About

Dr. Shuvajit Bhattacharya is a Research Associate Professor at the Bureau of Economic Geology. His areas of specialization include Petrophysics, Geophysics, and Machine Learning. His work involves applying advanced techniques in these fields to enhance understanding of subsurface energy systems and geological formations. Dr. Bhattacharya's research contributes to the development of innovative methods for analyzing and interpreting geological and geophysical data, supporting energy exploration and resource recovery efforts.

Research topics

• Geology
• Computer science
• Artificial intelligence
• Seismology
• Petrology

Selected publications

• Building a Picture of the Geological Hydrogen and Helium System in West Texas, USA

  2026-03-14

  articleOpen access

  Geological hydrogen and helium exploration have increased substantially in recent years, driven by requirements for the energy transition and high-tech industries. These efforts have highlighted the need for fundamental understanding of the underlying geologic systems influencing the generation, migration, and storage of these gases. Since hydrogen (H2) and helium (He) are naturally produced in the subsurface via chemical and nuclear reactions involving major igneous rock types that are common in crystalline basements (e.g., mafic/ultramafic for hydrogen and felsic for helium), predicting and mapping basement terranes and lithologies has become a key focus in these new exploration efforts. Further, historical data from oil and gas wells have suggested the presence He and H2 at depth. While these findings offer promising leads, many of these measurements are outdated and require modern verification to assess their current relevance and potential for commercial accumulation.Our research aims to generate regional-scale interpretations of the He and H2 system across the state of Texas. To this end, we explore field and well data to complement and refine existing basement lithology interpretations previously derived from core and geophysical data. The main contribution of our work is the application of Bayesian analysis as the basis for joint inversion of gravity and aeromagnetic data to produce probabilistic estimates of basement lithologies throughout the state. Secondly, the extensive analysis of soil and well gas samples for determining He and H2 generation and storage. Thirdly, improve well log analysis of basin scale lithological interpretations to increase the accuracy of the hydrogen and helium migration and storage potential across the system. These methods ultimately aim to significantly improve the predictive capability of He and H2 plays based on a suite of geochemical and geophysical data.The research is currently focusing on the Permian Basin and Ouachita Thrust Belt region in West Texas (USA) that have traditionally been targeted for oil and gas exploration. The Mesoproterozoic basement of the Permian Basin forms an intractonic sag and consists of a complex assemblage of igneous and metamorphic rocks, which are rock types known to generate He and H2. Interestingly, the basin comprises a 300-1200 m thick Permian evaporite sequence, which may act as an effective seal for basement-sourced He and H2. A soil gas survey was conducted to identify potential emission zones and to evaluate the sealing potential of the evaporite sequence. This survey was complemented by well data to investigate gas presence below any overburden. In the most favorable areas, long-term H₂ monitoring was implemented to assess possible cyclicity (e.g., diurnal, seasonal) in gas emissions. Basement rock sampling and well gas analyses provide insights into both past and potentially ongoing reactions beneath the overburden, helping to constrain the He and H2 system and the geological controls.In this presentation, we demonstrate this approach to generate Texas-wide basement lithology maps. We focus on specific compositions relevant to geologic He and H2 exploration, and highlight the utility of these maps to help focus future exploration and development efforts for this rapidly growing field of study.

  PublisherDOI

• Critical review of lithium recovery from geothermal brines with implications for Smackover Formation, USA

  Energy Conversion and Management X · 2026-02-13

  articleOpen access

  • Machine learning maps lithium–geothermal co-resources in Smackover Formation. • Review of direct lithium extraction and sorbent technologies for geothermal brines. • Framework proposed for sustainable co-production of lithium and geothermal energy. The rapidly growing demand for lithium, a critical element for energy storage and national security technologies, has intensified concerns over the long-term availability and environmental impact of conventional lithium sources, such as hard-rock mining. To meet future demand, it is vital to explore unconventional resources that can provide sustainable domestic supplies. Geothermal brines, produced as a byproduct of geothermal energy generation, offer a promising alternative for lithium recovery by leveraging existing infrastructure and renewable energy production. In particular, the Smackover Formation, an extensive reservoir of high-salinity brines spanning Arkansas, Texas, Louisiana, Mississippi, and Alabama in the U.S. Gulf Coast, holds significant untapped lithium reserves. Co-producing geothermal energy and lithium from these brines aligns with sustainable extraction objectives while addressing resource scarcity. This review synthesizes current knowledge of lithium occurrence in the Smackover Formation and geothermal resources in the region, while also exploring how emerging tools such as machine learning can enhance resource targeting and co-production efficiency. Finally, we discuss key technical challenges and outline future research directions needed to advance lithium extraction from geothermal brines and secure a resilient domestic supply chain

  PublisherDOI

• Electrofacies classification using supervised machine learning for Permian layered evaporitic sequences of the Delaware Basin, USA: implications for hydrogen storage potential

  Geoenergy · 2026-01-30

  article

  Evaporitic sequences offer significant potential for large-scale underground hydrogen storage (UHS) in salt caverns, but their geological heterogeneity poses challenges for cavern development. This study applies supervised machine learning for electrofacies classification in the Castile and Salado formations of the Delaware Basin, USA, to assess their suitability for UHS. The support vector machine, random forest and extreme gradient boosting (XGBoost) algorithms were assessed using conventional well logs calibrated with core data, with XGBoost achieving a superior performance for both formations. The models effectively captured distinctive mineralogical characteristics: the Castile Formation characterized by thicker, halite- and anhydrite-dominated beds, while the Salado Formation exhibited greater heterogeneity with interbedded non-evaporite rock layers. Core-log integration revealed well-log resolution limitations in capturing thin beds and subtle transitions. Integrated analysis of critical factors such as halite thickness and depth demonstrated that the Castile Formation's thicker, more uniform halite beds provide more favourable conditions for cavern development compared to the more complex Salado Formation, where heterogeneity and differential dissolution risks are greater. This study underscores the importance of electrofacies prediction in assessing layered evaporite sequences suitability for UHS. The developed workflow offers a scalable screening tool to support informed decision-making for site selection and risk assessment in diverse evaporitic settings worldwide.

  PublisherDOI

• Distribution of mafic and ultramafic rocks in the Southern Pecos Mafic Intrusive Complex, Texas: Assessing CO2 mineralization and hydrogen generation potential

  2026-02-10

  article

  Identifying the subsurface distribution and estimating volumes of mafic and ultramafic rocks has gained significant attention due to their role in carbon sequestration and hydrogen generation. We analyzed high-resolution magnetic anomalies to characterize the distribution of mafic and ultramafic rocks in the Southern Pecos Mafic Intrusive Complex (SPMIC), west Texas. This region is in the worldclass hydrocarbon-producing Permian Basin. We applied a deterministic Gauss-Newton, gradient-based inversion approach to map the subsurface 3D susceptibility distribution beneath the study area. The 3D inversion results revealed a broad, thick, high-magnetic susceptibility (HS) body with an irregular shape, varying in width between ~7 and ~15 km and extending from ~1 km to ~4 km in depth. The volume of this body was estimated to be approximately 1,180 km3. These findings highlight the potential of the SPMIC region as a future site for carbon mineralization and stimulated geologic hydrogen.

  PublisherDOI

• Preliminary Evaluation and Hydrocarbon Resource Assessment of the Barnett Shale in the Permian Basin, Texas and New Mexico

  Abstracts with programs - Geological Society of America · 2025-01-01

  article
  PublisherDOI

• Assessment of Seismic Hazard Potential for a Geothermal Field: A Case Study in West Texas

  The Seismic Record · 2025-04-01

  articleOpen access

  Abstract The El Paso (TX)–Ciudad Juárez (MX) metropolitan area, located within the tectonically active Rio Grande Rift, has historically recorded shaking from nearby high-magnitude earthquakes (e.g., the 1887 Mw 7.6 in Sonora, MX, and the 1931 Mw 5.8 in Valentine, Texas). Application of the machine-learning (ML)-based EarthQuake Compact Convolutional Transformer (EQCCT) algorithm to seismic data from 2008 to 2011 resulted in the detection of 645 seismic events in the area, lowering the magnitude detection threshold compared to public catalogs (e.g., U.S. Geological Survey ComCat with 35 events in the same period). Manual review and relocation using NonLinLoc and hierarchical clustering with GrowClust3D revealed seven seismic clusters: four clusters align with mapped Quaternary faults, whereas three clusters correspond to previously unrecognized seismogenic structures. These results demonstrate that advanced ML techniques can enhance earthquake detection and refine the understanding of regional seismicity. With new geothermal projects on the horizon in West Texas, the enhanced seismic catalog provides a more robust basis for assessing seismic hazard potential, which is critical for guiding safe geothermal development in the region.

  PublisherOA PDFDOI

• Opportunities for Conventional and Advanced Geothermal Systems in the Wilcox Group on the Texas Gulf Coast

  Abstracts with programs - Geological Society of America · 2025-01-01

  article1st authorCorresponding
  PublisherDOI

• Assessing the Potential for Co2 Sequestration of a Saline Aquifer in the Frio Formation, South Texas, USA

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access
  PublisherDOI

• Natural Hydrogen and Helium Resources in Texas: Where are the Sweet Spots?

  Abstracts with programs - Geological Society of America · 2025-01-01

  article
  PublisherDOI

• Characterizing Subsurface Mafic and Ultramafic Rock Distributions and Volumes using Potential Field Data: Insights from Southeast Minnesota

  Abstracts with programs - Geological Society of America · 2025-01-01

  article
  PublisherDOI

Frequent coauthors

• Sumit Verma

  The University of Texas of the Permian Basin

  18 shared

• Sarp Karakaya

  8 shared

• Osareni C. Ogiesoba

  Bureau of Economic Analysis

  8 shared

• Guochang Wang

  Jinan University

  7 shared

• Timothy R. Carr

  West Virginia University

  7 shared

• Brian Casey

  6 shared

• Ramón Treviño

  Bureau of Economic Analysis

  6 shared

• Kenneth W. Wisian

  Bureau of Economic Analysis

  6 shared

Education

• Ph.D./Geology, Geology & Geography

  West Virginia University

  2016

• M.Sc./Applied Geophysics, Earth Sciences

  Indian Institute of Technology Bombay

  2010

• B.Sc./Geology (Honors), Geology

  University of Calcutta

  2008

Awards & honors

• A.I. Levorsen Award from the Gulf Coast Section of American…
• J. Clarence Karcher Award from the Society of Exploration Ge…
• Honorable Mention of poster presentation (2nd place) at the…
• 1st place at the Society of Petrophysicists and Well Log Ana…
• 1st place at the Pacific Section AAPG Expo (Northridge) Post…