Audio-magnetotelluric Data Research Articles

Audio magnetotelluric view of the giant carbonatite-hosted Bayan Obo REE deposit, Inner Mongolia, northern China

As critical minerals in low-carbon economies, rare-earth elements (REEs) are crucial for modern industry, technology, and medicine. The largest known REE resource in the world is the Bayan Obo (BO) deposit in northern China. However, BO features as complicated mineral compositions and has experienced several geological events. As a reuslt, controversy remains about the BO REE genesis and enrichment mechanism, and debates are also ongoing about the controlling structure of this giant deposit. We carried out an multiscale electromagnetism study on BO mineral deposits. The multiscale study consists a microscale on samples, a small scale targeting mineral deposits and a mid scale concerning the mine field. The small and mid scale study were conducted using audio-magnetotelluric (AMT). This study revealed the controlling structure using geoelectrical characteristics. AMT data were acquired from more than 590 stations, and the petro-electromagnetism of several samples was analyzed to understand the geoelectrical features of the ore deposits and their surrounding rocks. The data were interpreted using Bostick transformation and generalized least-squares inversions. We obtained the geoelectrical structure of the BO complex down to a maximum depth of 3500 m, and we present two-dimensional imaging based on the AMT conversion results. The results show that the BO deposit developed at the transition of the high- and low-resistivity geoelectrical structure from south to north. Our AMT results indicate that the tectonic setting of the BO deposit is the transition zone between the rift edge and craton margin slope. The ore geology is presently controlled by the complex slope and the rift remnant, the ore-bearing dolostone in the profiles is Y-shaped. It goes downward from south to north and potentially features a great mineral prospect deep in the BO deposit.

Intelligent geological interpretation of AMT data based on machine learning

AMT (Audio Magnetotelluric) is widely used for obtaining geological settings related to sandstone-type Uranium deposits, such as the range of buried sand body and the top boundary of baserock. However, these geological settings are hard to interpret via survey sections without conducting geological interpretation, which highly relies on experience and cognition. On the other hand, with the development of 3D technology, artificial geological interpretation shows low efficiency and reliability. In this paper, a machine learning model constructed using U-net was used for the geological interpretation of AMT data in the Naren-Yihegaole area. To train the model, a training dataset was built based on simulated data from random models. The issue of insufficient data samples has been addressed. In the prediction stage, sand bodies and baserock were delineated from the inversion resistivity images. The comparison between two interpretations, one by machine learning method, showed high consistency with the artificial one, but with better time-saving. It indicates that this technology is more individualized and effective than the traditional way.

Deep resistivity geophysics of the San Juan–Silverton caldera complex, San Juan County, Colorado (USA)

Magnetotelluric (MT) and audiomagnetotelluric (AMT) data are used to better understand the subsurface geology and mineral resources in the San Juan–Silverton caldera complex located near Silverton, Colorado, western United States, as part of the extensive southern Rocky Mountains volcanic field that covers much of southwestern Colorado and northern New Mexico. Seven MT and AMT profiles of varying lengths image resistivity structure to depths of ~5 km. The AMT inversion models characterize geophysical responses of near-surface lithologies, structures, and mineralized systems and also help corroborate airborne electromagnetic data at shallow levels. The MT inversion models extend our depth of investigation from near the surface to great depths (~5 km) and help to form hypotheses about roots of the hydrothermal plumbing that fed shallower mineralized systems. Subsurface high resistivities occur beneath intermediate-composition lava flows and Proterozoic units. Subsurface moderate- to low-resistivity values may reflect hydrothermal plumbing that served as flow paths for mineralizing fluids and metallic ore formation. The model interpreta­tions presented in this study could be utilized in remediation planning or mineral resource applications. The methods used could be applied to other watersheds with similar volcanic environments containing acid-generating historical mines or hydrothermally altered and mineralized source rocks.

Imaging freshwater and saline aquifers beneath Bradford County, Pennsylvania, USA, using Audio-Magnetotelluric (AMT) data

We investigate the utility of audio-magnetotelluric (AMT) data for detecting high electrical conductivity zones indicative of fresh and saline groundwater lenses at depths of < ∼1000 m at seven survey sites in the southwestern corner of Bradford County, PA. Dimensionality analysis indicates the AMT data can be interpreted using two-dimensional (2-D) models. 2-D electrical resistivity models obtained from inverting the AMT data reveal conductive zones at depths of <30 m at all sites, between depths of 50–150 m at six sites, and between depths of 400–600 m at one site. The models show slightly lower resistivities (∼15–30 Ω m) in the deeper zones compared to the shallower zones (>30 Ω m). Consistent with well log data from two boreholes in the study area and salinity estimates obtained from the imaged resistivities, we interpret the <30 m deep conductive zone as the freshwater aquifer, and the two deeper conductive zones as salty/briny groundwater lenses. Our salinity estimates for the deeper zones vary from 1 to 380 (unitless Practical Salinity Scale), which agrees well with previous estimates of Appalachian brine salinity of 10–343. We attribute the high-salinity groundwater lenses to Appalachian Basin brine migrating upwards from deeper in the basin via bedrock fracture and fault systems. Our findings indicate AMT surveying can be useful for imaging fresh and saline aquifers at shallow depths (< ∼1000 m), at least within the northeastern section of the Appalachian Basin in Pennsylvania.

Audio‐Magnetotelluric Survey for Groundwater Investigation in the Al‐Jaww Plain in Eastern Abu Dhabi, Al‐Ain, United Arab Emirates

AbstractThe United Arab Emirates (UAE), located in an arid climate zone with low rainfall, relies on shallow aquifers for freshwater. Understanding the depth and extent of such aquifers is crucial for meeting water supply needs. The UAE's hydrogeology is influenced by neighboring mountains in Oman. The Al‐Jaww Plain in southeast of Al‐Ain city is an essential groundwater source, characterized by a large, flat area of gravel and sand deposits from the Oman Mountains. This study aims to map groundwater aquifers in the Al‐Jaww Plain by integrating the audio‐magnetotelluric (AMT) method, seismic reflection profiling, and borehole data. AMT data were collected along an 11‐km ENE–WSW profile and a 2D resistivity model was generated. The resulting model delineates three distinct geo‐electrical zones from the surface to a depth of 5 km. First, a shallow layer with low resistivity (0–15 Ωm) represents the Quaternary and Pliocene aquifers, in addition to the Upper Cretaceous Simsima and Tertiary groundwater aquifer zone, extending to a depth of 1.5 km. Second, a moderately resistive layer (15–250 Ωm) is recorded beneath the first layer, corresponding to the Upper Cretaceous Aruma foreland basin sequence. Finally, a high‐resistivity region (&gt;250 Ωm) at depths exceeding 3 km is attributed to the allochthonous Hawasina thrust sheet, which is associated with Late Cretaceous obduction of the Semail ophiolite. These findings have practical implications for managing groundwater resources in Al‐Ain.

Magnetotelluric Time Series Denoising Using Encoder-Decoder Consisted of LSTM Cells

Electromagnetic signals in geophysics are frequently disturbed by various interference in field data acquisition. Denoising for passive electromagnetic methods such as magnetotelluric (MT) or audio magnetotelluric (AMT) data is significant to improve data quality and finally imaging to the geoelectrical structure. Conventionally, most denoising methods are employed in frequency domain and few of them are applied in time domain. However, a great number of irregular noise in the electromagnetic time series prove difficulty to be removed. We propose a denoising method, using Encoder-Decoder consisted of Long Short-Term Memory cells (ED-LSTM), to reduce the effect of the step noise and the random-impulsive noise. Supervised learning and transductive learning are used for the denoising of the step noise and the random-impulsive noise, respectively. Our results indicate that the step and random-impulsive noise could be successfully removed from the raw time series. The result indicate that ED-LSTM could potentially to be wildly used in the electromagnetic time series denoising and then improve data quality.

One-dimensional magnetotelluric parallel inversion using a ResNet1D-8 residual neural network

Deep Learning is an effective tool to invert the underground electrical conductivity structure. In this study, we build a new 8-layer residual neural network (ResNet1D-8) for audio magnetotelluric (AMT) data inversion based on the deep learning theory. In terms of the network structure, the degradation of the model with the increase of depth is effectively avoided by adding shortcut connections. Meanwhile, adding a batch normalization layer greatly improves the model training speed and network generalization ability. This study uses the parallel technology to quickly generate millions of samples, which effectively reduces the computational time and provides a large number of high-quality samples for deep learning model training. Compared with the simulated annealing algorithm, the neural network model in this paper has the advantages of high reliability, short inversion time, and strong model generalization ability. Moreover, we add Gaussian noise to the data of testing samples, and inversion results show that the model has good robustness. The inversion test is carried out on the field measured AMT data set collected in the Dachaidan area of Qinghai Province, China. The results show that the ResNet1D-8 residual neural network model established in this paper can effectively invert the underground electrical structure.

Deep-learning-based sferics recognition for audio magnetotelluric data processing in the dead band

In audio magnetotelluric (AMT) sounding data processing, the absence of sferic signals in some time ranges results in a lack of energy in the AMT dead band, causing unreliable resistivity estimations. To address this issue, we develop a deep convolutional neural network (CNN) to automatically recognize sferic signals from redundantly recorded data over a long time range and use these sferic signals to accurately estimate resistivity. The CNN is trained using field time-series data with different signal-to-noise ratios (S/Ns) acquired from different regions of mainland China. To solve the potential overfitting due to the limited number of sferic labels, we develop a training strategy that randomly generates training samples with random data augmentations while optimizing the CNN model parameters. The training process and data generation are stopped when the training loss converges. In addition, we use a weighted binary cross-entropy loss function to solve the sample imbalance problem to optimize the network better, use multiple reasonable metrics to evaluate the network performance, and perform ablation experiments to optimize the model hyperparameters. Extensive field data applications indicate that our trained CNN can robustly recognize sferic signals from noisy time series for subsequent impedance estimation. The results indicate that our method can significantly improve the S/Ns and effectively solve the lack of energy in the dead band. Compared with the traditional processing method, our method can generate smoother and more reasonable apparent resistivity-phase curves and depolarized phase tensors, correct the estimation error of the sudden drop in high-frequency apparent resistivity and abnormal behavior of phase reversal, and better estimate the real shallow resistivity structure.

Two-dimensional interpretation of audio-magnetotelluric data around the epicenter distribution of the 2016 Gyeongju earthquake (ML 5.8), Korea

Two-dimensional interpretation of audio-magnetotelluric data around the epicenter distribution of the 2016 Gyeongju earthquake (ML 5.8), Korea

Analysis of Fluid Flow Pathways in the Mount Meager Volcanic Complex, Southwestern Canada, Utilizing AMT and Petrophysical Data

AbstractDefining the spatial distribution of geological structures and rock properties is important for understanding how fluid flow is controlled in a geothermal reservoir. Here, we present a procedure to examine the potential fluid pathways. By combining 3‐D resistivity models derived from audio‐magnetotelluric (AMT) data with available rock properties (porosity and permeability) and fluid sample data (fluid resistivity, salinity, and temperature), we investigated the relationship between electrical resistivity and fluid flow in an active volcanic system. Different petrophysical models and empirical relations are evaluated to determine the relationship between the fluid flow system at Mount Meager, British Columbia, and the resistivity model. In addition, we utilized porosity and permeability measured in the laboratory to define the porosity‐permeability relationship. The porosity of the volcanic core samples showed a range of 2.6%–23.2% and the permeability was in a range of 0.001–5,186.57 mD. The results showed the potential of 3‐D inversion of AMT data to map the fluid pathways at Mount Meager. These pathways are correlated with loss circulation zones in boreholes and can account for porosity up to 8.5%, which using the porosity‐permeability relationship translates to permeability of the order 0.249 mD. Not only are the fault and fracture zones important for reservoir exploitation, but they also provide permeability for the circulation of meteoric water. Our studies suggest that a set of fractures with 0.1 m spacing and 20 mm aperture can keep 40% fluid in pores and transmit fluid with possible permeability of 666 mD.

Genetic relationship between granite and pegmatite in the Kaluan lithium deposit, Western China: evidence from the inversion of audio-magnetotelluric data

Genetic relationship between granite and pegmatite in the Kaluan lithium deposit, Western China: evidence from the inversion of audio-magnetotelluric data

Constrained 2D inversion of radio-magnetotelluric and controlled-source audio-magnetotelluric data using high-resolution reflection seismic data: An example in groundwater surveying from Heby, Sweden

We advance a previously established method for 2D inversion of electromagnetic data, in which the smoothness constraints are locally reweighted according to the seismic envelope fractional gradients (SEFGs). As the first step of our modifications, seismic envelope values are edited and normalized. This results in the rejection of noise-contaminated parts, clipping the envelope outliers and increasing the reflectivity power of weak seismic signals. Second, we introduce a weighting matrix in the normalization process to incorporate prior information in the constrained inversion regarding the relative contrasts of electrical resistivity in the given parts of the model. Third, due to normalizing the SEFG, there is no need to search for an optimum stabilization factor to modify local smoothing weights, and hence, we set it to a constant value. Finally, an Occam inversion with additional Levenberg-Marquardt damping is used to mitigate possible artifacts in the resistivity model generated by reflection seismic constraints. In applying the proposed scheme to a synthetic example, interfaces of various geologic units are restored as sharp boundaries. In addition, artifacts generated in the original approach are effectively mitigated thanks to the applied normalization process. For the first time, we apply the method to radio-magnetotelluric (RMT) and controlled-source audio-magnetotelluric (CSAMT) field data acquired along a profile across a known aquifer in Heby, Sweden. Our inversion models compare favorably to previously presented results from seismic and geoelectric data. By modifying the smoothness weights based on SEFG, the depth to the bedrock is recovered well, being constrained by the corresponding interfaces in the seismic image. The resistivity models from seismically constrained inversions of RMT and CSAMT data reveal steeply dipping and possibly fractured bedrock underneath the valley-shaped aquifer in the area. This interpretation is verified by borehole logs.

Three-dimensional audio magnetotelluric imaging of the Yangyi geothermal field in Tibet, China

The Yangyi geothermal field in southern Tibet has enormous potential for geothermal energy development. It is the high-temperature geothermal field at the highest elevation in the world, and the second largest high-temperature geothermal field in China. The total planned installed capacity of the geothermal power station is 32 MW. At present, no detailed three-dimensional (3D) geophysical survey has been carried out in the Yangyi geothermal field, and in-depth research is urgently needed. The main goal of our geophysical exploration is to study the geothermal structure of this region. In this study, the audio magnetotelluric (AMT) data of 85 stations were collected in the Yangyi geothermal field. The average distance between the stations was about 500 m, and the dimensions of the exploration area were 6 × 7 km. First, we analyzed the magnetotelluric data using the phase tensor method to qualitatively estimate the dimensionality of the subsurface resistivity structure. Then, by performing 3D inversion of 85 AMT data with relatively high quality, the 3D resistivity model from the surface to a depth of 2 km was determined, the high-temperature hydrothermal system under the Yangyi geothermal field was displayed for the first time. In addition, the main characteristics of the geothermal system were identified, and the genetic mechanism of the geothermal system was discussed based on the geological information and borehole data.

Gravity and Magnetic Focusing Inversion in Revealing the Metallogenic Pattern of Dahongshan Copper–Iron Deposit in the Kangdian Area, China

The Dahongshan deposit is influenced by pronounced structural controls and intrusions, and its model of mineralization resulting from volcanic sedimentation has faced criticism for an extended period. To describe the deep structure and distribution characteristics of the ore deposit, and to investigate its ore-forming process and metallogenic model, this study employs the gravity, magnetic, and controlled source audio-magnetotelluric data with different scales to independently recover the density, magnetization intensity, and electrical resistivity for shedding light on the deep structure and mineralization distribution of the deposit. The inversion results show the presence of a giant intrusion extending up to 6 km deep within the deposit. The distribution of iron-rich ore bodies and deposit are controlled by the basement tilting and faults, with the deposit exhibiting a U-shaped distribution and the mineral body occurring in a lens-like shape. Additionally, the electrical results indicate the presence of high-resistance magma along faults that intrude the deposit. We propose that the deposit is a magmatic-related deposit, with a deep intrusion believed to be the residual source body from early rift intrusion, providing the source for mineralization of the deposit. The characteristics of the deposit controlled by east-west and north-south structures and the lenticular orebody distribution indicate that the deposit is closely influenced by regional structure and magmatism of fault intrusion. The mineralization model is proposed to be a result of the coordinated actions of structural, magmatic, and regional dynamic background for the breakup and convergence of supercontinents.

Modeling a fractured geothermal reservoir using 3-D AMT data inversion: Insights from Garibaldi Volcanic Belt, British Columbia, Canada

An audio-magnetotelluric (AMT) survey was conducted to explore for shallow geothermal resources in the Garibaldi Volcanic Belt, the location of which has the highest geothermal potential in Canada. The data cover the south Meager geothermal system, including Pylon Peak and Meager Creek which have proven borehole temperatures exceeding 250 °C. A dimensionality analysis of the AMT data suggests complex 3-D subsurface structure. The 3-D resistivity model of the area shows two high conductivity features near surface in the areas south of Pylon Peak and north of Meager Creek, both of which are related to hydrothermal alteration. These layers act as the caprock and connect close to the surface. The conductive zones reach surface near the locations of warm springs along Meager Creek. Clay cap layers are interpreted to consist mainly of smectite, illite and rare kaolinite with the resistivities below 15 Ωm in our model. The caprock overlays fractured quartz diorite permeated by hot water. This hot fluid reservoir is related to a higher resistivity feature coinciding with high temperature zones at a depth of approximately 1 km below sea level. This model illustrates possible conduits through which the hydrothermal fluids were transported to thermal springs at the surface. This research shows that integrating the AMT model, geology, and temperature data is crucial to build a conceptual model of the Mount Meager geothermal system to support targeted drilling by industry.

Audio magnetotelluric denoising via variational mode decomposition and adaptive dictionary learning

The audio magnetotelluric (AMT) data are inevitably corrupted by cultural noise in the AMT exploration. This noise will distort apparent resistivity and phase, which affects the geophysical interpretation. The current AMT denoising technologies can not perform well when the cultural noise is severe. In order to improve the denoising accuracy, we propose a denoising technology called V-DDTF, which combines the variational mode decomposition (VMD) and the data-driven tight frame (DDTF). In the V-DDTF, The instantaneous frequency of the AMT signal envelope is first used to determine the number of decomposition layers. Then, the AMT signal is decomposed to several intrinsic mode functions (IMFs) and a residual by the VMD, after which the IMFs and a residual are rearranged as the input to learn dictionaries based on a tight frame constraint. To optimize the selection of parameters and improve denoising accuracy, we adopt an adaptive dictionary learning strategy. Finally, the inverse transforms are applied to the coefficients to achieve the AMT denoising. In our experiments, we validate the V-DDTF by synthetic data. We compare the V-DDTF with some other denoising methods and use the signal-to-noise ratio (SNR) and the Nyquist diagram as the assessments. Consequently, the V-DDTF not only creates dependable denoising results but also achieves the best performance among these mentioned methods. Furthermore, the field data experiments show the potential of the V-DDTF in industrial applications.

Electrical resistivity structure in the Tocomar geothermal system obtained from 3-D inversion of audio-magnetotelluric data (Central Puna, NW Argentina)

The Tocomar Geothermal System is located in the Puna Plateau (NW Argentina), within the Central Puna Energy Hub, and is considered one of the most promising places to harness potential alternative of power and heat sources in the Central Andean Volcanic Zone (16-28 °S). It is related to the Calama-Olacapato-Toro lineament and to the Quaternary Tocomar volcanic centre. Moreover, it is surrounded by active and fossil geothermal manifestations, like hot-springs, travertines and siliceous sinter deposits. Despite some geological studies in the area, no geophysical investigations have targeted the geothermal fields along the Central Puna.In this work we present a 3-D inversion of audio-magnetotelluric data around the Tocomar Geothermal System. These data was obtained in the frequency range of 1000-0.1 Hz to map the main elements of the geothermal system (clay cap and potential reservoir) at depths of approximately 1000 m. To achieve this goal, previous geoelectrical studies, the local geology and the trend of the main structures were also considered. For the 3-D inversion process the ModEM code was used.The model shows a low-resistivity layer (less than 10 Ωm) at least 300 m thick, at a depth of about 200–500 m, aligned with both the strike of the Calama-Olacapato-Toro lineament and the local superficial geothermal manifestations (hot-springs and hydrothermally altered rocks). This low-resistivity layer is linked with the clay cap at the shallow depth of the geothermal reservoir. At depths greater than 800 m, a gradual increase in resistivity is observed related to a potential reservoir within the fractured Ordovician basement. The final 3-D resistivity model highly correlates with the conceptual models of high-temperature volcanic geothermal systems.

Identification of Geothermal Reservoirs in South Cameroon from a Combined Landsat 8 and AMT Data

This geothermal source prospecting work is carried out in order to respond to the energy deficit affecting the populations of South Cameroon in particular. The study combines audio-magnetotelluric (AMT) and Landsat 8 data for the geolocation of reservoirs, as well as the geological and tectonic information. The processing of these data defined 5 profiles and led to two-dimensional models of resistivity sections for each profile. The interpretation of the data identified a highly conductive zone with a resistivity ranged 1–10 Ω·m at an estimated depth of 1200 m in the locality of Menve’ele. The Landsat 8 data collected in this area during the same period enabled the elaboration of temperature and lineament anomaly maps of the study area. High-temperature areas with high lineament predominance correlate better with areas of low resistivity. For example, Menve’ele (A1) has a surface temperature range of 20°C–30°C and a high density of lineaments. By correlating these results with those provided by previous authors, the Menve’ele locality may be the target of a potential geothermal reservoir. A 3D resistivity model is built to better understand the variations of resistivity and their depths. The geological and tectonic information of the region confirm the tectonic origin of the faults and lineaments as well as the predominance of metamorphic and sedimentary formations.

Geoelectric heterogeneities of the Kerch iron ore basin

The three-dimensional geoelectric model of the Earth’s crust and upper mantle of the Kerch Peninsula has been built for the first time based on the results of experimental observations of the Earth’s low-frequency electromagnetic field, carried out in 2007—2013 by the Institutes of the National Academy of Sciences of Ukraine. Its physical and geological interpretation and detailing of the near-surface part were carried out according to the data of the audiomagnetotelluric sounding method to study the deep structure of the Kerch iron ore basin. To the east of the Korsak-Feodosiya fault along the southern part of the Indolo-Kuban trough (in the north of the South Kerch and almost under the entire North Kerch zones), a low-resistance anomaly (ρ=1 Ohm∙m) was found at depths from 2.5 km to 12 km about 20 km wide. Its eastern part is located in the consolidated Earth’s crust and is galvanically connected with surface sedimentary strata, while the western part is completely in sedimentary deposits. The anomaly covers the territory of the Kerch iron ore basin and occurrences of mud volcanism. The characteristics of the upper part of the layered section of the Kerch Peninsula in the interval of the first hundreds of meters were obtained from the results of one-dimensional inversion of the audiomagnetotelluric sounding data (frequency range 8—4000 Hz). It is shown that the first 15 m of the section, corresponding to Quaternary deposits, have resistivity values up to 1 Ohm∙m. Below, in the Neogene sediments, the electrical resistance increases to values of 5 Ohm∙m and more. Both horizontally and vertically, the distribution of resistivity values has a variable character, manifesting as a thin-layered structure with low resistivity values. Possibly, such areas have a direct connection with the channel for transporting hummock material and gases. A connection is assumed between the low-resistivity thin-layered near-surface areas, a deep anomaly of electrical conductivity in the upper part of the Earth’s crust, and the likely high electrical conductivity of rocks at the depths of the upper mantle with iron ore deposits, as well as the manifestation of mud volcanism. The heterogeneity of the crustal and mantle highly conductive layers may indicate a high permeability of the contact zones for deep fluids.

Geothermal Reservoir Identification in Way Ratai Area Based on Gravity Data Analysis

Gravity research in the Way Ratai geothermal prospect area was conducted to determine geothermal reservoirs, heat sources, and the structure of the geothermal reservoir. The research carried out includes 3D inversion modeling of gravity data. The Bouguer anomaly in the study area has 50 mGal to 120 mGal with low anomalies located in the southeast (Ketang and Kelagian), Northeast (Gedong Air, Sungai Langka, Gunung Betung) areas, and in the Pesawaran mountain area. The high anomaly is in Merawan – Hanuberak – Padang Cermin, Sumbersari and Kaliawi. The horizontal gravity gradient map analysis shows a pattern of fault structure trending northwest-southeast and southwest-northeast, according to the main fault structure in the area. 3D inversion modeling obtains a density distribution between 1.8 g/cc to 3g/cc with a low-density distribution in the south, Mount Pesawaran/Ratai, Gunung Betung, and Sidoharum. The location of the manifestation is 9 km southeast of the Mount Ratai/Pesawaran summit. The existence of geothermal reservoirs is estimated to be in the Lubuk Badak and Miwung Hills areas which are located between the peaks of Mount Ratai/Pesawaran and geothermal manifestations. This is supported by the low-density distribution in the area and the resistivity map from audio-magnetotelluric data.