. Structural controls, particularly NW–SE fault lineaments, provide additional justification for drilling in these locations, as they act as conduits for geothermal upflow. In addition to production wells, the model highlights outflow zones such as the Batukuwung hot spring as potential recharge sites for reinjection. These zones are characterized by lateral conductive extensions and discharge temperatures of 52–75°C, reflecting cooled geothermal fluids migrating away from the reservoir core. Reinjection into these outflow zones would enhance reservoir sustainability by maintaining pressure, facilitating fluid circulation, and minimizing environmental impacts associated with surface discharge. Together, the delineation of drilling targets and reinjection sites demonstrates the value of integrating magnetotelluric (MT) and time‑domain electromagnetic (TDEM) surveys with geological and geochemical datasets. This multidisciplinary approach ensures that drilling decisions are based on verifiable subsurface evidence, thereby improving exploration efficiency and supporting long‑term geothermal development in Banten Province. Discussion The integration of magnetotelluric (MT), time‑domain electromagnetic (TDEM), and three‑dimensional (3D) inversion modeling establishes a robust framework for geothermal exploration in complex volcanic terrains such as Mount Parakasak. By correcting static shift effects with TDEM data, the MT responses were calibrated to reflect true subsurface resistivity, thereby improving the reliability of inversion results. This methodological refinement ensures that resistivity anomalies are not artifacts of near‑surface heterogeneity but instead represent genuine subsurface features. The resulting anomalies correlate strongly with hydrothermal alteration zones and geochemical signatures, validating the delineation of upflow and outflow processes. Conductive horizons of ~ 100 Ω·m correspond to smectite‑rich clay caps, which act as impermeable seals above the reservoir. Beneath these caps, resistive anomalies near Kaipohan coincide with geochemical geothermometer estimates of 240–260°C, confirming the presence of high‑temperature upflow zones. In contrast, lateral conductive extensions toward Batukuwung hot spring align with measured discharge temperatures of 52–75°C, supporting their interpretation as outflow pathways. The consistency between geophysical anomalies, mineralogical alteration, and geochemical evidence strengthens confidence in the integrated model. Compared to conventional two‑dimensional (2D) interpretations, the 3D resistivity model significantly reduces uncertainty by honoring geological constraints and eliminating assumptions about strike direction. Whereas 2D sections provide valuable line‑based insights, they are limited in capturing the full spatial complexity of geothermal systems. The 3D volume integrates multiple trajectories into a coherent subsurface representation, constrained by structural lineaments and alteration patterns. This approach enhances interpretive accuracy, improves reproducibility, and provides a more realistic basis for reservoir delineation. From an exploration perspective, the integrated workflow directly supports cost‑effective drilling strategies. By identifying high‑confidence targets at ~ 1500 m depth within resistive upflow zones, the model reduces the risk of non‑productive wells. Simultaneously, the delineation of outflow zones provides potential recharge sites for reinjection, ensuring reservoir sustainability. The combined use of MT, TDEM, and 3D inversion thus advances geothermal resource assessment by linking geophysical anomalies to geological and geochemical evidence, aligning exploration practices with national standards such as SNI 6169:2018, and strengthening the scientific basis for geothermal development in Banten Province.‎ Conclusions This study demonstrates the effectiveness of integrating magnetotelluric (MT), time‑domain electromagnetic (TDEM), and three‑dimensional (3D) inversion modeling for geothermal exploration in volcanic terrains. The specific conclusions are as follows: Active geothermal system at Mount Parakasak: The resistivity model delineates a shallow conductive clay cap (~ 100 Ω·m) interpreted as smectite‑rich hydrothermal alteration, a resistive upflow zone near Kaipohan associated with reservoir temperatures of 240–260°C, and an outflow zone at Batukuwung hot spring characterized by discharge temperatures of 52–75°C. These features collectively confirm the presence of an active hydrothermal system with fault‑controlled permeability pathways. Improved resistivity interpretation through integrated modeling: The combined use of MT and TDEM data, corrected for static shift, and interpolated into a 3D resistivity volume significantly enhances subsurface characterization. This approach reduces interpretive uncertainty compared to conventional 2D models by honoring geological constraints and eliminating strike‑direction assumptions, thereby strengthening correlations between resistivity anomalies, alteration mineralogy, and geochemical signatures. Drilling targets supported by geophysical–geochemical correlations: The integrated model identifies high‑confidence drilling targets at ~ 1500 m depth within resistive upflow zones. These targets are validated by reservoir temperature estimates from geochemical geothermometers, ensuring that drilling strategies are both scientifically justified and cost‑effective. Outflow zones provide potential recharge sites for reinjection, supporting long‑term reservoir sustainability. Alignment with national standards and reproducibility: The methodology conforms to SNI 6169:2018, ensuring consistency with nationally recognized volumetric resource assessment practices. By integrating geophysical, geological, and geochemical datasets, the workflow provides a reproducible framework for geothermal exploration in Indonesia, offering a model that can be applied to other volcanic geothermal prospects across the archipelago. In summary, the integration of MT, TDEM, and 3D inversion modeling advances geothermal resource assessment by linking resistivity anomalies to hydrothermal processes and geochemical evidence. The approach reduces exploration risk, supports sustainable reservoir management, and contributes to the broader development of Indonesia’s geothermal potential. Declarations Acknowledgements We thank PT. Sintesa Banten Geothermal and BATAN for providing datasets and technical support. Author contributions E.Minarto: Conceptualization; Methodology; Data curation; Formal analysis; Investigation; Writing – review & editing; Visualization; Project administration; Supervision. F.Zepanya: Resources; Data acquisition; Validation; Writing – original draft; Funding acquisition. All authors have read and agreed to the published version of the manuscript. Funding This research was supported by PT. Sintesa Banten Geothermal, Jakarta, Indonesia, through provision of geophysical and geochemical datasets. Additional institutional support was provided by the Department of Physics, Institut Teknologi Sepuluh Nopember (ITS), Surabaya, Indonesia. No external grant funding was received for this study. Data availability The datasets used and analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare no competing interests. References Ahumada MF, Guevara L, Favetto A, et al (2022) Electrical resistivity structure in the Tocomar geothermal system obtained from 3-D inversion of audio-magnetotelluric data (Central Puna, NW Argentina). Geothermics 104:102436. https://doi.org/10.1016/j.geothermics.2022.102436 Alvarado H, Pescador J, Landinez J, et al (2025) Quantitative Integration of Audio-Magnetotelluric Sounding and Resistivity Well Logs for Groundwater Studies. Water 17:3389. https://doi.org/10.3390/w17233389 Belyakov N (2019) Geothermal energy. In: Sustainable Power Generation. Elsevier, pp 475–500 Cao X, Liu Z, Hu C, et al (2024) Three-Dimensional Geological Modelling in Earth Science Research: An In-Depth Review and Perspective Analysis. Minerals 14:686. https://doi.org/10.3390/min14070686 Chavanidis K, Stampolidis A, Salem A, et al (2025) Gravity modeling of a prospective geothermal field of a hot spring in Western Saudi Arabia. Journal of Volcanology and Geothermal Research 461:108307. https://doi.org/10.1016/j.jvolgeores.2025.108307 Elshehabi T, Alfehaid M (2025) Sustainable Geothermal Energy: A Review of Challenges and Opportunities in Deep Wells and Shallow Heat Pumps for Transitioning Professionals. Energies 18:811. https://doi.org/10.3390/en18040811 Giambiagi L, Álvarez P, Spagnotto S, et al (2019) Geomechanical model for a seismically active geothermal field: Insights from the Tinguiririca volcanic-hydrothermal system. Geoscience Frontiers 10:2117–2133. https://doi.org/10.1016/j.gsf.2019.02.006 Hidayat A, Suryanto, Utomowati R, Setiawan JV (2023) Assessment of the Relationship Between Repose Period and Eruption Magnitude of Gamalama Volcano for Community Preparedness in Ternate Island – Indonesia. IJSDP 18:773–779. https://doi.org/10.18280/ijsdp.180313 Hochstein MP, Sudarman S (2008) History of geothermal exploration in Indonesia from 1970 to 2000. Geothermics 37:220–266. https://doi.org/10.1016/j.geothermics.2008.01.001 Ishitsuka K, Ojima H, Mogi T, et al (2022) Characterization of hydrothermal alteration along geothermal wells using unsupervised machine-learning analysis of X-ray powder diffraction data. Earth Sci Inform 15:73–87. https://doi.org/10.1007/s12145-021-00694-3 Kassem MA, Moscariello A (2025) Geothermal energy: A sustainable and cost-effective alternative for clean energy production and climate change mitigation. Sustainable Futures 10:101247. https://doi.org/10.1016/j.sftr.2025.101247 Kereszturi G, Schaefer LN, Miller C, Mead S (2020) Hydrothermal Alteration on Composite Volcanoes: Mineralogy, Hyperspectral Imaging, and Aeromagnetic Study of Mt Ruapehu, New Zealand. Geochem Geophys Geosyst 21:e2020GC009270. https://doi.org/10.1029/2020GC009270 Kremer T, Ars JM, Gaubert-Bastide T, et al (2025) Chapter 6 • The use of passive seismic methods for Geothermal exploration and monitoring. In: Geophysics in geothermal exploration: a review. EDP Sciences, pp 181–222 Krivochieva S, Chouteau M (2003) Integrating TDEM and MT methods for characterization and delineation of the Santa Catarina aquifer (Chalco Sub-Basin, Mexico). Journal of Applied Geophysics 52:23–43. https://doi.org/10.1016/S0926-9851(02)00231-8 Kurnianto B (2025) THE ROLE OF FRACTURE DENSITY IN MANIFESTATIONS OF UPFLOW AND OUTFLOW ZONES OF AN UNGARAN MOUNTAIN GEOTHERMAL SYSTEM. GEOMATE 29:. https://doi.org/10.21660/2025.132.4905 Letelier JA, O’Sullivan J, Reich M, et al (2021) Reservoir architecture model and heat transfer modes in the El Tatio-La Torta geothermal system, Central Andes of northern Chile. Geothermics 89:101940. https://doi.org/10.1016/j.geothermics.2020.101940 Lichoro CM, Árnason K, Cumming W (2017) Resistivity imaging of geothermal resources in northern Kenya rift by joint 1D inversion of MT and TEM data. Geothermics 68:20–32. https://doi.org/10.1016/j.geothermics.2017.02.006 Muñoz G (2014) Exploring for Geothermal Resources with Electromagnetic Methods. Surv Geophys 35:101–122. https://doi.org/10.1007/s10712-013-9236-0 Nasruddin, Idrus Alhamid M, Daud Y, et al (2016) Potential of geothermal energy for electricity generation in Indonesia: A review. Renewable and Sustainable Energy Reviews 53:733–740. https://doi.org/10.1016/j.rser.2015.09.032 Rafiq J, Abu-Mahfouz IS, Chavanidis K, et al (2025) Spatial distribution of structural lineaments in the Al-Lith geothermal field, western Saudi Arabia: Remote sensing and aeromagnetic data analysis. Journal of Asian Earth Sciences: X 13:100191. https://doi.org/10.1016/j.jaesx.2025.100191 Ren Z, Kalscheuer T (2020) Uncertainty and Resolution Analysis of 2D and 3D Inversion Models Computed from Geophysical Electromagnetic Data. Surv Geophys 41:47–112. https://doi.org/10.1007/s10712-019-09567-3 Savitri KP, Hecker C, Van Der Meer FD, Sidik RP (2021) VNIR-SWIR infrared (imaging) spectroscopy for geothermal exploration: Current status and future directions. Geothermics 96:102178. https://doi.org/10.1016/j.geothermics.2021.102178 Stimac J, Ganefianto N, Baroek M, et al (2019) An overview of the Muara Laboh geothermal system, Sumatra. Geothermics 82:150–167. https://doi.org/10.1016/j.geothermics.2019.05.008 Suharmanto P, Fitria AN, Ghaliyah S (2015) Indonesian Geothermal Energy Potential as Source of Alternative Energy Power Plant. KEn 1:119. https://doi.org/10.18502/ken.v1i1.325 Sumotarto U, Hendrasto F, Triadi W (2019) Volcanostratigraphy of Batukuwung-Parakasak Geothermal Area, Serang Regency, West Java. J Phys: Conf Ser 1363:012048. https://doi.org/10.1088/1742-6596/1363/1/012048 Susilohadi S, Novico F, Husson L, et al (2024) Quaternary deposition and erosion in the northeastern Sunda Strait: An interplay between sea level, tectonics, and magmatic activity. Journal of Asian Earth Sciences: X 12:100179. https://doi.org/10.1016/j.jaesx.2024.100179 Szklarz SP, Barros EGD, Khoshnevis Gargar N, et al (2024) Geothermal field development optimization under geomechanical constraints and geological uncertainty: Application to a reservoir with stacked formations. Geothermics 123:103094. https://doi.org/10.1016/j.geothermics.2024.103094 Tripathi A, Low U, Karim A (2025) Deciphering structural framework of Bakreswar geothermal field, eastern India: insights from geophysical data analysis and 3D inversion modeling. Geothermics 133:103471. https://doi.org/10.1016/j.geothermics.2025.103471 Wahid MN, Asif M, Khan MI, Khalid M (2025) A strategic analysis of geothermal energy for sustainable energy transition: Case study from Indonesia. Energy Conversion and Management: X 28:101303. https://doi.org/10.1016/j.ecmx.2025.101303 Wamalwa AM, Serpa LF (2013) The investigation of the geothermal potential at the Silali volcano, Northern Kenya Rift, using electromagnetic data. Geothermics 47:89–96. https://doi.org/10.1016/j.geothermics.2013.02.001 Wang X, Cai H, Liu L, et al (2023) Three-Dimensional Inversion of Long-Offset Transient Electromagnetic Method over Topography. Minerals 13:908. https://doi.org/10.3390/min13070908 Yudha S, Tjahjono B, Longhurst P (2022) Unearthing the Dynamics of Indonesia’s Geothermal Energy Development. Energies 15:5009. https://doi.org/10.3390/en15145009 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. 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08:13:51","extension":"png","order_by":34,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":15000,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinegroupimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8506977/v1/833cd4f6dec42871195734b2.png"},{"id":100343267,"identity":"3054f9d8-9aea-4564-be59-e34b954137c8","added_by":"auto","created_at":"2026-01-16 00:09:11","extension":"png","order_by":35,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":742,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinegroupimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8506977/v1/780ccb9d0b269f2bbab50cd1.png"},{"id":100343280,"identity":"10b80d17-c053-4613-8d2e-6fb294c12ff3","added_by":"auto","created_at":"2026-01-16 00:09:12","extension":"xml","order_by":36,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":97312,"visible":true,"origin":"","legend":"","description":"","filename":"61185adb4228481e96804c725b712c371structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8506977/v1/937661aa2f972cb1f227fde4.xml"},{"id":100343276,"identity":"80e98ce6-8041-49d8-a192-0c701513e983","added_by":"auto","created_at":"2026-01-16 00:09:12","extension":"html","order_by":37,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":106180,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8506977/v1/a79a682d6bb158d2f6308a5d.html"},{"id":100343242,"identity":"b5016ae5-ce72-4aa8-a81d-ec801ddd6313","added_by":"auto","created_at":"2026-01-16 00:09:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":294364,"visible":true,"origin":"","legend":"\u003cp\u003eConceptual cross‑section of geothermal systems (Ahumada et al. 2022)‎, illustrating resistivity–temperature relationships, hydrothermal alteration zones, and reservoir structures relevant to subsurface fluid flow and geothermal potential\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8506977/v1/7964398a2f363c9258d70d95.png"},{"id":100378064,"identity":"8e1be7f6-09fa-4161-92cd-f2bb8c9f8356","added_by":"auto","created_at":"2026-01-16 08:49:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":380079,"visible":true,"origin":"","legend":"\u003cp\u003eRegional map of western Java, Indonesia, highlighting the research area near Jakarta. Major cities, coastlines, and infrastructure elements are shown to provide geographic context for the survey location and its tectonic setting\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8506977/v1/279a3e2b8ba1c66d251ee576.png"},{"id":100377854,"identity":"2531d99e-d04b-44fd-ad7d-145e24e6a0af","added_by":"auto","created_at":"2026-01-16 08:48:36","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":444955,"visible":true,"origin":"","legend":"\u003cp\u003eSurface manifestations of Mount Parakasak, West Java. The Kaipohan mofette, situated on the northern flank, releases carbon dioxide gas through diffuse soil degassing. In contrast, the Batukuwung hot spring emerges along fault-controlled zones in the southern sector, reflecting hydrothermal discharge pathways influenced by local structural controls\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8506977/v1/6143b99c725246d60dd24a06.png"},{"id":100343247,"identity":"404f2c87-61fe-4af8-8fd0-8fd2cc3a5592","added_by":"auto","created_at":"2026-01-16 00:09:11","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":464329,"visible":true,"origin":"","legend":"\u003cp\u003eGeological map of the Mount Parakasak region, Banten Province, Indonesia, adapted from (Sumotarto et al. 2019). The map delineates principal lithological units, fault structures, and volcanic zones that are relevant to geothermal manifestations and regional tectonic interpretation\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8506977/v1/9fd2b169ea813f9079adf5f7.png"},{"id":100343245,"identity":"7bdf7f8b-295c-4a2a-a4b1-3b62021d4ab0","added_by":"auto","created_at":"2026-01-16 00:09:11","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":211214,"visible":true,"origin":"","legend":"\u003cp\u003eMT Magnetotelluric (MT) measurement points overlaid on an elevation map of the study area. The topographic gradient provides spatial context for station distribution and potential correlations between surface morphology and subsurface resistivity structure\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8506977/v1/bc8e918e8ac2972fdffd61a2.png"},{"id":100373281,"identity":"7701c7c1-3133-4bf0-add9-dd5be1cbf058","added_by":"auto","created_at":"2026-01-16 08:14:00","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":212850,"visible":true,"origin":"","legend":"\u003cp\u003eMagnetotelluric (MT) response curves for station MT12 prior to static effect correction. The plots display apparent resistivity and phase versus frequency, highlighting uncorrected distortions in the shallow subsurface response\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8506977/v1/2afb0639244b119b74f5cb19.png"},{"id":100377850,"identity":"e6a96dbe-4f6f-4f47-baa0-1c359bc57dae","added_by":"auto","created_at":"2026-01-16 08:48:35","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":203070,"visible":true,"origin":"","legend":"\u003cp\u003eMagnetotelluric (MT) response curves for station MT12 after static effect correction and smoothing. The plots display apparent resistivity and phase versus frequency, highlighting improved data continuity and enhanced subsurface signal fidelity\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-8506977/v1/c4efbd0c0dc0f2a4c657ecb1.png"},{"id":100343249,"identity":"fec9e56d-85ec-4e6a-ac84-032d3211a5a9","added_by":"auto","created_at":"2026-01-16 00:09:11","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":158580,"visible":true,"origin":"","legend":"\u003cp\u003eInversion result for magnetotelluric (MT) station MT12. The left panels show apparent resistivity and phase curves as functions of period, while the right panel presents the derived resistivity model versus depth. The inversion reveals subsurface conductivity variations associated with geological structures and potential geothermal reservoirs\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-8506977/v1/231c59b2e37a97d1a6faa952.png"},{"id":100373651,"identity":"fc8b505c-239e-4dca-bb98-e9fa8e64fa99","added_by":"auto","created_at":"2026-01-16 08:16:01","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":936022,"visible":true,"origin":"","legend":"\u003cp\u003eTwo-dimensional resistivity cross-sections derived from magnetotelluric (MT) inversion along six survey lines: (a) Line 1, (b) Line 2, (c) Line 3, (d) Line 4, (e) Line 5, and (f) Line 6. The models reveal subsurface conductivity variations associated with geothermal features, including cap rocks, reservoirs, upflow zones, and outflow pathways\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-8506977/v1/1b75b6a04c913e7a17979af0.png"},{"id":100343284,"identity":"95d1a4b0-c3bd-4f63-aa7e-bf56cc541744","added_by":"auto","created_at":"2026-01-16 00:09:12","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":475163,"visible":true,"origin":"","legend":"\u003cp\u003eThree-dimensional resistivity model of the Mount Parakasak geothermal system. The visualization integrates magnetotelluric inversion results with topographic and structural data, revealing subsurface conductivity distribution, fault-controlled fluid pathways, and potential geothermal reservoirs\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-8506977/v1/9c52aa497f01aa897fc14b74.png"},{"id":104405265,"identity":"21332912-f019-45b7-bb33-20e246e3a322","added_by":"auto","created_at":"2026-03-11 12:22:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4455184,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8506977/v1/e924532a-d345-4aac-bb20-419573687328.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Advancing Geothermal Exploration With 2D Magnetotelluric and 3D Modeling: Case Study From Mount Parakasak, Banten, Indonesia","fulltext":[{"header":"Introduction","content":"\u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eIndonesia, located within the Pacific Ring of Fire, is one of the most tectonically dynamic regions on Earth. The convergence of the Indo-Australian, Eurasian, and Pacific plates has produced 129 active volcanoes (Hidayat et al. \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e), frequent seismicity, and abundant geothermal potential. This tectonic setting provides a unique combination of high heat flow, magmatic intrusions, and structurally controlled fluid pathways, all of which are favorable for geothermal system development (Letelier et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Despite these advantages, Indonesia\u0026rsquo;s utilization of geothermal energy remains limited. Although the country ranks third globally in geothermal electricity production, with an installed capacity of 1,197 MWe, it currently exploits only\u0026thinsp;~\u0026thinsp;5% of its estimated 27 GWe potential (Suharmanto et al. \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e; Yudha et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eThis underutilization reflects both technical and non-technical challenges. Exploration and drilling costs remain high, while uncertainties in subsurface characterization often delay project development (Szklarz et al. \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). Regulatory frameworks and community acceptance also influence the pace of geothermal expansion (Wahid et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). As a result, vast reserves\u0026mdash;representing nearly 40% of the world\u0026rsquo;s geothermal resources\u0026mdash;remain untapped beneath Indonesia\u0026rsquo;s volcanic terrain (Nasruddin et al. 2016). Unlocking this potential requires advanced geophysical and geochemical approaches that can reduce exploration risk, improve resource estimates, and guide sustainable development strategies. Within this national context, Banten Province, and specifically Mount Parakasak, emerges as a promising but underexplored geothermal prospect, where integrated geophysical modeling can provide critical insights into reservoir structure and fluid dynamics (Tripathi et al. \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eUnlike solar and wind, geothermal energy provides continuous baseload capacity (Kassem and Moscariello \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e), making it a critical component of long-term energy security strategies. Indonesia\u0026rsquo;s exploration history began at Kamojang in 1918, with systematic development only commencing in 1972 (Hochstein and Sudarman \u003cspan class=\"CitationRef\"\u003e2008\u003c/span\u003e). Since then, geothermal projects have expanded across Java, Sumatra, and Sulawesi, yet many promising volcanic systems remain underexplored. Mount Parakasak in Banten Province is one such prospect, where surface manifestations\u0026mdash;including hot springs, fumaroles, and hydrothermal alteration zones\u0026mdash;are accompanied by geophysical anomalies indicative of a hydrothermal system.\u003c/p\u003e\n \u003cp\u003ePrevious magnetotelluric (MT) and time‑domain electromagnetic (TDEM) surveys in the area successfully delineated low‑resistivity zones, suggesting the presence of conductive clay caps and potential reservoirs (Wamalwa and Serpa \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e). However, interpretations of upflow and outflow processes have remained largely qualitative, with limited integration of geological structures and geochemical signatures. This disconnect reduces confidence in subsurface models and increases exploration risk. Furthermore, volumetric resource assessments have often relied on generic parameters rather than site‑specific constraints, limiting accuracy and comparability across geothermal fields (Elshehabi and Alfehaid \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eThese limitations underscore the need for a comprehensive, multidisciplinary approach that quantitatively integrates MT and TDEM data with geological and geochemical evidence (Giambiagi et al. \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). Such integration can improve the delineation of subsurface resistivity structures, enhance the characterization of fluid pathways, and provide verifiable resource estimates. In the case of Mount Parakasak, this approach is essential for reducing uncertainty, identifying drilling targets, and supporting sustainable geothermal development in Banten Province.\u003c/p\u003e\n \u003cp\u003eThis study addresses these gaps by quantitatively integrating magnetotelluric (MT) and time‑domain electromagnetic (TDEM) data with geological and geochemical constraints to produce a robust characterization of the Mount Parakasak geothermal system. The combined workflow enables the delineation of upflow and outflow zones, which are critical for understanding reservoir dynamics and fluid migration pathways (Kurnianto \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). Unlike previous qualitative interpretations, the present study applies a locally justified volumetric approach that adheres to the Indonesian National Standard for geothermal resource assessment (SNI 6169:2018), thereby ensuring methodological consistency and comparability with other geothermal fields.\u003c/p\u003e\n \u003cp\u003eResistivity\u0026ndash;temperature correlations are employed to strengthen the interpretation of conductive clay caps, reservoir boundaries, and hydrothermal alteration zones (Savitri et al. \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e), allowing drilling targets to be proposed at depths where geophysical anomalies coincide with geochemical evidence of high‑temperature fluids (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). By integrating multidisciplinary datasets into a unified inversion and modeling framework, this study produces accurate and verifiable resource estimates. These results not only reduce exploration risk but also provide quantitative guidance for future drilling and development strategies, thereby advancing geothermal resource utilization in Banten Province and contributing to Indonesia\u0026rsquo;s broader energy security goals.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Methodology","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTo address these limitations, this study integrates magnetotelluric (MT) and time‑domain electromagnetic (TDEM) data with geological and geochemical constraints, applying both two‑dimensional inversion and three‑dimensional modeling to delineate upflow and outflow zones, quantify reservoir parameters, and identify drilling targets in accordance with national standards (SNI 6169:2018). This integrated approach is designed to overcome the shortcomings of earlier qualitative interpretations and generic volumetric assessments (Mu\u0026ntilde;oz \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), thereby providing a more reliable and site‑specific evaluation of geothermal resources.\u003c/p\u003e \u003cp\u003eBuilding on the need for integrated and quantitative analysis, the research employs a multidisciplinary workflow tailored to characterize the geothermal system at Mount Parakasak. The approach combines geophysical surveys (MT and TDEM), geological mapping, and geochemical investigations within a unified inversion and modeling framework. This ensures that geophysical anomalies are interpreted in direct relation to lithological units, structural features, and hydrothermal alteration zones, thereby reducing ambiguity and enhancing confidence in resource estimates (Belyakov \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). By explicitly linking resistivity anomalies to geochemical signatures and geological structures, the workflow strengthens the correlation between subsurface models and observable manifestations, which is critical for reducing exploration risk (Kremer et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe methodology adopted in this study was structured into three interconnected stages. First, data acquisition involved the systematic collection of magnetotelluric (MT) soundings and time‑domain electromagnetic (TDEM) measurements, complemented by geological field mapping and geochemical sampling of hot springs and fumaroles. These multidisciplinary datasets provided complementary constraints on subsurface resistivity, lithology, and fluid chemistry, ensuring that electrical anomalies were interpreted within a robust geological and geochemical framework (Alvarado et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In the second stage, data processing and inversion were carried out by correcting static shift effects using TDEM near‑surface resistivity, followed by one‑dimensional and two‑dimensional inversion to validate resistivity\u0026ndash;depth profiles. The resulting 2D sections were subsequently assembled into a coherent three‑dimensional resistivity volume through spatial interpolation and inversion, constrained by geological structures and geochemical indicators (Ren and Kalscheuer \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This integration ensured that the final resistivity model honored both geophysical measurements and independent geological evidence, thereby improving model fidelity. Finally, interpretation and resource assessment focused on delineating conductive clay caps, upflow and outflow zones, and reservoir boundaries. Resistivity anomalies were correlated with geochemical signatures to estimate reservoir temperature and thickness (Lichoro et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), while volumetric calculations of geothermal potential were performed in accordance with SNI 6169:2018. This stage provided quantitative guidance for drilling target selection and resource evaluation, ensuring methodological consistency and comparability with other Indonesian geothermal fields.\u003c/p\u003e \u003cp\u003eThis integrated workflow provides a reproducible framework for geothermal exploration, ensuring that resistivity anomalies are interpreted within their geological and geochemical context. By combining multiple datasets into a single inversion and modeling process, the study reduces uncertainty, improves the reliability of resource estimates, and offers practical guidance (Cao et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) for exploration drilling strategies in Banten Province. More broadly, the methodology demonstrates how multidisciplinary integration can enhance geothermal resource assessments in complex volcanic terrains, contributing to Indonesia\u0026rsquo;s national energy security and advancing global best practices in geothermal exploration.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy area\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe study area is located within the Mount Parakasak region of Banten Province (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), approximately 100 km west of Jakarta, and spans the administrative boundaries of Pandeglang and Serang Regencies (6\u0026deg;20\u0026prime;\u0026ndash;6\u0026deg;30\u0026prime; S, 105\u0026deg;50\u0026prime;\u0026ndash;106\u0026deg;00\u0026prime; E). The terrain is characterized by undulating hills with elevations ranging from 970 to 1050 m above sea level and slope gradients of 20\u0026deg;\u0026ndash;45\u0026deg;, reflecting the influence of volcanic morphology and erosional processes. Land use varies according to topography, with dense forest cover on the upper slopes, rice fields and agricultural plots on gentler terrain, and settlements concentrated in valley areas. This distribution highlights the interaction between geomorphology and human activity, which is typical of volcanic landscapes in western Java.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eHydrothermal manifestations provide direct evidence of geothermal activity in the region (Ishitsuka et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The Kaipohan mofette, located on the northern flank, releases carbon dioxide gas through diffuse soil degassing, while the Batukuwung hot spring emerges along fault‑controlled zones in the southern sector (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These features indicate active fluid circulation within the subsurface and suggest the presence of permeable structures that may serve as conduits for geothermal upflow (Chavanidis et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The spatial association of surface manifestations with structural lineaments further supports the interpretation of Mount Parakasak as a hydrothermal system (Rafiq et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Together, the geomorphological setting, land use patterns, and hydrothermal features establish the study area as a promising target for integrated geophysical and geochemical investigations aimed at delineating subsurface reservoirs and assessing geothermal potential.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eGeological Setting\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe Mount Parakasak region forms part of the western Java volcanic arc, which developed in response to the ongoing subduction of the Indo‑Australian Plate beneath the Eurasian Plate (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The area is dominated by Quaternary volcanic deposits, including andesitic to basaltic lava flows, pyroclastic sequences, and reworked volcaniclastic sediments (Susilohadi et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These lithologies are interbedded with older Tertiary formations, such as sandstones and shales, which locally act as impermeable barriers to fluid migration. The volcanic stratigraphy is characterized by alternating permeable and impermeable horizons, creating favorable conditions for geothermal reservoir development.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e illustrates the distribution of Quaternary volcanic deposits (andesitic\u0026ndash;basaltic lava flows, pyroclastic sequences, and volcaniclastic sediments) interbedded with older Tertiary formations. Major NW\u0026ndash;SE and NE\u0026ndash;SW fault systems are highlighted, showing their spatial association with hydrothermal manifestations such as the Kaipohan mofette and Batukuwung hot spring. Areas of hydrothermal alteration (argillic and propylitic zones) are indicated, delineating conductive clay caps that overlie potential geothermal reservoirs (Stimac et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Elevation contours (970\u0026ndash;1050 m) and land-use patterns (forest, agriculture, settlements) are included to provide geomorphological context. This map forms the basis for integrating geophysical and geochemical datasets in the delineation of reservoir boundaries and fluid pathways.\u003c/p\u003e \u003cp\u003eStructurally, the region is dissected by NW\u0026ndash;SE and NE\u0026ndash;SW trending faults, which are consistent with regional tectonic stress orientations. These faults and associated fracture zones provide pathways for hydrothermal fluids, as evidenced by the alignment of surface manifestations such as the Kaipohan mofette and Batukuwung hot spring. Hydrothermal alteration, including argillic and propylitic assemblages, is observed along fault zones and in areas of intense fumarolic activity, further supporting the presence of active fluid circulation (Kereszturi et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The conductive clay caps identified in geophysical surveys are interpreted as alteration products of volcanic rocks, which overlie potential geothermal reservoirs at depth.\u003c/p\u003e \u003cp\u003eTogether, the lithological framework, stratigraphic variability, and structural controls define a complex volcanic‑hydrothermal system at Mount Parakasak. This geological setting provides the basis for integrating geophysical and geochemical data, enabling the delineation of reservoir boundaries and the identification of upflow and outflow zones critical to geothermal resource assessment.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eData Acquisition\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eGeophysical, geological, and geochemical datasets were acquired to support the integrated characterization of the Mount Parakasak geothermal system. Magnetotelluric (MT) surveys were conducted along six profiles, yielding a total of 36 EDI‑formatted soundings (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). These soundings provided deep resistivity information essential for delineating subsurface structures, including clay caps, reservoir zones, and fault‑controlled fluid pathways. To enhance near‑surface resolution and correct for static shift effects inherent in MT data, time‑domain electromagnetic (TDEM) measurements were performed at each MT station (Krivochieva and Chouteau \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). The TDEM data enabled calibration of shallow resistivity values and improved the accuracy of inversion results, particularly in areas with complex topography and heterogeneous surface conditions (Wang et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eGeological mapping was carried out in parallel, focusing on lithological boundaries, structural lineaments, and zones of hydrothermal alteration. Field observations documented the distribution of volcanic and sedimentary units, fault orientations, and surface manifestations such as fumaroles and hot springs. These geological features were used to constrain geophysical models and interpret resistivity anomalies in relation to known lithologies and structural controls.\u003c/p\u003e \u003cp\u003eGeochemical investigations included fluid sampling from the Kaipohan mofette and Batukuwung hot spring. Samples were analyzed for major ions, stable isotopes (δ\u0026sup1;⁸O, δD), and gas compositions (CO₂, H₂S, CH₄), with geothermometric calculations applied to estimate subsurface temperatures. These geochemical signatures provided independent validation of reservoir conditions inferred from resistivity models and helped identify zones of active upflow.\u003c/p\u003e \u003cp\u003eAll datasets were provided by PT. Sintesa Banten Geothermal and the National Nuclear Energy Agency of Indonesia (BATAN), ensuring consistency in acquisition protocols and data quality. The integration of these multidisciplinary datasets forms the foundation for subsequent inversion, modeling, and resource assessment workflows.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eData Processing and Inversion\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eFollowing acquisition, geophysical datasets were processed to enhance signal quality and prepare for inversion modeling. Magnetotelluric (MT) data were first examined for noise, and static shift corrections were applied using co‑located time‑domain electromagnetic (TDEM) measurements. The TDEM data provided near‑surface resistivity values that served as calibration points, ensuring that shallow MT responses were accurately anchored and minimizing distortion caused by lateral resistivity contrasts.\u003c/p\u003e \u003cp\u003eInversion was conducted in two stages. One‑dimensional (1D) inversion was applied to individual MT soundings to generate preliminary resistivity\u0026ndash;depth profiles and identify anomalous zones. These results informed the setup of two‑dimensional (2D) inversion along each survey line, using a smooth‑occam algorithm to resolve lateral and vertical resistivity variations. The 2D resistivity sections revealed conductive zones interpreted as clay caps, resistive cores associated with potential reservoirs, and fault‑controlled discontinuities indicative of fluid pathways.\u003c/p\u003e \u003cp\u003eTo construct a comprehensive subsurface model, multiple 2D profiles were interpolated and assembled into a three‑dimensional (3D) resistivity volume. This 3D model was constrained by geological mapping and geochemical indicators, including the spatial distribution of surface manifestations and isotopic geothermometry results. Integration of these datasets ensured that the resistivity model honored both geophysical measurements and independent geological evidence, thereby improving model fidelity and interpretive confidence.\u003c/p\u003e \u003cp\u003eThe final resistivity volume served as the basis for delineating upflow and outflow zones, estimating reservoir geometry, and guiding volumetric resource calculations. All inversion procedures were performed using industry‑standard software and validated through sensitivity testing and cross‑profile correlation.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eInterpretation and Resource Assessment\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe integrated resistivity models, constrained by geological and geochemical datasets, were interpreted to delineate key features of the Mount Parakasak geothermal system. Conductive zones identified in the three‑dimensional resistivity volume were correlated with hydrothermal alteration assemblages observed in the field, confirming their role as clay caps that seal underlying reservoirs. Beneath these conductive layers, resistive anomalies were interpreted as potential reservoir zones, consistent with elevated subsurface temperatures inferred from isotopic and gas geothermometer analyses of hot spring and fumarole fluids.\u003c/p\u003e \u003cp\u003eUpflow zones were characterized by steeply dipping resistive structures aligned with NW\u0026ndash;SE and NE\u0026ndash;SW fault systems, which coincide spatially with surface manifestations such as the Kaipohan mofette and Batukuwung hot spring. These structural corridors are interpreted as permeable conduits facilitating the ascent of geothermal fluids. Outflow zones, in contrast, were delineated by lateral extensions of conductive anomalies, reflecting the dispersal of cooled fluids into surrounding formations. The integration of geochemical signatures with resistivity anomalies strengthened the interpretation of reservoir boundaries and fluid pathways, reducing uncertainty in subsurface characterization.\u003c/p\u003e \u003cp\u003eVolumetric resource assessment was conducted in accordance with SNI 6169:2018, applying locally justified parameters derived from geophysical and geochemical constraints rather than generic values. Reservoir thickness, porosity, and temperature estimates were extracted directly from the integrated models, ensuring methodological consistency and comparability with other Indonesian geothermal fields. The resulting resource estimates provide quantitative guidance for drilling target selection, highlighting zones where resistivity anomalies, structural permeability, and geochemical evidence converge.\u003c/p\u003e \u003cp\u003eThis multidisciplinary interpretation demonstrates the value of integrating MT and TDEM surveys with geological and geochemical data. By reducing reliance on qualitative assumptions and generic parameters, the study produces verifiable resource estimates that strengthen exploration strategies and support sustainable geothermal development in Banten Province.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatic Shift Correction\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eStatic shift is a common distortion in magnetotelluric (MT) data, arising from near‑surface heterogeneities and galvanic effects that cause vertical offsets in apparent resistivity curves. If uncorrected, these distortions can lead to erroneous interpretations of subsurface resistivity structures. To address this issue, time‑domain electromagnetic (TDEM) measurements were acquired at each MT station and used to calibrate shallow resistivity values. The TDEM data provided independent near‑surface constraints, enabling correction of static shift and alignment of transverse electric (TE) and transverse magnetic (TM) curves.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAs illustrated in Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, the application of TDEM corrections successfully eliminated static offsets, producing consistent TE and TM responses across multiple profiles. This alignment improved the accuracy of resistivity estimates and enhanced confidence in the reliability of the dataset. Following correction, one‑dimensional (1D) inversions were performed for each MT sounding to validate resistivity\u0026ndash;depth trends. The 1D inversion results confirmed the presence of conductive layers at shallow depths, interpreted as clay caps, underlain by resistive zones associated with potential geothermal reservoirs (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe consistency of corrected resistivity\u0026ndash;depth profiles across stations demonstrates the robustness of the static shift correction procedure. By integrating TDEM calibration, the study ensures that resistivity anomalies reflect true subsurface conditions rather than artifacts of surface heterogeneity. This methodological refinement reduces uncertainty in reservoir delineation, strengthens the correlation between geophysical models and geological\u0026ndash;geochemical evidence, and provides a reliable foundation for subsequent two‑dimensional (2D) and three‑dimensional (3D) inversion and resource assessment.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eResistivity Structure\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe two‑dimensional (2D) resistivity sections derived from magnetotelluric (MT) inversion provide the first level of subsurface characterization along individual survey lines. Each profile consistently reveals a shallow conductive horizon with resistivity values of ~\u0026thinsp;100 Ω\u0026middot;m, interpreted as a smectite‑rich clay cap. Such alteration products are typical of high‑enthalpy geothermal systems, where circulating acidic fluids transform primary volcanic minerals into low‑resistivity clays. The lateral continuity of this horizon across multiple lines confirms its role as a regional cap rock, restricting vertical fluid migration and maintaining reservoir pressure.\u003c/p\u003e \u003cp\u003eFigures \u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e present representative two‑dimensional (2D) resistivity cross‑sections along each survey trajectory. The profiles consistently delineate a shallow conductive horizon (~\u0026thinsp;100 Ω\u0026middot;m), interpreted as a smectite‑rich clay cap, together with underlying resistive anomalies associated with high‑temperature reservoir zones. This visualization reinforces the interpretation of a laterally continuous alteration zone that effectively seals the reservoir, restricts vertical fluid migration, and maintains subsurface pressure conditions essential for geothermal system integrity.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eBeneath the clay cap, resistive anomalies are concentrated near the Kaipohan sector. These zones are interpreted as upflow regions where geothermal fluids ascend through fault‑controlled conduits. The resistivity signature reflects relatively unaltered volcanic rocks saturated with high‑temperature fluids. Geochemical analyses of fumarolic gases and hot spring fluids indicate reservoir temperatures of 240\u0026ndash;260\u0026deg;C, consistent with the resistivity anomalies observed. The spatial correlation between resistive structures, NW\u0026ndash;SE fault lineaments, and geochemical geothermometers strengthens the interpretation of Kaipohan as the principal upflow zone.\u003c/p\u003e \u003cp\u003eIn contrast, the Batukuwung hot spring is characterized by lateral conductive extensions trending away from the reservoir core. These features are interpreted as outflow zones where geothermal fluids migrate laterally beneath the clay cap before discharging at the surface. Measured discharge temperatures of 52\u0026ndash;75\u0026deg;C reflect the thermal decline associated with outflow processes. The conductive anomalies in this sector validate the geophysical interpretation of cooled fluid dispersal into surrounding formations.\u003c/p\u003e \u003cp\u003eInterpolation of multiple 2D sections into a three‑dimensional (3D) resistivity volume yields a coherent model of the Mount Parakasak geothermal system. Figure\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e presents the integrated 3D resistivity model, delineating three principal components: (i) a shallow conductive clay cap (~\u0026thinsp;100 Ω\u0026middot;m) consistent with smectite alteration, (ii) a resistive upflow zone near Kaipohan associated with reservoir temperatures of 240\u0026ndash;260\u0026deg;C, and (iii) an outflow zone at Batukuwung hot spring, expressed as conductive extensions linked to discharge temperatures of 52\u0026ndash;75\u0026deg;C. Structural lineaments constrain the geometry of these zones, highlighting fault‑controlled permeability pathways.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe integration of 2D and 3D resistivity models with geological and geochemical datasets reduces interpretive uncertainty and provides quantitative guidance for drilling target selection. This multidisciplinary approach demonstrates the effectiveness of static‑shift‑corrected MT data in producing reliable subsurface models and establishes a robust framework for reservoir characterization and resource assessment in accordance with SNI 6169:2018.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDrilling Targets\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe integrated resistivity\u0026ndash;geochemical model provides quantitative guidance for the selection of drilling targets within the Mount Parakasak geothermal system. Resistivity anomalies identified at depths of approximately 1500 m coincide spatially with geochemical evidence of high‑temperature fluids, including gas geothermometer estimates of 240\u0026ndash;260\u0026deg;C in the Kaipohan sector. These resistive zones are interpreted as permeable reservoir rocks saturated with geothermal fluids, bounded above by a smectite‑rich clay cap. The convergence of geophysical anomalies, structural permeability, and geochemical signatures strengthens confidence in the reliability of these targets and reduces uncertainty in reservoir delineation.\u003c/p\u003e \u003cp\u003eThe proposed drilling depth of ~\u0026thinsp;1500 m is consistent with the vertical extent of resistive anomalies observed in the three‑dimensional model and aligns with reservoir thickness estimates derived from volumetric calculations. This depth is expected to intersect the high‑enthalpy reservoir zone while remaining below the conductive clay cap, thereby maximizing the likelihood of encountering productive fluid pathways. Structural controls, particularly NW\u0026ndash;SE fault lineaments, provide additional justification for drilling in these locations, as they act as conduits for geothermal upflow.\u003c/p\u003e \u003cp\u003eIn addition to production wells, the model highlights outflow zones such as the Batukuwung hot spring as potential recharge sites for reinjection. These zones are characterized by lateral conductive extensions and discharge temperatures of 52\u0026ndash;75\u0026deg;C, reflecting cooled geothermal fluids migrating away from the reservoir core. Reinjection into these outflow zones would enhance reservoir sustainability by maintaining pressure, facilitating fluid circulation, and minimizing environmental impacts associated with surface discharge.\u003c/p\u003e \u003cp\u003eTogether, the delineation of drilling targets and reinjection sites demonstrates the value of integrating magnetotelluric (MT) and time‑domain electromagnetic (TDEM) surveys with geological and geochemical datasets. This multidisciplinary approach ensures that drilling decisions are based on verifiable subsurface evidence, thereby improving exploration efficiency and supporting long‑term geothermal development in Banten Province.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe integration of magnetotelluric (MT), time‑domain electromagnetic (TDEM), and three‑dimensional (3D) inversion modeling establishes a robust framework for geothermal exploration in complex volcanic terrains such as Mount Parakasak. By correcting static shift effects with TDEM data, the MT responses were calibrated to reflect true subsurface resistivity, thereby improving the reliability of inversion results. This methodological refinement ensures that resistivity anomalies are not artifacts of near‑surface heterogeneity but instead represent genuine subsurface features.\u003c/p\u003e \u003cp\u003eThe resulting anomalies correlate strongly with hydrothermal alteration zones and geochemical signatures, validating the delineation of upflow and outflow processes. Conductive horizons of ~\u0026thinsp;100 Ω\u0026middot;m correspond to smectite‑rich clay caps, which act as impermeable seals above the reservoir. Beneath these caps, resistive anomalies near Kaipohan coincide with geochemical geothermometer estimates of 240\u0026ndash;260\u0026deg;C, confirming the presence of high‑temperature upflow zones. In contrast, lateral conductive extensions toward Batukuwung hot spring align with measured discharge temperatures of 52\u0026ndash;75\u0026deg;C, supporting their interpretation as outflow pathways. The consistency between geophysical anomalies, mineralogical alteration, and geochemical evidence strengthens confidence in the integrated model.\u003c/p\u003e \u003cp\u003eCompared to conventional two‑dimensional (2D) interpretations, the 3D resistivity model significantly reduces uncertainty by honoring geological constraints and eliminating assumptions about strike direction. Whereas 2D sections provide valuable line‑based insights, they are limited in capturing the full spatial complexity of geothermal systems. The 3D volume integrates multiple trajectories into a coherent subsurface representation, constrained by structural lineaments and alteration patterns. This approach enhances interpretive accuracy, improves reproducibility, and provides a more realistic basis for reservoir delineation.\u003c/p\u003e \u003cp\u003eFrom an exploration perspective, the integrated workflow directly supports cost‑effective drilling strategies. By identifying high‑confidence targets at ~\u0026thinsp;1500 m depth within resistive upflow zones, the model reduces the risk of non‑productive wells. Simultaneously, the delineation of outflow zones provides potential recharge sites for reinjection, ensuring reservoir sustainability. The combined use of MT, TDEM, and 3D inversion thus advances geothermal resource assessment by linking geophysical anomalies to geological and geochemical evidence, aligning exploration practices with national standards such as SNI 6169:2018, and strengthening the scientific basis for geothermal development in Banten Province.\u0026lrm;\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis study demonstrates the effectiveness of integrating magnetotelluric (MT), time‑domain electromagnetic (TDEM), and three‑dimensional (3D) inversion modeling for geothermal exploration in volcanic terrains. The specific conclusions are as follows:\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eActive geothermal system at Mount Parakasak: The resistivity model delineates a shallow conductive clay cap (~\u0026thinsp;100 Ω\u0026middot;m) interpreted as smectite‑rich hydrothermal alteration, a resistive upflow zone near Kaipohan associated with reservoir temperatures of 240\u0026ndash;260\u0026deg;C, and an outflow zone at Batukuwung hot spring characterized by discharge temperatures of 52\u0026ndash;75\u0026deg;C. These features collectively confirm the presence of an active hydrothermal system with fault‑controlled permeability pathways.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eImproved resistivity interpretation through integrated modeling: The combined use of MT and TDEM data, corrected for static shift, and interpolated into a 3D resistivity volume significantly enhances subsurface characterization. This approach reduces interpretive uncertainty compared to conventional 2D models by honoring geological constraints and eliminating strike‑direction assumptions, thereby strengthening correlations between resistivity anomalies, alteration mineralogy, and geochemical signatures.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eDrilling targets supported by geophysical\u0026ndash;geochemical correlations: The integrated model identifies high‑confidence drilling targets at ~\u0026thinsp;1500 m depth within resistive upflow zones. These targets are validated by reservoir temperature estimates from geochemical geothermometers, ensuring that drilling strategies are both scientifically justified and cost‑effective. Outflow zones provide potential recharge sites for reinjection, supporting long‑term reservoir sustainability.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAlignment with national standards and reproducibility: The methodology conforms to SNI 6169:2018, ensuring consistency with nationally recognized volumetric resource assessment practices. By integrating geophysical, geological, and geochemical datasets, the workflow provides a reproducible framework for geothermal exploration in Indonesia, offering a model that can be applied to other volcanic geothermal prospects across the archipelago.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn summary, the integration of MT, TDEM, and 3D inversion modeling advances geothermal resource assessment by linking resistivity anomalies to hydrothermal processes and geochemical evidence. The approach reduces exploration risk, supports sustainable reservoir management, and contributes to the broader development of Indonesia\u0026rsquo;s geothermal potential.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank PT. Sintesa Banten Geothermal and BATAN for providing datasets and technical support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u003c/strong\u003e\u003cstrong\u003econtributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eE.Minarto: Conceptualization; Methodology; Data curation; Formal analysis; Investigation; Writing \u0026ndash; review \u0026amp; editing; Visualization; Project administration; Supervision. F.Zepanya: Resources; Data acquisition; Validation; Writing \u0026ndash; original draft; Funding acquisition.\u0026nbsp;All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by PT. Sintesa Banten Geothermal, Jakarta, Indonesia, through provision of geophysical and geochemical datasets. Additional institutional support was provided by the Department of Physics, Institut Teknologi Sepuluh Nopember (ITS), Surabaya, Indonesia. No external grant funding was received for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eavailability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting\u003c/strong\u003e\u003cstrong\u003einterests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAhumada MF, Guevara L, Favetto A, et al (2022) Electrical resistivity structure in the Tocomar geothermal system obtained from 3-D inversion of audio-magnetotelluric data (Central Puna, NW Argentina). Geothermics 104:102436. https://doi.org/10.1016/j.geothermics.2022.102436\u003c/li\u003e\n\u003cli\u003eAlvarado H, Pescador J, Landinez J, et al (2025) Quantitative Integration of Audio-Magnetotelluric Sounding and Resistivity Well Logs for Groundwater Studies. Water 17:3389. https://doi.org/10.3390/w17233389\u003c/li\u003e\n\u003cli\u003eBelyakov N (2019) Geothermal energy. In: Sustainable Power Generation. Elsevier, pp 475\u0026ndash;500\u003c/li\u003e\n\u003cli\u003eCao X, Liu Z, Hu C, et al (2024) Three-Dimensional Geological Modelling in Earth Science Research: An In-Depth Review and Perspective Analysis. Minerals 14:686. https://doi.org/10.3390/min14070686\u003c/li\u003e\n\u003cli\u003eChavanidis K, Stampolidis A, Salem A, et al (2025) Gravity modeling of a prospective geothermal field of a hot spring in Western Saudi Arabia. Journal of Volcanology and Geothermal Research 461:108307. https://doi.org/10.1016/j.jvolgeores.2025.108307\u003c/li\u003e\n\u003cli\u003eElshehabi T, Alfehaid M (2025) Sustainable Geothermal Energy: A Review of Challenges and Opportunities in Deep Wells and Shallow Heat Pumps for Transitioning Professionals. Energies 18:811. https://doi.org/10.3390/en18040811\u003c/li\u003e\n\u003cli\u003eGiambiagi L, \u0026Aacute;lvarez P, Spagnotto S, et al (2019) Geomechanical model for a seismically active geothermal field: Insights from the Tinguiririca volcanic-hydrothermal system. Geoscience Frontiers 10:2117\u0026ndash;2133. https://doi.org/10.1016/j.gsf.2019.02.006\u003c/li\u003e\n\u003cli\u003eHidayat A, Suryanto, Utomowati R, Setiawan JV (2023) Assessment of the Relationship Between Repose Period and Eruption Magnitude of Gamalama Volcano for Community Preparedness in Ternate Island \u0026ndash; Indonesia. IJSDP 18:773\u0026ndash;779. https://doi.org/10.18280/ijsdp.180313\u003c/li\u003e\n\u003cli\u003eHochstein MP, Sudarman S (2008) History of geothermal exploration in Indonesia from 1970 to 2000. Geothermics 37:220\u0026ndash;266. https://doi.org/10.1016/j.geothermics.2008.01.001\u003c/li\u003e\n\u003cli\u003eIshitsuka K, Ojima H, Mogi T, et al (2022) Characterization of hydrothermal alteration along geothermal wells using unsupervised machine-learning analysis of X-ray powder diffraction data. Earth Sci Inform 15:73\u0026ndash;87. https://doi.org/10.1007/s12145-021-00694-3\u003c/li\u003e\n\u003cli\u003eKassem MA, Moscariello A (2025) Geothermal energy: A sustainable and cost-effective alternative for clean energy production and climate change mitigation. Sustainable Futures 10:101247. https://doi.org/10.1016/j.sftr.2025.101247\u003c/li\u003e\n\u003cli\u003eKereszturi G, Schaefer LN, Miller C, Mead S (2020) Hydrothermal Alteration on Composite Volcanoes: Mineralogy, Hyperspectral Imaging, and Aeromagnetic Study of Mt Ruapehu, New Zealand. Geochem Geophys Geosyst 21:e2020GC009270. https://doi.org/10.1029/2020GC009270\u003c/li\u003e\n\u003cli\u003eKremer T, Ars JM, Gaubert-Bastide T, et al (2025) Chapter 6 \u0026bull; The use of passive seismic methods for Geothermal exploration and monitoring. In: Geophysics in geothermal exploration: a review. EDP Sciences, pp 181\u0026ndash;222\u003c/li\u003e\n\u003cli\u003eKrivochieva S, Chouteau M (2003) Integrating TDEM and MT methods for characterization and delineation of the Santa Catarina aquifer (Chalco Sub-Basin, Mexico). Journal of Applied Geophysics 52:23\u0026ndash;43. https://doi.org/10.1016/S0926-9851(02)00231-8\u003c/li\u003e\n\u003cli\u003eKurnianto B (2025) THE ROLE OF FRACTURE DENSITY IN MANIFESTATIONS OF UPFLOW AND OUTFLOW ZONES OF AN UNGARAN MOUNTAIN GEOTHERMAL SYSTEM. GEOMATE 29:. https://doi.org/10.21660/2025.132.4905\u003c/li\u003e\n\u003cli\u003eLetelier JA, O\u0026rsquo;Sullivan J, Reich M, et al (2021) Reservoir architecture model and heat transfer modes in the El Tatio-La Torta geothermal system, Central Andes of northern Chile. Geothermics 89:101940. https://doi.org/10.1016/j.geothermics.2020.101940\u003c/li\u003e\n\u003cli\u003eLichoro CM, \u0026Aacute;rnason K, Cumming W (2017) Resistivity imaging of geothermal resources in northern Kenya rift by joint 1D inversion of MT and TEM data. Geothermics 68:20\u0026ndash;32. https://doi.org/10.1016/j.geothermics.2017.02.006\u003c/li\u003e\n\u003cli\u003eMu\u0026ntilde;oz G (2014) Exploring for Geothermal Resources with Electromagnetic Methods. Surv Geophys 35:101\u0026ndash;122. https://doi.org/10.1007/s10712-013-9236-0\u003c/li\u003e\n\u003cli\u003eNasruddin, Idrus Alhamid M, Daud Y, et al (2016) Potential of geothermal energy for electricity generation in Indonesia: A review. Renewable and Sustainable Energy Reviews 53:733\u0026ndash;740. https://doi.org/10.1016/j.rser.2015.09.032\u003c/li\u003e\n\u003cli\u003eRafiq J, Abu-Mahfouz IS, Chavanidis K, et al (2025) Spatial distribution of structural lineaments in the Al-Lith geothermal field, western Saudi Arabia: Remote sensing and aeromagnetic data analysis. Journal of Asian Earth Sciences: X 13:100191. https://doi.org/10.1016/j.jaesx.2025.100191\u003c/li\u003e\n\u003cli\u003eRen Z, Kalscheuer T (2020) Uncertainty and Resolution Analysis of 2D and 3D Inversion Models Computed from Geophysical Electromagnetic Data. Surv Geophys 41:47\u0026ndash;112. https://doi.org/10.1007/s10712-019-09567-3\u003c/li\u003e\n\u003cli\u003eSavitri KP, Hecker C, Van Der Meer FD, Sidik RP (2021) VNIR-SWIR infrared (imaging) spectroscopy for geothermal exploration: Current status and future directions. Geothermics 96:102178. https://doi.org/10.1016/j.geothermics.2021.102178\u003c/li\u003e\n\u003cli\u003eStimac J, Ganefianto N, Baroek M, et al (2019) An overview of the Muara Laboh geothermal system, Sumatra. Geothermics 82:150\u0026ndash;167. https://doi.org/10.1016/j.geothermics.2019.05.008\u003c/li\u003e\n\u003cli\u003eSuharmanto P, Fitria AN, Ghaliyah S (2015) Indonesian Geothermal Energy Potential as Source of Alternative Energy Power Plant. KEn 1:119. https://doi.org/10.18502/ken.v1i1.325\u003c/li\u003e\n\u003cli\u003eSumotarto U, Hendrasto F, Triadi W (2019) Volcanostratigraphy of Batukuwung-Parakasak Geothermal Area, Serang Regency, West Java. J Phys: Conf Ser 1363:012048. https://doi.org/10.1088/1742-6596/1363/1/012048\u003c/li\u003e\n\u003cli\u003eSusilohadi S, Novico F, Husson L, et al (2024) Quaternary deposition and erosion in the northeastern Sunda Strait: An interplay between sea level, tectonics, and magmatic activity. Journal of Asian Earth Sciences: X 12:100179. https://doi.org/10.1016/j.jaesx.2024.100179\u003c/li\u003e\n\u003cli\u003eSzklarz SP, Barros EGD, Khoshnevis Gargar N, et al (2024) Geothermal field development optimization under geomechanical constraints and geological uncertainty: Application to a reservoir with stacked formations. Geothermics 123:103094. https://doi.org/10.1016/j.geothermics.2024.103094\u003c/li\u003e\n\u003cli\u003eTripathi A, Low U, Karim A (2025) Deciphering structural framework of Bakreswar geothermal field, eastern India: insights from geophysical data analysis and 3D inversion modeling. Geothermics 133:103471. https://doi.org/10.1016/j.geothermics.2025.103471\u003c/li\u003e\n\u003cli\u003eWahid MN, Asif M, Khan MI, Khalid M (2025) A strategic analysis of geothermal energy for sustainable energy transition: Case study from Indonesia. Energy Conversion and Management: X 28:101303. https://doi.org/10.1016/j.ecmx.2025.101303\u003c/li\u003e\n\u003cli\u003eWamalwa AM, Serpa LF (2013) The investigation of the geothermal potential at the Silali volcano, Northern Kenya Rift, using electromagnetic data. Geothermics 47:89\u0026ndash;96. https://doi.org/10.1016/j.geothermics.2013.02.001\u003c/li\u003e\n\u003cli\u003eWang X, Cai H, Liu L, et al (2023) Three-Dimensional Inversion of Long-Offset Transient Electromagnetic Method over Topography. Minerals 13:908. https://doi.org/10.3390/min13070908\u003c/li\u003e\n\u003cli\u003eYudha S, Tjahjono B, Longhurst P (2022) Unearthing the Dynamics of Indonesia\u0026rsquo;s Geothermal Energy Development. Energies 15:5009. https://doi.org/10.3390/en15145009\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":"Magnetotelluric, TDEM, resistivity inversion, upflow–outflow zones, geothermal modeling, ‎Mount Parakasak ‎","lastPublishedDoi":"10.21203/rs.3.rs-8506977/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8506977/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMount Parakasak in Banten hosts promising yet underexplored geothermal resources. This study integrates two-dimensional magnetotelluric (MT) and time-domain electromagnetic (TDEM) surveys with three-dimensional inversion modeling to delineate subsurface resistivity structures and characterize the geothermal system. Thirty-six MT soundings, corrected for static shift using TDEM data, were inverted to generate 2D resistivity sections and interpolated into a 3D resistivity volume constrained by geological and geochemical datasets. Results reveal a conductive clay cap (~100 Ω·m) and an upflow zone near the Kaipohan manifestation, associated with reservoir temperatures of 240–260 °C. The Batukuwung hot spring marks an outflow zone at 52–75 °C. Integrated modeling supports the presence of an active geothermal system with drilling targets at ~1500 m depth. These findings provide quantitative guidance for exploration and resource assessment, advancing geothermal development in Banten Province.\u003c/p\u003e","manuscriptTitle":"Advancing Geothermal Exploration With 2D Magnetotelluric and 3D Modeling: Case Study From Mount Parakasak, Banten, Indonesia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-16 00:09:00","doi":"10.21203/rs.3.rs-8506977/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":"9172ebb9-6da9-4bf9-9248-a357432333b9","owner":[],"postedDate":"January 16th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-10T09:12:15+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-16 00:09:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8506977","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8506977","identity":"rs-8506977","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}