Electrical Resistivity Model Research Articles

Micro–Macro-Analysis and Model Derivation of Electrical Resistivity of Ningxia Cement–Loess

In recent years, highway infrastructure in the Ningxia region of China has rapidly advanced. Cement–loess is extensively utilized in the roadbed and foundation reinforcement. It is necessary to conduct micro–macro-analysis and model derivation of the electrical resistivity on Ningxia cement–loess, which are beneficial for both the practical application of electrical resistivity and the evaluation of the geotechnical properties of cement–loess. Therefore, a series of electrical resistivity measurements, microstructural observations (scanning electron microscopy), mineral analyses (thermogravimetric analysis), and theoretical analyses were adopted on the cement–loess. The following conclusions can be drawn: The electrical resistivity is negatively related to dry density and water content, while it is positively related to cement dosage and curing age. A cement dosage of 6% exhibits a lower hydration reaction potential compared to 12%, causing a slower increase in electrical resistivity. The formation of calcium silicate gel around particles results in particle clustering and pore filling, reducing the pore area and increasing electrical resistivity. Increased hydration also decreases microscopic orientation, contributing to a higher electrical resistivity of cement–loess. Finally, a new three-dimensional electrical resistivity model was created, finding that the electrical resistivity of Ningxia cement–loess was determined by the dry density, water content (ρd·w), cement dosage, and curing age (aw·T) in an exponential function form. The new three-dimensional electrical resistivity model could be used in the high-efficiency evaluation of the cement–loess geotechnical parameter, offering valuable insights for the monitoring and maintenance of road infrastructure.

Three-dimensional interpretation of magnetotelluric data at Fogo Volcano, Azores Islands

The resistivity structure of Fogo volcano and the seismically active Congro region of São Miguel Island has been determined by 3-D inversion from 44 magnetotelluric soundings to yield new insights into the internal architecture of this volcanic island. Following comprehensive testing of processing codes to yield optimum magnetotelluric responses from the collected time-series, a robust electrical resistivity model was obtained. Sensitivity analysis of various features from the inversion process was used to determine their reliability, and aid geological interpretation. The magnetotelluric data imaged, and provided new structural insights into the Ribeira Grande geothermal system on the northern flank of Fogo volcano, where a shallow low resistivity (1 - 5Ωm) region has strong correlation with borehole data, and is shown to be an excellent proxy for mapping temperature and clay alteration mineralogy. Beneath the central edifice of Fogo volcano and also throughout the Congro region, the geology is very resistive, however the new magnetotelluric observations do not yield any further constraints on the origin of the seismicity that poses threats to the local populations residing on this hazardous island.

Geoelectric studies in earthquake hazard assessment: the case of the Kozlodui nuclear power plant, Bulgaria

AbstractThe study presents the results of geoelectric research for seismic risk assessment on the example of the Kozlodui nuclear power plant in Bulgaria. The image of the geoelectric structure in the study area was obtained using one-dimensional inverse electrical resistivity modeling of the full five-component magnetotelluric data and quasi-three-dimensional inverse conductivity modeling of the geomagnetic responses recorded during the summer 2021 field campaign. According to the presented results, the geoelectrically anomalous structure is divided into two levels. The near-surface anomalous structure in the immediate reach of human geotechnical activity corresponds to the electrically conductive sedimentary fill. The mid-crustal layer is coincident with the low seismic velocity zone at the brittle and ductile crust interface, revealed in previous studies. The presented results imply that the geological environment is not affected by large faults capable of transmitting seismic energy from tectonically active areas, however, in further studies, attention should be paid to the strike-slip fault systems adjacent to the study area.

Fuzzy c-mean (FCM) integration of geophysical data from an iron-oxide copper gold (IOCG) deposit under thick cover

Geophysical methods depend on a range of physical and chemical mechanisms, and each method has different sensitivities and resolution of Earth parameters, and over different scale lengths. Additionally, such geophysical methods will also have their own statistical characteristics. Thus, it is a significant challenge to combine different methods through a single inversion framework. Rather than attempting to find an optimal and single model for different geophysical responses, an alternative approach is to use FCM clustering to identify clusters of parameters from two or more different geophysical data sets or models that have similar statistical properties. In this paper, we apply the FCM approach to integrate data and model sets for an array of 100 broadband magnetotelluric (MT) and 100 passive seismic receivers spaced 1 km apart on a 10 by 10 grid above the Vulcan IOCG prospect in the Olympic Cu–Au Province, southern Australia. The challenge for exploration of the Vulcan prospect is that it lies beneath 750 m of regolith sedimentary cover, no single geophysical method provides a unique characterization of the deposit geometry, and drilling is very expensive. Fuzzy c-mean cluster analyses are undertaken in 2D for gravity data and shear-wave velocity model data for basement depths beneath cover and in 3D for shear-wave velocity and electrical resistivity model data. Fuzzy c-mean clustering is shown to provide a simple and efficient method of integrating different geophysical measurements to produce a geological framework that can be verified with drilling information.

The structure of a continental intraplate volcanic system and controls from shear zones: Insights into the central Hoggar Cenozoic volcanic province, Northwest Africa, from electrical resistivity images

Continental intraplate volcanic systems, with their locations far from plate tectonic boundaries, are not well understood: the crustal and lithospheric mantle structure of these systems remain enigmatic and there is no consensus on the mechanisms that cause melt generation and ascent. The Cenozoic saw the development of numerous volcanic provinces on the African plate, including within the Central Hoggar, located in Northwest Africa, part of the Tuareg shield. The magmatic activity began at approximately 34 Ma and continued throughout the Quaternary. In order to understand the origins and potential mechanisms that generated the intraplate volcanic activity in the Central Hoggar we aim to image the subsurface architecture, in terms of electrical resistivity, from the surface to the lithospheric mantle. To do so we use magnetotelluric measurements from 40 locations to generate a 3-D electrical resistivity model, over an area of about 100 km by 160 km. Low-resistivity features (i.e., conductors) are observed in the crust that are narrow, linear structures congruent with the boundaries of terranes and prominent fault zones (e.g., Azrou N’Fad). They likely reflect the Pan-African mega-shear zones, which were reactivated throughout the tectonic evolution of the region. The model reveals that these faults are lithospheric-scale. The low-resistivity features likely represent the signatures of past fluid pathways and mineralization. A deeper low-resistivity feature is observed in the upper lithospheric mantle directly beneath the Manzaz and Atakor volcanic districts. It may represent local, small-scale metasomatism of the sub-continental lithospheric mantle, and low-percent partial melting, that sits above a regional, large-scale asthenospheric upwelling associated with the Hoggar swell. It is likely the origin point of the fluids responsible for the overlying anomalies. The results highlight the control of the lithospheric-scale, mega-shear zones on the spatial distribution of the recent Cenozoic volcanic activity, which was influenced by the location of pre-existing structural weaknesses.

Mantle plume trail beneath the ca. 1.1 Ga North American Midcontinent Rift revealed by magnetotelluric data.

Whilst the 1.1 Ga North American Midcontinent Rift (MCR) system is formed in association with the Keweenaw mantle plume, the absence of a northern third rift arm or aulacogen (a general characteristic of mantle plumes) has previously not been well understood. To help clarify this unusual plume-rift relationship and to better establish the region affected by the Keweenaw mantle plume, we present the first electrical resistivity model of the MCR derived from 3D inversion of EarthScope USArray and Lithoprobe magnetotelluric (MT) data, extending northwards into the Archean Superior Province. Our model shows a prominent highly conductive anomaly trending NW-SE at the base of Western Superior's cratonic lithospheric mantle, cross-cutting and extending for over 300km on both sides of the western rift branch. We propose that this anomaly reflects the ancient signature of a plume trail, resulting from metasomatism and/or partial melting of the sulfide-rich basal lithospheric mantle during impingement of the Keweenaw mantle plume.

Machine learning enables electrical resistivity modeling of printed lines in aerosol jet 3D printing

Among various non-contact direct ink writing techniques, aerosol jet printing (AJP) stands out due to its distinct advantages, including a more adaptable working distance (2–5 mm) and higher resolution (~ 10 μm). These characteristics make AJP a promising technology for the precise customization of intricate electrical functional devices. However, complex interactions among the machine, process, and materials result in low controllability over the electrical performance of printed lines. This significantly affects the functionality of printed components, thereby limiting the broad applications of AJP. Therefore, a systematic machine learning approach that integrates experimental design, geometrical features extraction, and non-parametric modeling is proposed to achieve printing quality optimization and electrical resistivity prediction for the printed lines in AJP. Specifically, three classical convolutional neural networks (CNNs) architectures are compared for extracting representative features of printed lines, and an optimal operating window is identified to effectively discriminate better line morphology from inferior printed line patterns within the design space. Subsequently, three representative non-parametric machine learning techniques are employed for resistivity modeling. Following that, the modeling performances of the adopted machine learning methods were systematically compared based on four conventional evaluation metrics. Together, these aspects contribute to optimizing the printed line morphology, while simultaneously identifying the optimal resistivity model for accurate predictions in AJP.

A Review of Relationship between the Metallogenic System of Metallic Mineral Deposits and Lithospheric Electrical Structure: Insight from Magnetotelluric Imaging

In development over 70 years, magnetotelluric (MT) sounding, a high-resolution technique for subsurface electrical resistivity imaging, has been widely applied in resource exploration in the Earth. The key factors of the metallogenic system of metallic mineral deposits can be closely correlated to the electrical anomalies of the lithosphere. In this paper, we review the relationship between the electrical resistivity model of the lithosphere and the metallogenic system. At the beginning, we indicate why the electrical parameters relate to the metallogenic system in all geophysical parameters. The advantage of MT sounding in sketching an electrical resistivity model of the lithosphere is subsequently discussed, and some methods of data processing, analysis and inversion are also introduced. Furthermore, we summarize how to bridge the relationship between the electrical resistivity model of the lithosphere and metallogenic system, and analyze the influence of the rheological variation estimated from conductivity in the lithosphere on mineralization. In the end, we list some typical cases of the application of MT sounding in mineral exploration, and also give some suggestions for future work. This study is aimed at providing guidance in discussing the metallogenic system using an electrical resistivity model.

Lithospheric electrical structure of the Alxa Block, NW China, southern central Asian Orogenic Belt, revealed by 2D inversion of magnetotelluric data

The Alxa Block, situated between the Tarim and North China cratons, is essential to understand the tectonics of northwest China. It has undergone several tectonic cycles, including rifting from northern Gondwana in Neoproterozoic, subduction-accretion of the Paleo-Asian Ocean during Paleozoic, and intracontinental deformation in Mesozoic. Broadband magnetotelluric data covering a frequency range of 320 Hz to ∼ 10000 s was collected along two NW-SE trending lines across major tectonic units of the Alxa region to investigate the deep structures of the Alxa Block. By applying the nonlinear conjugate gradient (NLCG) inversion approach, two-dimensional (2D) electrical resistivity models were obtained at a 100 km depth. These findings indicate that the Zhusileng-Hangwula and Zongnaishan-Shalazhashan tectonic zones have high resistivity in their lower crust and upper mantle, with an overall layered high-low–high resistivity pattern. The upper crust of the Nuru-Langshan tectonic zone is primarily characterized by high resistivity values, whereas the lower crust and upper mantle contain a large-scale low-resistivity (or conductive) zone that is likely the result of partial melting. The large-scale Early–Middle Jurassic nappe structures may be connected to sub-horizontal low-resistivity anomalies in the shallow strata, which are located up to 20 km below the Yagan and Zhusileng–Hangwula tectonic zones. Below the Engger Us fault, two low-resistivity bands are interpreted as the product of bidirectional subduction and final closure of the Paleo-Asian Ocean. The Alxa Block may have subducted southwards beneath the Ordos Block, as suggested by a clear low-resistivity anomaly between the two blocks. Furthermore, partial melting may have happened for high-conductivity bodies in the upper mantle based on the modified Archie formula’s evaluation of their melting degree.

Monitoring the crack lengths in composite lap joints under cyclic loading

Abstract Monitoring crack lengths in composites lap joints is crucial for the evaluation of safety and integrity in composite structures. The crack lengths in adhesively bonded single-lap and double-strap joints were characterized by using epoxy adhesive containing aligned graphene. The epoxy adhesive was prepared by adding graphene to epoxy resin and then aligning the graphene through an electrical field. The incorporation of 0.15wt% aligned graphene can have the epoxy adhesive being electrically conductive. The single-lap and double-strap joints containing the graphene epoxy adhesive were tested under cyclic loading. During the cyclic tests, the crack extension and electrical resistance were measured concurrently. In addition, the electrical resistance model expressed in terms of the crack lengths for the lap joints was proposed in the examination. The results illustrated that the crack length and the electrical resistance increased as the cyclic number increased. Moreover, the experimental resistance variation associated with the increased crack length can be described using the electrical resistance model. Thus, the functionalized epoxy adhesive containing aligned graphene can be employed for effectively detecting the length of cracks in composite lap joints under cyclic loading.

A new conceptual model of the Travale (Italy) enhanced geothermal system: Insights from electromagnetic geothermometry

The paper presents an electromagnetic geothermometer-based two-dimensional temperature model for the Travale (Italy) enhanced geothermal system derived from magnetotelluric and temperature data. Joint analysis of the temperature and electrical resistivity models made feasible a new self-consistent conceptual model of this site, which agrees with available geological data and previous geophysical results. It explains the nature of seismic reflection horizons detected in 1978 and unusual seismicity distribution in depth which could not be properly addressed earlier without temperature predicting beyond boreholes. It is concluded that the heat source feeding this system may be a granitic intrusion located at a depth below 4 km, which corresponds to the isotherm of 600 °C. A sharp temperature gradient above this intrusion forms a contact thermo-metamorphic halo in the depth range of 3–4 km. Assessment of the released fluid volume fraction from the electrical resistivity model indicates that the general amount of thermo-metamorphic and magmatic fluids in the rock-dominated Travale geothermal system is negligible. It is concluded that meteoric waters are the main source of fluids penetrating along normal faults up to 3 km. Despite some supercritical fluids of thermo-metamorphic origin could circulate in the system below this depth, their amount is hardly sufficient for economically justified exploration drilling. The results of the study indicate that building the temperature model of the geothermal area is crucially important for the exploration of enhanced geothermal systems.

A novel machine learning approach for interpolating seismic velocity and electrical resistivity models for early-stage soil-rock assessment

A novel machine learning approach for interpolating seismic velocity and electrical resistivity models for early-stage soil-rock assessment

Resistivity and chloride diffusion coefficient of cement-based materials characterized by non-contact electrical resistivity method and resistivity model

The present study involves the application of the non-contact electrical resistivity measurement (NC-ERM) as a non-destructive method to continuously and in-situ measure the resistivity changes of cement-based materials. The NC-ERM was enhanced and utilized to evaluate the resistivity of the materials, and the steady-state chloride diffusion coefficients of various types of cement-based materials were experimentally determined. The results revealed that the highest resistivity was observed in mortar with a sand-to-cement ratio of 1.0 and concrete with an aggregate-to-cement ratio of 0.6, and the steady-state chloride diffusion coefficient increased with the concentration of the pore solution. Furthermore, a novel multi-level series-parallel model was developed to predict the resistivity and steady-state chloride diffusion coefficient of cement-based materials, with calculated values differing by 5% or less. The calculated chloride diffusion coefficient closely matched the value obtained from NC-ERM, indicating the satisfactory accuracy of the non-destructive experiment and theoretical calculation model.

Monitoring of Älvkarleby test embankment dam using 3D electrical resistivity tomography for detection of internal defects

Electrical resistivity tomography (ERT) is a potential-based method for detecting internal erosion in the core of embankment dams using the electrodes installed outside. This study aims at evaluating the practical capability of ERT monitoring for detecting internal defects in embankment dams. A test embankment dam with in-built well-defined defects was built in Älvkarleby, Sweden, to assess different monitoring systems including ERT and the defect locations were unknown to the monitoring teams. Between 7500 and 14,000 ERT data points were acquired daily, which were used to create the distribution of electrical resistivity models of the dam using 3D time-lapse inversion. The inversion models revealed a layered resistivity structure in the core that might be related to variations in water content or unintentional variations in material properties. Several anomalous zones that were not associated with the defects were detected, which might be caused by unintentional variations in material properties, temperature, water content, or other installations. The results located two out of five defects in the core, horizontal and vertical crushed rock zones, with a slight location shift for the horizontal zone. The concrete block defect in the core was indicated, although not as distinctly and with a lateral shift. The two remaining defects in the core, a crushed rock zone at the abutment and a wooden block and a crushed rock zone in the filter, were not discovered. The results cannot be used to fully evaluate the capability of ERT in detecting internal erosion under typical Swedish conditions due to limited seepage associated with the defects. Furthermore, scale effects need to be considered for larger dams.

Characterization of subsurface geology and hydrogeology in Kribi -Cameroon using electrical resistivity soundings and 3D-Implicit modelling: Baseline for groundwater resource management

This scientific article aims to characterize the geology and hydrogeology of Kribi, Cameroon for the purposes of water resources management, infrastructure development, and environmental protection. The specific objectives include mapping the subsurface electrical resistivity structure, identifying groundwater potential zones, and constructing a hydrogeological model for groundwater modelling. The study employed the Schlumberger method to map the electrical resistivity structure of the 3D subsurface and utilized 3D implicit modelling techniques to delineate groundwater potential zones. The study revealed that Kribi exhibits a highly complex geology, characterized by three-layered electrical resistivity models, typical of sedimentary and metamorphic formations. The major lithologies identified include laterite, clay, sand, quartz, and granite. The region encompasses areas with low water potential and brackish zones alongside high groundwater production areas. The study established the presence of aquifers within Kribi, with the unconfined aquifer found at depths ranging from 2 m to 13 m, and the confined aquifer extending from 14 m to 40 m. The aquifers are notably thick and productive, indicating substantial groundwater resources. Static groundwater volumes were estimated at 50,179,381 m3 and 317,118,946 m3 for the unconfined and confined aquifers respectively. Despite this potential, water resources management in the area is non-existent. The study recommends the implementation of Integrated Water Resources Management (IWRM) to improve water resource management, with a primary focus on groundwater modelling. The northern and southern regions of Kribi exhibit high permeability, which is advantageous for groundwater recharge and storage projects but also poses challenges for environmental remediation efforts. Consequently, safeguarding the delineated area for groundwater provision is of utmost importance.

Predicting the properties of concrete incorporating graphene nano platelets by experimental and machine learning approaches

Modern infrastructure requirements necessitate structural components with improved durability and strength properties. The incorporation of nanomaterials (NMs) into concrete emerges as a viable strategy to enhance both the durability and strength of the concrete. Nevertheless, the complexities inherent in these nanoscale cementitious composites are notably intricate. Traditional regression models face constraints in comprehensively capturing these intricate compositions. Thus, posing challenges in delivering precise and dependable estimations. Therefore, the current study utilized three machine learning (ML) methods, including artificial neural network (ANN), gene expression programming (GEP), and adaptive neuro-fuzzy inference system (ANFIS), in conjunction with experimental investigation to study the effect of the integration of graphene nanoplatelets (GNPs) on the electrical resistivity (ER) and compressive strength (CS) of concrete containing GNPs. Concrete containing GNPs demonstrated an improved fractional change in resistivity (FCR) and strength. The experimental measures depict that strength enhancement was notable at GNP concentrations of 0.05% and 0.1%, showcasing increases of 13.23% and 16.58%, respectively. Simultaneously, the highest observed FCR change reached −12.19% and −13%, respectively. The prediction efficacy of the three models proved to be outstanding in forecasting the characteristics of concrete containing GNPs. For CS, the GEP, ANN, and ANFIS models demonstrated impressive correlation coefficient (R) values of 0.974, 0.963, and 0.954, respectively. For electrical resistivity, the GEP, ANN, and ANFIS models exhibited high R-values of 0.999, 0.995, and 0.987, respectively. The comparative analysis of the models revealed that the GEP model delivered precise predictions for both ER and CS. The mean absolute error (MAE) of the GEP-CS model demonstrated a 14.51% reduction compared to the ANN-CS model and a substantial 48.15% improvement over the ANFIS-CS model. Similarly, the ANN-CS model displayed an MAE that was 38.14% lower compared to the ANFIS-CS model. Moreover, the MAE of the GEP-ER model demonstrated a 56.80% reduction compared to the ANN-CS model and a substantial 82.47% improvement over the ANFIS-CS model. The Shapley Additive explanation (SHAP) analysis provided that curing age exhibited the highest SHAP score. Thus, indicating its predominant contribution to CS prediction. In predicting ER, the graphene content exhibited the highest SHAP score, signifying its predominant contribution to ER estimation. This study highlights ML's accuracy in predicting the properties of concrete with graphene nanoplatelets, offering a fast and cost-effective alternative to time-consuming experiments.

Two-dimensional magnetotelluric inversion using unstructured triangular mesh implemented in Julia

This study presents a 2-D magnetotelluric inversion code tailored for unstructured triangular meshes, developed using Julia, a high-level, high-performance programming language designed for scientific and numerical computation. The forward modeling engine utilizes a node-based finite element method to solve electromagnetic fields throughout the modeling domain. The inversion process employs the Gauss-Newton optimization algorithm, iteratively updating the model via the minimization of a regularized least-squares objective function. We verified the accuracy of the forward modeling using two reference models and performed a synthetic inversion experiment to validate our inversion method and stress the necessity of accurately handling topography-influenced data. Through its application to constructing an electrical resistivity model beneath the northwestern end of Sumatra Island, Indonesia, we demonstrate the practicality of our code for inverting field datasets.

Magnetotelluric Imaging of the Central Himalayan Crust Away From Rift Zones

AbstractImaging the crustal structure and state of the Himalayan Orogenic Belt (HOB) is of great significance for understanding crustal deformation and its tectonic response in the collision front of the Indian‐Eurasian plates. To avoid the influence from the anomalies underneath the north‐south trending rifts, a three‐dimensional electrical resistivity model across the central HOB was obtained between the Dingjie‐Shenzha and Yadong‐Gulu rifts. No lower‐crustal conductor was found in the southern Lhasa Terrane, and the lower crust with a moderate resistivity value of approximately 100 Ωm is interpreted to be the residue of previous partial melting beneath the Gangdese porphyry copper deposits. The middle crust between the Main Himalayan Thrust and Southern Tibet Detachment System is electrically resistive to the north of the north Himalayan gneiss domes (NHGD) belt and conductive to the south. The middle crust in the northern Himalayas may have undergone partial melting and crystallization during southward migration and duplexing. There is a strong deep‐shallow coupling relationship in the central HOB, where an increase in the underthrusting angle of the Indian crust has resulted in a southward turn of the NHGD belt.

Understanding the behaviour of seismically derived Poisson's ratio in near-surface characterization

Near-surface characterization is often challenging using a single geophysical technique. We show that seismic refraction is an effective tool by combining P- and S-wave velocity models in the form of V P / V S and Poisson's ratio ( σ ) to detect buried targets along with electrical resistivity imaging (ERI). We acquired vertical and horizontal component seismic data along a 2D profile over two known targets. The first is a water pipe of c . 0.8 m diameter located c . 1.5 m below the surface and the second is a storm drainage pipe (SDP) of c . 1 m diameter at c . 2 m depth. The first arrival times of vertical and horizontal component data were picked and inverted using grid-based tomography. The resulting velocity models have smoothly varying structures and could not identify any of the target features. However, when combined as V P / V S and Poisson's ratio models, the features clearly appeared as anomalous zones. A collocated 2D electrical resistivity model shows the presence of anomalies around the same locations. Our study suggests that anomalous V P / V S and Poisson's ratio values derived from seismic velocities are indicative of the relative changes owing to the disturbances in the soil because of construction with respect to the background instead of the anomaly.

Evidence for partial melting and earthquake activity in the crust from a 2-D electrical resistivity model in the vicinity of the Chayu region, southeastern Jiali-Chayu fault, Tibetan Plateau

The southeastern segment of the Jiali-Chayu fault is a prominent strike-slip fault that separates the eastern Lhasa terrane. Its formation and activity are influenced by the subduction of the Indian plate towards the Lhasa terrane and clockwise rotation in the Himalayan Eastern syntaxis region. Notably, the Chayu 1950 Ms 8.6 earthquake, triggered by this fault, remains the largest recorded inland earthquake to date. However, due to a lack of high-precision geophysical evidence, the deep crustal structure of the hypocenter area remains challenging to reconstruct, limiting our understanding of earthquake activity in the region. In this paper, the Magnetotelluric data is consisted of 70 sites spaced 2 km apart. Through a joint inversion of the transverse electric and magnetic modes, we recovered the 2-D resistivity model that is approximately 140 km long and 50 km deep. The resistivity model provides compelling evidence that the presence of magmatic rocks and metamorphic basement is responsible for the high resistivity anomaly. Conversely, the low resistivity anomaly observed in the northern region can be attributed to crustal melting. These results suggest that the variation in earthquake activity between the Gongrigabu fault and Guyu fault can be attributed to the contrasting characteristics of the crustal material. The Gongrigabu fault represents a brittle plate with low water content and high crystallinity, resulting in a distinctive high resistivity anomaly. On the other hand, the Guyu fault corresponds to a molten plate, exhibiting a low resistivity anomaly. We believe that the Chayu earthquake is a typical intraplate earthquake in the Lhasa terrane and its seismogenic fault is a deeper hidden fault located below the Gongrigab fault, challenging the belief held by other scholars that the Gongrigabu fault is solely responsible. We think the Gongrigabu fault is a high-risk zone for severe earthquakes that demands continuous vigilance in the future.