Audio-frequency Magnetotellurics Research Articles

Analysis and Design of an Airborne-Dangled Monopole-Antenna Symmetric Remote-Sensing Radiation Source for Airport Runway Monitoring

Traditional methods for monitoring the foundation settlement of airport runways predominantly employ equipment such as leveling instruments, total stations, layered settlement instruments, magnetic ring settlement instruments, ground-penetrating radar (GPR), and synthetic aperture radar. These methods suffer from low automation levels, are time-consuming, labor-intensive, and can significantly disrupt airport operations. An alternative electromagnetic detection technique, Controlled Source Audio-Frequency Magnetotellurics (CSAMT), offers deep-depth detection capabilities. However, CSAMT faces significant challenges, particularly in generating high signal-to-noise ratio (SNR) signals in the far-field region (FfR). Traditional CSAMT utilizes grounded horizontal dipoles (GHDs), which radiate symmetric beams. Due to the low directivity of GHDs, only a small fraction of the radiated energy is effectively utilized in FfR observations. Enhancing the SNR in FfR typically requires either reducing the transceiving distance or increasing the transmitting power, both of which introduce substantial complications. This paper proposes an airborne-dangled monopole-antenna symmetric remote-sensing radiation source for airport runway monitoring, which replaces the conventional GHD. The analytical, simulation, and experimental verification results indicate that the energy required by the airborne-dangled symmetric source to generate the same electric field amplitude in the FfR is only one-third of that needed by traditional CSAMT. This results in significant energy savings and reduced emissions, underscoring the advantages of the airborne-dangled monopole-antenna symmetric source in enhancing energy efficiency for CSAMT. The theoretical analysis, simulations, and experimental results consistently verify the validity and efficacy of the proposed airborne-dangled monopole-antenna symmetric remote-sensing radiation source in CSAMT. This innovative approach holds substantial promise for airport runway monitoring, offering a more efficient and less intrusive solution compared to traditional methods.

Advancing Sustainable Geothermal Energy: A Case Study of Controlled Source Audio-Frequency Magnetotellurics Applications in Qihe, Shandong

Geothermal energy is a key part of sustainable and renewable energy strategies, especially for clean heating in northern regions. This study focuses on Qihe County in Shandong Province, applying a controlled source audio-frequency magnetotellurics (CSAMT) method to investigate deep karst geothermal reservoirs. This research addresses the complex geological conditions and electromagnetic interference in the region, aiming to improve sustainable geothermal resource development. The findings indicate that the geothermal reservoir in the study area primarily consists of Ordovician limestone, characterized by moderate burial depth, high water volume, and elevated water temperature. Integrating CSAMT with vertical electrical sounding (VES) and radiometric surveying has clearly defined the deep aquifer layers and major water-controlling fault structures. Drilling verification results demonstrate the significant effectiveness of the integrated geophysical methods employed, providing reliable technical support for deep geothermal exploration in similar regions. This study makes a significant contribution to the scientific and technical foundation necessary for the sustainable development and utilization of geothermal resources, supporting the broader goals of environmental sustainability and renewable energy.

Improving deep groundwater aquifer characterization with deep learning inversion of audio-frequency magnetotelluric data

Deep groundwater is a crucial resource for drinking, industry, and ecosystems. However, its extensive subsurface distribution poses challenges for traditional hydrological sampling methods. Audio-frequency Magnetotelluric (AMT) is commonly used to image shallow subsurface resistivity distribution, but its application for quantifying deep groundwater aquifers is challenging. In this study, we propose a two-step strategy deep learning (DL) to estimate subsurface water information from AMT data. First, we employ an inversion DL network to directly predict subsurface resistivity distribution from AMT data. To assess the impact of data and prior information on DL inversions, we progressively include more input data during training, from apparent resistivity to apparent resistivity, phase, and Bostick transformed initial models. In the second step, we use another DL network to predict subsurface structure from AMT inversion results. We then estimate water content based on unit-specific petrophysical relationships. Evaluating our algorithm with synthetic cases, we find that including more information generally improves network performance, particularly when incorporating initial Bostick transformed models. Applying the algorithm to a field hydrogeological survey, we compare the inversion network trained with apparent resistivity, phase, and Bostick transformed initial models to traditional regularization inversions. The new approach shows better consistency with borehole data. Another network extracts structure information, enabling the estimation of subsurface water content and gaining valuable hydrogeological insights. To summarize, our study presents a novel DL-based approach to quantitatively delineate deep groundwater aquifers using AMT data. The proposed algorithm demonstrates promising performance in estimating subsurface hydrologic properties, providing valuable insights for hydrogeological investigations.

Estimation of rock core indices for development of underground infrastructure using non-invasive geophysical methods

Rock mass characterization offers the basis of the stability criterion for the planning and advancement of civil engineering projects. Rock core index (RCI) is one of the key geotechnical parameters adopted in rock mechanics and rock engineering. RCI provides risk assessment regarding the success criteria of engineering design. Consequently, an accurate estimate of such parameters is a challenging task in the context of credibility, budget, and time. However, the traditional estimation of geomechanical parameters needs lots of drilling tests at some selected points. The point-scale data often cause more ambiguity and less authenticity in engineering design. Besides, the conventional approaches are invasive, uneconomical, and laborious and cannot investigate the complete project site. We offer an indirect technique for the estimate of RCI using empirical relationships between drilling and geophysical data, which addresses the drawbacks of the conventional methods. Geophysical techniques offer the subsurface volumetric data and are faster, more affordable, and easier to use. In this study, we employ a non-invasive CSAMT (controlled-source audio-frequency magnetotellurics) method for the first time to quickly assess 2D and 3D RCI models. The suggested approach assesses the intricate geological subsurface at a depth of 1 km in order to produce a more precise and complete image of the quality of the rock mass across a wide area. These findings are crucial for improving our understanding of the intricate geological conditions, estimating the likelihood of failure early on, and supporting the safe, stable, and cost-effective construction of deep underground engineering structures. In regions where there is a deficiency of mechanical drilling data, our approach decreases the gaps between an appropriate geotechnical model and insufficient data, yields more objective indices, and serves as a guide for more correct engineering structure design.

Application Research of Integrated Geophysical Methods in Hydrogeological Survey in Extremely Arid Desert Areas

The research area is located in the Wuyi Mountain area of Dunhuang, Gansu Province, belonging to an extremely arid desert region. Previous hydrogeological surveys in the area had not conducted geophysical exploration work, and most of the hydrological boreholes previously drilled had either low water yield or almost no water yield. In this study, based on a comprehensive analysis of existing regional geological and hydrogeological data, the researchers conducted Controlled Source Audio-frequency Magnetotellurics (CSAMT) measurements and high-density electrical resistivity tomography (ERT) measurements. This work essentially identified the hydrogeological characteristics such as buried fracture water in the structural zones of the research area and water-rich properties. Hydrogeological boreholes were then deployed, and subsequent drilling confirmed a relatively high water yield.

Configuration of Carbonatite Constrained in Preintrusion Transpositional Foliation in the Bayan Obo Giant Rare Earth Element Deposit, China

Abstract The Bayan Obo ore deposit is the largest rare earth element (REE) deposit in the world and has been assumed to be hosted in dolomite that was folded in a syncline. This has been challenged by results from drill holes and low-resistivity, controlled-source audio-frequency magnetotellurics (CSAMT) survey. In this paper, we present structural analysis of clastic sedimentary rocks from around the deposit, their relationship with carbonatite, and the orientations of the carbonatite bodies and dikes to constrain the possible configuration of carbonatite. Clastic sedimentary rocks underwent mylonitic deformation to slate, metasandstone, and metaconglomerate, displaying dramatic changes of thickness along strike. Slates locally preserve intrafolial folds and hook folds bounded by foliations; metasandstones have parallel layers of recrystallized and preferred-orientated quartz aggregations; metaconglomerates contain flattened pebbles with Flinn k values of 0.01 to 0.05 and 0. The above structures and foliations were crosscut and intruded by carbonatite and associated fenite, demonstrating preintrusion transposition of original bedding to steep foliation. Preintrusion foliation provides zones of weakness that were exploited by upwelling of carbonatite magma. Northeast-SW–striking left-stepping en echelon carbonatite dikes and E-W–striking carbonatite bodies indicate that the carbonatite was emplaced in a sinistral transtensional zone. The northern and southern segments of the carbonatite bodies are parallel to the steep foliation at shallow depths and merge together at depth, constraining a Y-shaped configuration, consistent with the low resistivity result of the CSAMT survey. The newly recognized Y-shaped morphology indicates that the carbonatite extends deeper than 1,775.4 m, more than twice the previously inferred maximum depth of the syncline model, and contributes to a significant >1.78 times increase in global potential RE2O3 resources than previously estimated in 2021.

Distributed wide-field electromagnetic method for coal mining goaf detection in a complex urban environment: A case study in Jinan, China

Urban expansion has resulted in many proposed projects located over coal mining zones, which has highlighted the importance of detecting the spatial scope and water abundance of goafs before the commencement of construction work. Although electromagnetic (EM) methods have proven effective for goaf detection, their applications in intensely noisy and urbanized environments remain limited. To address this challenge, we evaluate an investigation of a coal mining goaf in Jinan, China, using the distributed wide-field EM (DWFEM) method. A third-order [Formula: see text] sequence pseudorandom signal with 39 survey frequencies is transmitted to achieve long-time data acquisition at each station. Unlike the controlled-source audio-frequency magnetotellurics method, the DWFEM records only the electric field [Formula: see text] component. The synthetic model tests and field data demonstrate the consistency of the [Formula: see text] apparent resistivity and the Cagniard resistivity in the far field. The long-time acquisition and 1C recording greatly improve data quality and exploration efficiency. We also use an all-angle resistivity calculation formula and an electrode layout method parallel to the wire source to obtain electrical connections in different directions. The DWFEM inversion results are obtained using the 1D Gauss-Newton iterative method under a plane-wave assumption. By interpolating the data from different measurement stations, we image resistivity depth profiles and obtain 3D subsurface electrical data for the subsurface from 0 to 1000 m. We interpret the obtained profiles with geologic and mining information, revealing two significant water-enriched goaf areas. Validation is performed using seismic data and drill cores. The results significantly enhance our understanding of the characteristics of the coal mine under our project and highlight the applicability of the DWFEM for detecting goafs in complex urban environments.

Denoising CSAMT signals in the time domain based on long short-term memory

Abstract Controlled-source audio frequency magnetotellurics (CSAMT) is an artificial-source electromagnetic technique that partially mitigates the limitations of weak natural-field signals. However, practical field surveys inevitably encounter strong interference, severely affecting signal quality. Traditional methods such as Fourier transformation, which directly computes apparent resistivity from frequency-domain information, are inadequate in this context, so we need alternative denoising approaches. However, research on CSAMT denoising is currently limited. Given the excellent performance of long short-term memory (LSTM) neural networks in the processing of magnetotelluric (MT) data, as demonstrated by previous studies, this paper proposes the use of LSTM to denoise CSAMT signals in the time domain. Unlike traditional denoising methods, we aim to directly extract the target frequency signal from the time-series data for denoising. For MT data, target frequency signals and noise are all mixed together, so noise suppression can only be achieved by identifying noise characteristics in the time series. However, unlike MT data, CSAMT data has an artificial transmitting source, and the frequency of the valid signal is fixed within a time interval. This allows for the direct extraction of target frequency signals without considering the complex characteristics of noise. In this study, we developed a neural network based on bidirectional LSTM to accomplish the task of noise suppression. After conducting both simulated and measured data tests, this method was able to, on average, improve the signal-to-noise ratio (SNR) of CSAMT data by approximately 20 dB and partially address the challenge of denoising when the data's SNR falls below 0 dB.

Spatial structural characteristics of the Deda ancient landslide in the eastern Tibetan Plateau: Insights from Audio-frequency Magnetotellurics and the Microtremor Survey Method

Spatial structural characteristics of the Deda ancient landslide in the eastern Tibetan Plateau: Insights from Audio-frequency Magnetotellurics and the Microtremor Survey Method

3-D Inversion of the Data-Normalized Time-Lapse Controlled-Source Audio-Frequency Magnetotelluric Method

3-D Inversion of the Data-Normalized Time-Lapse Controlled-Source Audio-Frequency Magnetotelluric Method

Detecting and recovering critical mineral resource systems using broadband total-field airborne natural source audio frequency magnetotellurics measurements

Airborne geophysical methods offer a substantial advantage compared to ground-based techniques in exploring territories of different sizes, ranging from entire metallogenic provinces to the deposit scale, including those hosting critical minerals. An airborne method with measurements of natural magnetic field variations, known as audio frequency magnetotellurics (a passive field method), significantly increases the depth of investigation and expands the resistivity detection range compared with some controlled-source primary-field methods. We describe the technical solutions used in an airborne electromagnetic passive system with a mobile sensor of the total magnetic field variations and the stationary sensor of electric field variations, and its applications to recovering the complex geology of hydrothermal-magmatic systems often associated with critical minerals. The system’s ability to explore depths, typically beginning from the near-surface and down to 1–2 km, by recording responses in three orthogonal inductive coils over a broad bandwidth from 22 Hz to 21,000 Hz allows for mapping resistivities across a broad range. This capability is crucial for obtaining more comprehensive exploration models. Field case studies of the natural field system include application in exploring for unconformity uranium mineralization, along with other associated minerals, epithermal gold and polymetallic-bearing structures, and ferromanganese and polymetallic deposits formed in a continental rift valley. An extra case study involving kimberlites was incorporated as a proven example of the natural field system’s capability in conducting near-surface and deep investigations. The case histories illustrate the airborne natural electromagnetic field technology capabilities in recovering geoelectric models and their specific patterns.

Delineation of shallow volcanic structures from audio-frequency magnetotelluric data beneath Ulleung Island, East Sea (Sea of Japan)

As volcanoes are closely related to the living environment of humans, in particular via natural hazards and geothermal energy, scientific studies on volcanic edifice structures are required. Ulleung Island is a Quaternary volcanic island located in the mid-western East Sea (Sea of Japan). In this study, we conducted an audio-frequency magnetotelluric (AMT) survey to image the substructure of the Ulleung volcanic edifice. In addition, the electrical structure was interpreted from the geothermal system perspective, geochemical compositions of volcanic rocks, and the possibility of the presence of a magma reservoir. AMT data were obtained from 25 stations and processed using the remote reference technique. Then, the three-dimensional (3-D) approach was reasonably adopted according to dimensionality analysis. Before conducting the 3-D inversion, the effects on topography and ocean were analyzed using a simplified 3-D synthetic model, because Ulleung Island is surrounded by sea and the topography is undulating. Most AMT stations on Ulleung Island are distorted by topographical and oceanic effects; in particular, oceanic effects are significant at frequencies lower than 10 Hz. The 3-D inversion was conducted with full impedance components and vertical magnetic transfer functions in a frequency range of 10,000–1 Hz. The results show that the Ulleung volcanic edifice is characterized by two layers of electrical structures as follows: near-surface resistive anomalies and an underlying conductive layer. Considering the high geothermal gradient on Ulleung Island, we suggest that the conductive layer of the volcanic edifice is due to hydrothermal alteration of basaltic rocks, with a potential heat source underneath. Based on the geochemical characteristics of the Ulleung volcanic rocks, the possibility of heat transfer from a trachytic magma reservoir within the shallow crustal is suggested. In summary, this study presents a geological interpretation of shallow volcanic structures beneath Ulleung Island and the possibility of an active magma reservoir as a potential heat source for the volcanic edifice.Graphical

Evaluation of rock mass units using a non-invasive geophysical approach

Thorough and accurate assessment of rock mass units is important for development of engineering infrastructures and groundwater resources assessments. Rock mass units are widely evaluated by reliable geomechanical parameters namely rock quality designation (RQD) and rock core index (RCI). Conventionally, these parameters are acquired via an extensive number of geotechnical tests. Such tests, however, suffer efficiency for data coverage, cost, equipment and topographic constrictions, and hence cause ambiguity in geological models for a detailed evaluation of rock mass integrity. Conversely, geophysical surveys offer fast, more user-friendly, less invasive, more cost-effective and less time-consuming approach for geological investigations. The past research confirms a useful link between geophysical and geotechnical parameters. But, none of the past studies provides a suitable and generalized relation between these parameters which can reduce geotechnical model uncertainty mostly caused by inadequate data and subsurface heterogeneity. This paper proposes a meaningful and feasible method to obtain geomechanical parameters using a certain number of drillings and geophysical data of four different sites. Based on electrical resistivity obtained from electrical resistivity tomography (ERT) and controlled-source audio-frequency magneto telluric (CSAMT), this research provides the general and adaptable formulas for geotechnical parameter estimation and reduces geological model uncertainty for more detailed 2D/3D imaging of RQD and RCI covering the whole sites where even no drilling data exists. Thus, the investigated sites are assessed laterally and vertically along each geophysical profile via distinct value ranges of geological parameters for a thorough and reliable evaluation of rock mass units in highly heterogeneous setting. Our research reduces the ambiguity caused by structural heterogeneities and scarce data, fills the gap between inadequate well tests and the true geological models, and gives new insights into the rock mass units for proper engineering design and groundwater exploitation.

Deep Learning Based Noise Identification for CSAMT Data Processing

Controlled-source audio-frequency magnetotellurics (CSAMT) has been seriously affected by strong electromagnetic interferences including large-scale drift, durative outbreak interference, and impulsive outliers. To improve the efficiency of noise reduction, a deep learning strategy was proposed to identify the type of noise interference, so as to select the appropriate noise reduction method. First, a CSAMT time series simulation algorithm was developed based on current decomposition and one-dimensional (1D) forward modeling. Three kinds of noise interferences were also generated by simulation and randomly added to the pure signals. A total of 30000 groups of simulated noisy electromagnetic signals were generated. Together with 210 sets of practically measured data, these samples were used to train a long-short-term memory network (LSTM) noise classifier. Then, three targeted de-noising algorithms were adopted to separate the three interferences in the CSAMT time series according to the identifications. The test results by simulated data showed that the identification accuracy of LSTM for noise interferences can reach more than 95%. Finally, the noise identification and suppression methods were applied to a practical CSAMT dataset and the effect was further verified.

Application of audio-frequency magnetotelluric data to cover characterisation – validation against borehole petrophysics in the East Tennant region, Northern Australia

The characterisation of the thickness and geology of cover sequences significantly improves targeting for mineral exploration in buried terrains. Audio-frequency Magnetotelluric (AMT) data is applicable to characterise cover sequences, where their conductivity (inverse resistivity) can be differentiated. We present a regional study from the under-cover East Tennant region in the Northern Territory (Australia) where we have applied deterministic and probabilistic inversion methods to derive 2D and 1D resistivity models. We integrated these models with information of co-located basement penetrating boreholes (lithological and geophysical logs) to ground-truth and validate the models and to improve geophysical interpretations. In the East Tennant region, borehole lithology and wireline logging demonstrate that the modelled AMT response is largely controlled by the mineralogy of the cover and basement rocks. The bulk conductivity is due primarily to bulk mineralogy and the success of using the AMT models to predict cover thickness is shown to be dependent on whether the bulk mineralogy of cover and basement rocks are sufficiently different to provide a detectable conductivity contrast. Our investigation of a range of geological scenarios that differ in thickness, complexity and geology of the cover and basement rocks suggests that in areas where there is sufficient difference in bulk mineralogy and where the stratigraphy is relatively simple, AMT models predict the cover thickness with high certainty. In more complex scenarios interpretation of AMT models may be more ambiguous and requires integration with other data (e.g. drilling, wireline logging, potential field modelling). Overall, we conclude that the application of the method has been validated and the results compare favourably with borehole stratigraphy logs once geological (i.e. bulk mineralogical) complexity is understood. This demonstrates that the method is capable of identifying major litho-stratigraphic units with resistivity contrasts. Our results have assisted with the planning of regional drilling programs and have helped to reduce the uncertainty and risk associated with intersecting targeted stratigraphic units in covered terrains.

Anatomy of the convective geothermal system from geophysical and hydrochemical data: A case study from the Changshou geothermal field, South China

There are abundant low-medium temperature geothermal resources in southern China; however, a lack of research into their properties restricts the utilization of the geothermal energy. To expand the geothermal energy potential in southern China, it is vital to clarify the nonvolcanic geothermal system mechanisms. This study aimed to elucidate the mechanisms for the Changshou geothermal field, as a representative structurally controlled convective geothermal system, by analyzing the geophysical and hydrochemical data. The surface-to-subsurface (400 m depth) electrical resistivity structure of the geothermal field was obtained by 2D inversion of two intersecting controlled-source audio-frequency magnetotellurics and electrical resistivity tomography geophysical profiles. We identified the cap rock, reservoir, and fluid pathways of the geothermal system and verified them via drilling results. The cap was composed of Quaternary sediments and Cretaceous sandstone with moderate resistivity (10–50 Ωm), and the geothermal reservoir and fluid pathways were composed of dolomites and fracture zones with low resistivity (less than 5 Ωm), respectively. The hydrochemical results showed that the geothermal water was of the type HCO3·SO4−Ca·Mg, with low values of total dissolved solids resulting from shallow groundwater mixing. Isotope analyses indicated that the geothermal water was derived from precipitation in the Dahong Mountains, southeast of the geothermal field. The average temperature of the geothermal reservoir, as estimated by chalcedony and K-Mg geothermometers, was 53°C. Based on the geothermal gradient calculation, the circulation depth of the groundwater was 1500 m, with the circulation process driven by heat flows originating deep within the earth. The Changshou geothermal field was identified as a potential source of energy for residential heating in winter, owing to the large flow (2700 m3/d) and high permeability (24.03 m/d) of the geothermal reservoir.

Exploration of geothermal resources using comprehensive electromagnetic method

Geothermal resource is a kind of crucial clean, renewable energy with high potential development and application. However, it involves great exploiting risks since it buried deep beneath the crust of the Earth. The location and depth of geothermal resources can be determined using the geophysical methods. Controlled source audio-frequency magnetotellurics (CSAMT) and transient electromagnetic method (TEM) have relatively high efficiency and robustness. In this paper, a simplified geothermal system resistivity model was established, which allowed TEM and CSAMT to differentiate target faults with various characteristics (resistivity, dip angle and width). Through a comprehensive electromagnetic exploration in Huairen County, Shanxi Province, China as an example, the performance of TEM and CSAMT in determining geothermal resources was evaluated. The results showed that both methods could examine the geoelectrical structures from various perspectives, and the effectiveness of comprehensive electromagnetic method for geothermal resources was presented.

Comprehensive Evaluation of Goaf Range in a Coal Mine with a Complex Terrain through CSAMT and an Activated-Carbon Method for Radon Measurement

Underground goaves were left in many mining areas due to the continuous exploitation of coal resources. These mining areas seriously affect the production safety of the mines and the safety of life and property of the surrounding residents. Enormous safety hazards will be generated if the goaf range is not accurately controlled. In this study, we proposed a method for the detection of goaves in coal mines with a complex terrain by combining controlled source audio-frequency magnetotellurics (CSAMT) and an activated-carbon method for radon measurement. The disadvantage of failing to interpret goaf depth for the activated-carbon method for radon measurement was compensated by the advantage of the capability of goaf-depth sounding for CSAMT. Subsequently, the reference for CSAMT data was provided by the immunity of the activated-carbon method for radon measurement to the influences of terrain, earth electricity, and EMF. On this basis, the proposed method was employed to detect the goaf of Houjiagou Coal Mine in Liulin County, China, and obtained reliable detection results. The feasibility of the comprehensive geophysical prospecting method in the complex terrain was verified and it provides a new reference for the detection method of goaves with other conditions.

Shallow resistivity structure around the 2018 craters of Mt. Motoshirane of Kusatsu-Shirane Volcano, Japan, revealed by audio-frequency magnetotellurics

In 2018, a phreatic eruption occurred at Mt. Motoshirane, a pyroclastic cone group of the Kusatsu-Shirane Volcano in central Japan. The eruption was abrupt, and no signs of volcanic activity have been observed in recent years, in contrast to the other major pyroclastic cone group, Mt. Shirane, which hosts the active crater lake and has endured repeated phreatic eruptions. To understand the mechanism of the eruption at Mt. Motoshirane, information on the shallow hydrothermal system, which is thought to be the source region of phreatic eruptions, is required; however, few studies have been conducted on this particular cone group. In this study, we conducted an audio-frequency magnetotelluric survey in 2020 to reveal the shallow resistivity structure around the 2018 craters. A three-dimensional resistivity structure model showed generally two layers, with high resistivities at shallow depths overlain by low resistivities underneath. The boundary between the layers corresponded to the top boundary of the Neogene basement rocks. These low resistivities were not found beneath the 2018 craters; therefore, part of the Neogene basement rocks could have been lost by the eruption beneath the 2018 craters. This is consistent with the geochemical study on the mineral assemblage of the erupted deposits, which suggested that the explosions reached the depth of the basement.Graphical

Hydrogeological Study in Tongchuan City Using the Audio-Frequency Magnetotelluric Method

Tongchuan City, located in Shaanxi Province, northwest China, has limited groundwater resources. Rational planning and exploitation of groundwater are crucial to the sustainable development of the city, for which investigating the distribution of groundwater is the premise. Traditional resistivity sounding methods are often used to detect groundwater; however, these methods are not applicable in the study area where thick Quaternary loess is extensively distributed. In this study, we arranged five audio-frequency magnetotelluric (AMT) profiles to detect the deep clastic rock groundwater and carbonate karst fissure groundwater in Tongchuan. Firstly, we analyzed the electromagnetic interference (EMI) noises in Tongchuan City, revealing that the main EMI is power frequency interference (PFI). We used the dictionary learning processing technology to suppress the PFI. Secondly, the two-dimensional (2D) nonlinear conjugate gradient method was employed to invert a 2D electrical structure model for the area shallower than 1 km. We analyzed the characteristics of the electrical structure and its geological significance. Lastly, the three-dimensional (3D) electrical structure model of the study area was inverted using the 3D nonlinear conjugate gradient method, and the spatial distribution characteristics of the water-bearing strata were further analyzed. The results show that the PFI in urban environment can be suppressed by the dictionary learning processing technology. In Tongchuan city, the distribution of clastic rock fissure water is controlled by folds and faults, as well as the thickness of sandstone layers, and that of the carbonate karst fissure water is mainly controlled by faults. On this basis, we infer that the water-bearing areas are in the middle east and south of the study area.