Imaging the Geothermal System Using MT and CSEM Data in the Xinzhou Geothermal Field, Northern China

Meihua Wei , Yanxin Wang , Wenlong Zhou , Qinghai Guo , Weiyang Liao , Xin Yang , Xiangyun Hu

Journal of Earth Science ›› 2026, Vol. 37 ›› Issue (5) : 2228 -2243.

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Journal of Earth Science ›› 2026, Vol. 37 ›› Issue (5) :2228 -2243. DOI: 10.1007/s12583-025-0342-y
Energy Science
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Imaging the Geothermal System Using MT and CSEM Data in the Xinzhou Geothermal Field, Northern China
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Abstract

The Xinzhou geothermal field, situated within the Xinzhou Basin of northern China, represents a classic hydrothermal system with substantial development and utilization potential. To characterize the distribution of the geothermal system in this region, we deployed an integrated electromagnetic survey network comprising 98 Magnetotelluric (MT) stations and 226 Controlled-Source Electromagnetic (CSEM) stations. Through the application of three-dimensional MT inversion techniques and two-dimensional CSEM inversion methodologies, we constructed a comprehensive electrical conductivity model of the region, revealing the distinctive electrical characteristics of the deep subsurface structures. The crustal structure within the study area can be vertically subdivided into three primary stratigraphic units. The uppermost unit (C1), composed of Quaternary and Neogene sedimentary sequences, presents as a low-resistivity layer with thickness varying from 20 to 360 m. Within this layer, anomalous conductive zones associated with clay alteration zones have been identified. The intermediate unit, predominantly consisting of Archaean metamorphic rocks, manifests as a high-resistivity layer (R1), which contains three distinct low-resistivity anomalies (C2–C4). These anomalous bodies, characterized by resistivity values below 40 Ω·m, are interpreted as geothermal reservoirs located at depths ranging from 0.5–3 km. The basal unit comprises an extensive low-resistivity layer (C5), primarily situated at depths between 6–12 km. This layer is interpreted as an indirect heat source for the geothermal field, with estimated temperatures ranging from 195 to 420 °C. The formation of this heat source is likely attributed to crust-mantle thermal conduction processes. Distinct thermal conduits exist between the heat source and the geothermal reservoirs, characterized by relatively low resistivity features that are closely associated with concealed fault systems in the region. These conduits facilitate heat transfer within the system. This comprehensive investigation not only delineates the spatial distribution of the Xinzhou geothermal system but also provides crucial technical support for the sustainable development and utilization of geothermal resources in the region.

Keywords

MT & CSEM / electrical resistivity / geothermal systems / geothermal fields / Xinzhou Basin

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Meihua Wei, Yanxin Wang, Wenlong Zhou, Qinghai Guo, Weiyang Liao, Xin Yang, Xiangyun Hu. Imaging the Geothermal System Using MT and CSEM Data in the Xinzhou Geothermal Field, Northern China. Journal of Earth Science, 2026, 37 (5) : 2228-2243 DOI:10.1007/s12583-025-0342-y

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References

[1]

Abubakar A, Li M, Pan G, et al. Joint MT and CSEM Data Inversion Using a Multiplicative Cost Function Approach. Geophysics, 2011, 763F203F214.

[2]

Agemar T. Bottom Hole Temperature Correction Based on Empirical Correlation. Geothermics, 2022, 99: 102296.

[3]

Booker J R. The Magnetotelluric Phase Tensor: A Critical Review. Surveys in Geophysics, 2014, 351740.

[4]

Cagniard L. Basic Theory of the Magneto-Telluric Method of Geophysical Prospecting. Geophysics, 1953, 183605635.

[5]

Caldwell T G, Bibby H M, Brown C. The Magnetotelluric Phase Tensor. Geophysical Journal International, 2004, 1582457469.

[6]

Chen L. Lithospheric Structure Variations between the Eastern and Central North China Craton from S- and P-Receiver Function Migration. Physics of the Earth and Planetary Interiors, 2009, 1733/4216227.

[7]

Cherkose B A, Mizunaga H. Resistivity Imaging of Aluto-Langano Geothermal Field Using 3-D Magnetotelluric Inversion. Journal of African Earth Sciences, 2018, 139: 307-318.

[8]

Cherkose B A, Saibi H. Investigation of the Ayrobera Geothermal Field Using 3D Magnetotelluric Data Inversion, Afar Depression, NE Ethiopia. Geothermics, 2021, 94: 102114.

[9]

Cumming W. Geothermal Resource Conceptual Models Using Surface Exploration Data. Proceedings, Thirty-Fourth Workshop on Geothermal Reservoir Engineering Stanford University, February 9–11, 2009, 2009

[10]

Cumming W. Resource Conceptual Models of Volcano-Hosted Geothermal Reservoirs for Exploration Well Targeting and Resource Capacity Assessment: Construction, Pitfalls and Challenges. Geothermal Resources Council Transactions, 2016, 40: 623-637

[11]

Domra Kana J, Djongyang N, Raïdandi D, et al. A Review of Geophysical Methods for Geothermal Exploration. Renewable and Sustainable Energy Reviews, 2015, 44: 87-95.

[12]

Egbert G D, Kelbert A. Computational Recipes for Electromagnetic Inverse Problems: Computational Recipes for EM Inverse Problems. Geophysical Journal International, 2012, 1891251267.

[13]

Gao J, Zhang H J, Zhang S Q, et al. Three-Dimensional Magnetotelluric Imaging of the Geothermal System beneath the Gonghe Basin, Northeast Tibetan Plateau. Geothermics, 2018, 76: 15-25.

[14]

Glover P W J, Vine F J. Electrical Conductivity of the Continental Crust. Geophysical Research Letters, 1994, 212223572360.

[15]

Han D M, Liang X, Jin M G, et al. Evaluation of Groundwater Hydrochemical Characteristics and Mixing Behavior in the Daying and Qicun Geothermal Systems, Xinzhou Basin. Journal of Volcanology and Geothermal Research, 2010, 1891/292104.

[16]

Han Y, Bai X F, Zhang X. Discussion on Geothermal Resources and Its Exploitation and Utilization Model in Shanxi Province. Geological Survey of China, 2018, 551320

[17]

Hersir G P, Árnason K, Vilhjálmsson A M, et al. Krýsuvík High Temperature Geothermal Area in SW Iceland: Geological Setting and 3D Inversion of Magnetotelluric (MT) Resistivity Data. Journal of Volcanology and Geothermal Research, 2020, 391: 106500.

[18]

Jolie E, Scott S, Faulds J, et al. Geological Controls on Geothermal Resources for Power Generation. Nature Reviews Earth & Environment, 2021, 25324339.

[19]

Kelbert A, Meqbel N, Egbert G D, et al. ModEM: A Modular System for Inversion of Electromagnetic Geophysical Data. Computers & Geosciences, 2014, 66: 40-53.

[20]

Li Y L, Yang J C, Xia Z K, et al. Tectonic Geomorphology in the Shanxi Graben System, Northern China. Geomorphology, 1998, 2317789.

[21]

Liao W Y, Peng R H, Hu X Y, et al. 3-D Joint Inversion of MT and CSEM Data for Imaging a High-Temperature Geothermal System in Yanggao Region, Shanxi Province, China. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 1-13.

[22]

Lu C, Lin W J, Gan H N, et al. Occurrence Types and Genesis Models of Hot Dry Rock Resources in China. Environmental Earth Sciences, 2017, 7619646.

[23]

Manzella A. Geophysical Methods in Geothermal Exploration. Apuntes de Clases, 1973, Pisa: Italian National Research Council International Institute for Geothermal Research

[24]

Moeck I S. Catalog of Geothermal Play Types Based on Geologic Controls. Renewable and Sustainable Energy Reviews, 2014, 37: 867-882.

[25]

Mohan K, Kumar G P, Chaudhary P, et al. Magnetotelluric Investigations to Identify Geothermal Source Zone near Chabsar Hotwater Spring Site, Ahmedabad, Gujarat, Northwest India. Geothermics, 2017, 65: 198-209.

[26]

Peng R H, Zhou W L, Hu X Y, et al. 3D Inversion of Multifrequency Controlled-Source Electromagnetic Data and Its Application to Geothermal Exploration in the Tianzhen Region of the Northern Datong Basin, China. Geophysics, 2023, 886E173E187.

[27]

Rung-Arunwan T, Siripunvaraporn W, Utada H. Use of Ssq Rotational Invariant of Magnetotelluric Impedances for Estimating Informative Properties for Galvanic Distortion. Earth, Planets and Space, 2017, 69180.

[28]

Samrock F, Kuvshinov A, Bakker J, et al. 3-D Analysis and Interpretation of Magnetotelluric Data from the Aluto-Langano Geothermal Field, Ethiopia. Geophysical Journal International, 2015, 202319231948.

[29]

Santos P. Geothermal Well Target Approaches in the Exploration Stage. Short Course on Geothermal Drilling, Resource Development and Power Plants, January 16–22, 2011, 2011

[30]

Sasaki Y. 3D Inversion of Marine CSEM and MT Data: An Approach to Shallow-Water Problem. Geophysics, 2013, 781E59E65.

[31]

Schumacher S, Moeck I. A New Method for Correcting Temperature Log Profiles in Low-Enthalpy Plays. Geothermal Energy, 2020, 8127.

[32]

Shi W, Cen M, Chen L, et al. Evolution of the Late Cenozoic Tectonic Stress Regime in the Shanxi Rift, Central North China Plate Inferred from New Fault Kinematic Analysis. Journal of Asian Earth Sciences, 2015, 114: 54-72.

[33]

Spichak V, Manzella A. Electromagnetic Sounding of Geothermal Zones. Journal of Applied Geophysics, 2009, 684459478.

[34]

Ussher G, Harvey C, Johnstone R, et al. Understanding the Resistivities Observed in Geothermal Systems. Proceedings World Geothermal Congress, May 28–June 10, Tohoku, 2000

[35]

Uwiduhaye J D, Sakindi G, Saibi H, et al. Subsurface Geoelectrical Structure from 3-d Inversion of Magnetotelluric Data of Gisenyi Geothermal Field, Western Part of Rwanda. Journal of Applied Geophysics, 2021, 186: 104277.

[36]

Wang G L, Lin W J, Zhang W, et al. Research on Formation Mechanisms of Hot Dry Rock Resources in China. Acta Geologica Sinica (English Edition), 2016, 90414181433.

[37]

Wannamaker P E, Rose P E, Doerner W M, et al. Magnetotelluric Surveying and Monitoring at the Coso Geothermal Area, California, in Support of the Enhanced Geothermal Systems Concept: Survey Parameters and Initial Results. Proceedings of the Twenty-Ninth Workshop on Geothermal Reservoir Engineering, 2004, Stanford: Stanford University

[38]

Wu C F, Hu X Y, Wang G L, et al. Magnetotelluric Imaging of the Zhangzhou Basin Geothermal Zone, Southeastern China. Energies, 2018, 1182170.

[39]

Wu G J, Hu X Y, Huo G P, et al. Geophysical Exploration for Geothermal Resources: An Application of MT and CSAMT in Jiangxia, Wuhan, China. Journal of Earth Science, 2012, 235757767.

[40]

Xiao J Z, Zhang R F. Characteristics of Hydrogeochemistry of Geothermal Field of Qi Village, Shanxi, and Earthquake Monitoring. Earthquake Research in Shanxi, 2006, 1: 13-15

[41]

Xu S, Unsworth M J, Hu X Y, et al. Magnetotelluric Evidence for Asymmetric Simple Shear Extension and Lithospheric Thinning in South China. Journal of Geophysical Research: Solid Earth, 2019, 1241104124.

[42]

Xu X B, Zhao L, Wang K, et al. Indication from Finite-Frequency Tomography beneath the North China Craton: The Heterogeneity of Craton Destruction. Science China Earth Sciences, 2018, 61912381260.

[43]

Yuan D D, Liu Q, Xu H J, et al. High-Temperature Geothermal Source in the Northeastern Datong Basin, North China: Evidence from the Drilled Rhyolite. Journal of Earth Science, 2024, 35517761780.

[44]

Zhang M Z, Guo Q H, Liu M L, et al. Geochemical Characteristics and Formation Mechanisms of the Geothermal Waters in the Xinzhou Basin, Shanxi Province. Earth Science, 2022, 483973987(in Chinese with English Abstract)

[45]

Zhang S-M, Ren J J, Luo M H, et al. Stepwise Landforms and Quaternary Episodic Uplifts of Mountains around Xinding Basin. Seismology and Geology, 2008, 301187201

[46]

Zhou W L, Hu X Y, Guo H D, et al. Three-Dimensional Magnetotelluric Inversion Reveals the Typical Geothermal Structure of Yanggao Geothermal Field in Datong Basin, Northern China. Geothermics, 2022, 105: 102505.

[47]

Zhou W L, Hu X Y, Wei M H, et al. Geothermal Potential of the Southern Tianyang Basin, Northern China, Revealed by 3D Inversion of Magnetotelluric Data. Physics of the Earth and Planetary Interiors, 2025, 359: 107306.

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