Search Results (73)

Magnetotelluric (MT) sounding is a crucial technique in mineral exploration. However, MT data are highly susceptible to various types of noise. Traditional data processing methods, which rely on the assumption of signal stationarity, often result in severe distortion when suppressing non-stationary noise. In this study, we propose a novel, adaptive, and less parameter-dependent signal decomposition method for MT signal denoising, based on time–frequency domain analysis and the application of modal decomposition. The method uses Variational Mode Decomposition (VMD) to adaptively decompose the MT signal into several intrinsic mode functions (IMFs), obtaining the instantaneous time–frequency energy distribution of the signal. Subsequently, robust statistical methods are introduced to extract the independent components of each IMF, thereby identifying signal and noise components within the decomposition results. Synthetic data experiments show that our method accurately separates high-amplitude non-stationary interference. Furthermore, it maintains stable decomposition results under various parameter settings, exhibiting strong robustness and low parameter dependency. When applied to field MT data, the method effectively filters out non-stationary noise, leading to significant improvements in both apparent resistivity and phase curves, indicating its practical value in mineral exploration. Full article

The precise identification of hydrocarbon-rich zones is crucial for optimizing exploration and production processes in the oil industry. Magnetotelluric (MT) surveys play a fundamental role in mapping subsurface geological structures. This study presents a novel methodology for automatically delineating resistivity contrasts in MT models by employing advanced machine learning and computer vision techniques. This approach commences with data augmentation to enhance the diversity and volume of resistivity data. Subsequently, a bilateral filter was applied to reduce noise while preserving edge details within the resistivity images. To further improve image contrast and highlight significant resistivity variations, contrast-limited adaptive histogram equalization (CLAHE) was employed. Finally, k-means clustering was utilized to segment the resistivity data into distinct groups based on resistivity values, enabling the identification of color features in different centroids. This facilitated the detection of regions with significant resistivity contrasts in the reservoir. From the clustered images, color masks were generated to visually differentiate the groups and calculate the area and proportion of each group within the pictures. Key features extracted from resistivity profiles were used to train unsupervised learning models capable of generalizing across different geological settings. The proposed methodology improves the accuracy of detecting zones with oil potential and offers scalable applicability to different datasets with minimal retraining, applicable to different subsurface environments. Ultimately, this study seeks to improve the efficiency of petroleum exploration by providing a high-precision automated framework with segmentation and contrast delineation for resistivity analysis, integrating advanced image processing and machine learning techniques. During initial analyses using only k-means, the resulting optimal value of the silhouette coefficient K was 2. After using bilateral filtering together with contrast-limited adaptive histogram equalization (CLAHE) and validation by an expert, the results were more representative, and six clusters were identified. Ultimately, this study seeks to improve the efficiency of petroleum exploration by providing a high-precision automated framework with segmentation and contrast delineation for resistivity analysis, integrating advanced image processing and machine learning techniques. Full article

Metallic minerals and some nonmetallic deposits (such as gas hydrate and natural gas) exhibit significant resistivity contrast with their surrounding rocks. Therefore, magnetotelluric (MT) sounding, which is highly sensitive to low-resistivity anomalies, offers a unique advantage in identifying these mineral resources. For metallogenic systems in sedimentary environments with approximately layered structures, we propose the Dynamic Error Bat Algorithm (DEBA), which integrates the cooling strategy, the dynamized fit error function, and the Bat Algorithm. DEBA enhances the breadth of global exploration in the early iteration stages while focusing on the depth of local exploitation in the later stages, yielding a more effective fitting outcome and better identification of electrical interfaces. Validity and noise immunity tests on typical synthetic models prove the robustness of DEBA. For broadband MT stations from the central Songliao Basin, we observed that the model derived from three-dimensional inversion did not provide an ideal layering effect for the shallow structure. Notably, the apparent resistivity and phase curves of these MT stations are similar, suggesting that the shallow structure in the study area has approximately one-dimensional (1-D) features, a conclusion that was further supported by phase tensor analysis. To gain a clearer understanding of the shallow structure, we applied DEBA to perform an averaged 1-D inversion. The subsequent results reveal a low-resistivity layer, which may be attributed to metallic sulfides or saline fluids. Full article

This study presents the results of the Magnetotelluric (MT) survey aimed at resolving the subsurface structures in the northern part of the Pingtung Plain. Data analysis was conducted using ten local observation stations and one remote reference station. Due to the significant noise of the urban environment, the process of obtaining high-quality results proved to be challenging. The impact of such noise on the transfer function estimation is demonstrated, emphasizing the need for careful data selection and processing to mitigate its effects. The results reveal a distinct low–high–low-resistivity trend in the subsurface, with the Quaternary–Neogene sediment boundary estimated to be up to 500 m deep. Additionally, this study maps depths of up to 4 km, where it indicates possible faulting structures below the study area, which may be related to the previously assumed structures south of the study area. Given the limited, available deep subsurface information of the study area, these findings offer a preliminary understanding of the subsurface characteristics of the northern Pingtung Plain, which may contribute to ongoing research on the geological characteristics of the region while taking into account the importance of addressing urban noise when interpreting MT data. Full article

This study investigated the formation mechanism of the Kahui Geothermal Field in Western Sichuan, China, using geophysical and geochemical approaches to elucidate its geological structure and geothermal origins. This study employed a combination of 2D and 3D inversion techniques involved in natural electromagnetic methods (magnetotelluric, MT, and audio magnetotelluric, AMT) along with the analysis of hydrogeochemical samples to achieve a comprehensive understanding of the geothermal system. Geophysical inversion revealed a three-layer resistivity structure within the upper 2.5 km of the study area. A geological interpretation was conducted on the resistivity structure model, identifying two faults, the Litang Fault and the Kahui Fault. The analysis suggested that the shallow part of the Kahui Geothermal Field is controlled by the Kahui Fault. Hydrochemical analysis showed that the water chemistry of the Kahui Geothermal Field is of the HCO₃−Na type, primarily sourced from atmospheric precipitation. The deep heat source of the Kahui Geothermal Field was attributed to the partial melting of the middle crust, driven by the upwelling of mantle fluids. This process provides the necessary thermal energy for the geothermal system. Atmospheric precipitation infiltrates through tectonic fractures, undergoes deep circulation and heating, and interacts with the host rocks. The heated fluids then rise along faults and mix with shallow cold water, ultimately emerging as hot springs. Full article

Sensor measurements are often affected by complex ambient noise and complicating signal processing tasks. The singular spectrum decomposition (SSA) algorithm, while widely used, faces challenges such as the difficulty of determining the number of decomposition layers, requiring iterative adjustments that reduce precision and increase processing time. This paper proposes an improved adaptive singular spectrum analysis (ASSA) algorithm that integrates a deep residual network (Res-Net) for automatic recognition. A comprehensive interference signal database was constructed to train the Deep Res-Net, and common interferences were restored through the combination of different signals, enabling greater frequency resolution performance. Meanwhile, a novel correlation detection reconstruction method based on a clustering algorithm for adaptive signal classification was developed to suppress background noise and extract meaningful signals. ASSA addresses the challenge of determining the optimal number of decomposition layers, eliminating the parameter adjusting process and enhancing the measurement efficiency of sensor systems. Through experiments, magnetotelluric (MT) observation data with complex interferences were applied to demonstrate the performance of ASSA, and promising results with an RMSE of 0.2 were obtained. The experiments also showed that the accuracy of ASSA was improved by 14% compared to other signal extraction algorithms, proving that ASSA can achieve excellent results when applied to other data processing fields. Full article

Magnetotelluric (MT) forward modeling is a key technique in magnetotelluric sounding, and deep learning has been widely applied to MT forward modeling. In three-dimensional (3-D) problems, although existing methods can predict forward modeling results with high accuracy, they often use multiple networks to simulate multiple forward modeling parameters, resulting in low efficiency. We apply multi-task learning (MTL) to 3-D MT forward modeling to achieve simultaneous inference of apparent resistivity and impedance phase, effectively improving overall efficiency. Furthermore, through comparative analysis of feature map differences in various decoder layers of the network, we identify the optimal branching point for multi-task learning decoders. This enhances the feature extraction capabilities of the network and improves the prediction accuracy of forward modeling parameters. Additionally, we introduce an uncertainty-based loss function to dynamically balance the learning weights between tasks, addressing the shortcomings of traditional loss functions. Experiments demonstrate that compared with single-task networks and existing multi-task networks, the proposed network (MT-FeatureNet) achieves the best results in terms of Structural Similarity Index Measure (SSIM), Mean Relative Error (MRE), and Mean Absolute Error (MAE). The proposed multi-task learning model not only improves the efficiency and accuracy of 3-D MT forward modeling but also provides a novel approach to the design of multi-task learning network structures. Full article

The strong multi-stage tectonic movement caused the northwest of the North China Plain to rise and the southeast to fall. The covering layer in the plain area was several kilometers thick. In addition to expensive drilling, it is difficult to obtain deep geological information through traditional geological exploration. In this study, gravity, magnetotelluric (MT) sounding and shallow seismic methods are used to explore the basement relief and stratigraphic structure of the alluvial proluvial area in front of Taihang Mount in the North China Plain so as to understand the geological structure and sedimentary evolution of the area. The gravity anomaly map reveals the basement uplift, depression shape and faults distribution on the horizontal plane in the whole area. The MT profile reflects the geoelectric characteristics of the three-layer distribution in the Cenozoic. The seismic profile deployed on the Daxing Uplift depicts the structural style of the uplift area. The well-to-seismic calibration establishes the relationship between the lithostratigraphic and the wave impedance interface so that we can accurately obtain the shape and depth of the bedrock surface and further subdivide Cenozoic strata. Finally, we have improved the accuracy of interface inversion by using a variable density model based on density logging parameter statistics to constrain the depth of geological interfaces determined through drilling and multi-geophysical methods. Through the combination of geology and comprehensive geophysics, we have obtained the undulating patterns of Paleogene and Quaternary bottom interfaces, the structural styles of the basement and the distribution of faults in the survey area, which provide strong support for the study of neotectonic movement and sedimentary environment evolution since the Cenozoic. The successful application of this pattern proves that geophysical surveys based on prior geological information are an important supplementary tool for geological research in thick coverage areas. Full article

To effectively separate strong cultural noise in Magnetotelluric (MT) signals under strong interference conditions and restore the true forms of apparent resistivity and phase curves, this paper proposes an improved method for suppressing strong cultural noise based on Particle Swarm Optimization (PSO) and Variational Mode Decomposition (VMD). First, the effects of two initial parameters, the decomposition scale K and penalty factor α, on the performance of variational mode decomposition are studied. Subsequently, using the PSO algorithm, the optimal combination of influential parameters in the VMD is determined. This optimal parameter set is applied to decompose electromagnetic signals, and Intrinsic Mode Functions (IMFs) are selected for signal reconstruction based on correlation coefficients, resulting in denoised electromagnetic signals. The simulation results show that, compared to traditional algorithms such as Empirical Mode Decomposition (EMD), Intrinsic Time Decomposition (ITD), and VMD, the Normalized Cross-Correlation (NCC) and signal-to-noise ratio (SNR) of the PSO-optimized VMD method for suppressing strong cultural noise increased by 0.024, 0.035, 0.019, and 2.225, 2.446, 1.964, respectively. The processing of field data confirms that this method effectively suppresses strong cultural noise in strongly interfering environments, leading to significant improvements in the apparent resistivity and phase curve data, thereby enhancing the authenticity and reliability of underground electrical structure interpretations. Full article

Geothermal resources are abundant in the Southern North China Basin, which is one of the prospective areas hosting low–medium-temperature geothermal resources in sedimentary basins in China. The purpose of this work is to reveal the formation and storage conditions of the geothermal resources in the western margin of the Taikang Uplift and delineate the range of potential geothermal reservoirs. This paper uses five magnetotelluric sounding profiles for data processing and analysis, including the calculation of 2D skewness and electric strike. Data processing, analysis, and NLCG 2D inversion were performed on MT data, which consisted of 111 measurement points, and reliable two-dimensional resistivity models and resistivity planes were obtained. In combination with drilling verification and the analysis of geophysical logging data, the stratigraphic lithology and the range of potential geothermal reservoirs were largely clarified. The results show that using the magnetotelluric sounding method can well delineate the range of deep geothermal reservoirs in sedimentary basins and that the MT method is suitable for exploring buried geothermal resources in deep plains. The analytical results showed that the XZR-1 well yielded 1480 cubic meters of water per day, with the water temperature of the wellhead being approximately 78 °C, and combined with the results of this electromagnetic and drilling exploration, a geothermal geological model and genesis process of the west of the Taikang Uplift area was constructed. The water yield and temperature were higher than those of previous exploration results, which has important guiding significance for the future development and utilization of karst fissure heat reservoirs in the western Taikang Uplift. Full article

The Sumatran Fault runs from the southeast (SE) to the northwest (NW) of Sumatra Island, with the highest slip rates reaching about 3.0 cm per year in the northwestern part. There is a seismic gap along this fault, including the northern Aceh domain, which consists of the Aceh and Seulimeum fault segments. Previous studies have used various methods to investigate the Sumatran Fault system, including seismic, geoelectric, gravity anomaly, and magnetotellurics (MT). The MT method has proven advantageous as it can non-destructively image a wide range of depths. However, previous studies using the two-dimensional (2D) MT inversion did not represent realistic information of the subsurface conditions. Therefore, a three-dimensional (3D) MT data inversion was used in this study to obtain more realistic information about the resistivity structure of the Aceh and Seulimeum segments. The results confirmed that the Sumatran Fault is a strike-slip fault, with a relatively northwest (NW)–southeast (SE) direction of conductivity strike with an angle of S 71.61° E from Groom–Bailey decomposition of MT data. The 3D resistivity distribution model from 33 stations showed that the Aceh Fault Segment is 20–30 km away, while the Seulimeum Fault Segment is 55–60 km away based on the MT data. The results also indicated a creeping zone at a depth of 2 km beneath the Aceh Fault Segment. Different rock formations were identified beneath the fault system, with the western part of the Aceh Segment dominated by high-resistivity metamorphic rocks (150–1000 Ωm) from the Triassic–Cretaceous age. The zone between the Aceh and Seulimeum fault segments exhibited low resistivity, characterized by volcanic rocks (1–15 Ωm) from the Lam Teuba Volcanic Formation and the Indrapuri Formation. Beneath the eastern part of the Seulimeum Fault Segment was found to consist of low-resistivity quaternary volcanic rocks (1–15 Ωm) and high-resistivity andesite rocks (4.5 × 10⁴–1.7 × 10⁵ Ωm). These findings correlated well with the geological map. Full article

The exploration of porphyry deposits in Greenland has become increasingly important due to their significant economic potential. We utilized total magnetic intensity (TMI) and mobile magnetotelluric (MobileMT) airborne data to delineate potential porphyry mineralization zones. The TMI method was employed to map variations in the Earth’s magnetic field caused by subsurface geological features, including mineral deposits. By analyzing anomalies in TMI data, potential porphyry targets were identified based on characteristic magnetic signatures associated with mineralized zones. Complementing TMI data, MT airborne surveys provided valuable insights into the electrical conductivity structure of the subsurface. Porphyry deposits exhibited distinct conductivity signatures due to the presence of disseminated sulfide minerals, aiding in their identification and delineation. Integration of the TMI and MobileMT datasets allowed for a comprehensive assessment of porphyry exploration targets in Flammefjeld. The combined approach facilitates the identification of prospective areas with enhanced geological potential, optimizing resource allocation and exploration efforts. Overall, this study demonstrates the efficacy of integrating TMI and MobileMT airborne data for porphyry exploration in Greenland, offering valuable insights for mineral exploration and resource development in the region. Full article

Over the past few years, there has been a noticeable change in the occurrence of seismic disasters in Sichuan, China. The focus has shifted from Western Sichuan to the previously more stable Southeastern Sichuan. The recent Ms6.0 earthquake in Luxian, Southeastern Sichuan, on 16 September 2021, has once again captured the interest of scholars, who are closely examining the seismogenic environment and potential seismic hazards in the region. We conducted a magnetotelluric (MT) array survey in the Luxian earthquake area to explore the deep seismogenic environment of the 2021 Luxian Ms6.0 earthquake zone and understand the potential effects of industrial extraction on seismic activities. Here are the insights we obtained: Underneath the anticline in the Luxian Ms6.0 earthquake area, there is a structure that mainly exhibits high resistance. On the other hand, beneath the syncline, a structure with medium to low resistance is observed. The epicenter of the mainshock was identified near the intersection of high- and low-resistance media within the Fuji syncline area. Smaller aftershocks that followed the mainshock were mainly concentrated in the low-resistance layers at depths of 3–5 km in the Fuji syncline area. MT survey results have confirmed the existence of a detachment zone in the shallow crust near the epicenter of the Luxian Ms6.0 earthquake. It is believed that this detachment layer played a significant role in the seismogenic process of the Luxian Ms6.0 earthquake. During different stress conditions, this layer became active and caused the compression and faulting of a hidden fault below, resulting in the Luxian Ms6.0 earthquake. After the main earthquake, a series of smaller aftershocks with varying focal mechanisms occurred as the stress fields continued to release. It is important to note that the Luxian Ms6.0 earthquake highlights the ongoing high stress levels in the southern region of the Sichuan Basin. This emphasizes the need for continued monitoring and consideration of potential seismic hazards in the southern Sichuan area. Full article

Due to the complex intersection and control of multiple structural systems, the hydrogeological conditions of the Laiyuan Basin in China are complex. The depth of research on the relationship between geological structure and groundwater migration needs to be improved. The supply relationship of each aquifer is still uncertain. This paper systematically conducts research on the characteristics of hydrogen and oxygen isotopes, and combines magnetotelluric impedance tensor decomposition and two-dimensional fine inversion technology to carry out fine exploration of the strata and structures in the Laiyuan Basin, as well as comprehensive characteristics of groundwater migration and replenishment. The results indicate the following: (i) The hydrogen and oxygen values all fall near the local meteoric water line, indicating that precipitation is the main groundwater recharge source. (ii) The excess deuterium decreased gradually from karst mountain to basin, and karst water and pore water experienced different flow processes. (iii) The structure characteristics of three main runoff channels are described by MT fine processing and inversion techniques. Finally, it is concluded that limestone water moved from the recharge to the discharge area, mixed with the deep dolomite water along the fault under the control of fault F2, and eventually rose to the surface of the unconsolidated sediment blocked by fault F1 to emerge into an ascending spring. Full article

The Jinchuan Ni-Cu sulfide deposit in the Longshoushan terrane is among the world’s largest magmatic sulfide deposits. This study uses magnetotelluric (MT) survey data imaging combined with previous geophysical data to investigate Segment III of the deposit. The image of MT data reveals a significant low-resistivity anomaly ~200 m beneath Segment III, aligning with known ore bodies, and an additional anomaly to the north, indicating further exploration potential. These findings highlight the deep-seated intrusions and their connection to surface mineralization, emphasizing the critical role of ultramafic rock encapsulation and fault-controlled morphology in ore body formation. The newly identified northern anomaly, resembling the Segment III ore bodies, suggests a promising target for future exploration. Integrating MT surveys with other geophysical methods enhances the understanding of subsurface structures and mineralization, providing a robust framework for discovering concealed mineral deposits and improving exploration efficiency. Full article