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18 pages, 4398 KB

Open AccessArticle

Connectivity Evaluation of Fracture-Cavity Reservoirs in S91 Unit

by Yunlong Xue, Yinghan Gao and Xiaobo Peng

Appl. Sci. 2025, 15(17), 9738; https://doi.org/10.3390/app15179738 - 4 Sep 2025

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Carbonate fracture–cavity reservoirs are significant oil and gas reservoirs globally, and their efficient development is influenced by the connectivity between fracture–cavity units within the reservoir. These reservoirs primarily consist of large caves, dissolution holes, and natural fractures, which serve as the primary storage [...] Read more.

Carbonate fracture–cavity reservoirs are significant oil and gas reservoirs globally, and their efficient development is influenced by the connectivity between fracture–cavity units within the reservoir. These reservoirs primarily consist of large caves, dissolution holes, and natural fractures, which serve as the primary storage and flow spaces. The S91 unit of the Tarim Oilfield is a karstic fracture–cavity reservoir with shallow coverage. It exhibits significant heterogeneity in the fracture–cavity reservoirs and presents complex connectivity between the fracture–cavity bodies. The integration of static and dynamic data, including geology, well logging, seismic, and production dynamics, resulted in the development of a set of static and dynamic connectivity evaluation processes designed for highly heterogeneous fracture–cavity reservoirs. Methods include using structural gradient tensors and stratigraphic continuity attributes to delineate the boundaries of caves and holes; performing RGB fusion analysis of coherence, curvature, and variance attributes to characterize large-scale fault development features; applying ant-tracking algorithms and fracture simulation techniques to identify the distribution and density characteristics of fracture zones; utilizing 3D visualization technology to describe the spatial relationship between fracture–cavity units and large-scale faults and fracture development zones; and combining dynamic data to verify interwell connectivity. This process will provide a key geological basis for optimizing well network deployment, improving water and gas injection efficiency, predicting residual oil distribution, and formulating adjustment measures, thereby improving the development efficiency of such complex reservoirs. Full article

(This article belongs to the Special Issue Advances in Geophysical Exploration)

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22 pages, 8314 KB

Open AccessArticle

Efficient Three-Dimensional Marine Controlled-Source Electromagnetic Modeling Using Coordinate Transformations and Adaptive High-Order Finite Elements

by Feiyan Wang and Song Cheng

Appl. Sci. 2025, 15(17), 9626; https://doi.org/10.3390/app15179626 - 1 Sep 2025

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Abstract

Efficient and accurate forward modeling of electromagnetic fields is essential for advancing geophysical exploration in complex marine environments. However, realistic survey conditions characterized by low-frequency spectra, fine sedimentary strata, irregular bathymetry, and anisotropic materials pose significant challenges for conventional numerical methods. To address [...] Read more.

Efficient and accurate forward modeling of electromagnetic fields is essential for advancing geophysical exploration in complex marine environments. However, realistic survey conditions characterized by low-frequency spectra, fine sedimentary strata, irregular bathymetry, and anisotropic materials pose significant challenges for conventional numerical methods. To address these issues, this work presents a parallel modeling framework that combines coordinate transformations with an adaptive high-order finite-element approach for 3D marine controlled-source electromagnetic (MCSEM) simulations. The algorithm exploits the form invariance of Maxwell’s equations to map the original boundary value problem over the physical domain to one defined over a computationally favorable domain filled with anisotropic media. The transformed model is then discretized and solved using a parallel high-order finite-element scheme enhanced with a goal-oriented adaptive mesh refinement strategy. We examine the performance of the proposed framework using both synthetic models and the realistic Marlim R3D benchmark dataset. The results demonstrate that the proposed approach can effectively reduce computational costs while maintaining high accuracy across a wide frequency range and varying water depths. These findings highlight the framework’s potential for large-scale, high-resolution CSEM exploration of offshore resources. Full article

(This article belongs to the Special Issue Advances in Geophysical Exploration)

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17 pages, 3606 KB

Open AccessArticle

Kalman–FIR Fusion Filtering for High-Dynamic Airborne Gravimetry: Implementation and Noise Suppression on the GIPS-1A System

by Guanxin Wang, Shengqing Xiong, Fang Yan, Feng Luo, Linfei Wang and Xihua Zhou

Appl. Sci. 2025, 15(17), 9363; https://doi.org/10.3390/app15179363 - 26 Aug 2025

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Abstract

High-dynamic airborne gravimetry faces critical challenges from platform-induced noise contamination. Conventional filtering methods exhibit inherent limitations in simultaneously achieving dynamic tracking capability and spectral fidelity. To overcome these constraints, this study proposes a Kalman–FIR fusion filtering (K-F) method, which is validated through engineering [...] Read more.

High-dynamic airborne gravimetry faces critical challenges from platform-induced noise contamination. Conventional filtering methods exhibit inherent limitations in simultaneously achieving dynamic tracking capability and spectral fidelity. To overcome these constraints, this study proposes a Kalman–FIR fusion filtering (K-F) method, which is validated through engineering implementation on the GIPS-1A airborne gravimeter platform. The proposed framework employs a dual-stage strategy: (1) An adaptive state-space framework employing calibration coefficients (S_x, S_y, S_z) continuously estimates triaxial acceleration errors to compensate for gravity anomaly signals. This approach resolves aliasing artifacts induced by non-stationary noise while preserving low-frequency gravity components that are traditionally attenuated by conventional FIR filters. (2) A window-optimized FIR post-filter explicitly regulates cutoff frequencies to ensure spectral compatibility with downstream processing workflows, including terrain correction. Flight experiments demonstrate that the K-F method achieves a repeat-line internal consistency of 0.558 mGal at 0.01 Hz—a 65.3% accuracy improvement over standalone FIR filtering (1.606 mGal at 0.01 Hz). Concurrently, it enhances spatial resolution to 2.5 km (half-wavelength), enabling the recovery of data segments corrupted by airflow disturbances that were previously unusable. Implemented on the GIPS-1A system, K-F enables precision mineral exploration and establishes a noise-suppressed paradigm for extreme-dynamic gravimetry. Full article

(This article belongs to the Special Issue Advances in Geophysical Exploration)

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18 pages, 31746 KB

Open AccessArticle

Analysis of the Genetic Mechanism of Thermal Anomaly in the A’nan Sag, Erlian Basin Based on 3D Magnetotelluric Imaging

by Sen Wang, Wei Xu, Tianqi Guo, Wentao Duan and Zhaoyun Wang

Appl. Sci. 2025, 15(16), 9085; https://doi.org/10.3390/app15169085 - 18 Aug 2025

Viewed by 374

Abstract

This study focuses on the genesis mechanism of thermal anomalies in the southwestern part of the Anan Depression in the Erlian Basin. Based on magnetotelluric 3D inversion data, a high-resolution electrical resistivity structure model was constructed, revealing the spatial configuration of deep heat [...] Read more.

This study focuses on the genesis mechanism of thermal anomalies in the southwestern part of the Anan Depression in the Erlian Basin. Based on magnetotelluric 3D inversion data, a high-resolution electrical resistivity structure model was constructed, revealing the spatial configuration of deep heat sources and thermal pathways. The main conclusions are as follows: (1) Magnetotelluric 3D imaging reveals an elliptical low-resistivity anomaly (Anomaly C: 20 km × 16 km × 5 km, 0–5 Ωm) at depths of ~10–15 km. This anomaly is interpreted as a hypersaline fluid (approximately 400 °C, ~1.5% volume fraction, 3–5 wt.% NaCl), acting as the primary heat source. (2) Upward migration along F1/F3 fault conduits (10–40 Ωm) establishes a continuous pathway to mid-depth reservoirs D1/D2 (~5 km, 5–10 Ωm) and shallow crust. An overlying high-resistivity caprock (40–100 Ωm) seals thermal energy, forming a convective “source-conduit-reservoir-cap” system. (3) Integrated seismic data reveal that heat from the Abaga volcanic melt supplements Anomaly C via conduction through these conduits, combining with mantle-derived heat to form a composite source. This research delineates the interacting genesis mechanism of “deep low-resistivity heat source—medium-low resistivity fault conduit—shallow low-resistivity reservoir—relatively high-resistivity cap rock” in the southwestern A’nan Sag, providing a scientific basis for optimizing geothermal exploration targets and assessing resource potential. Full article

(This article belongs to the Special Issue Advances in Geophysical Exploration)

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26 pages, 15575 KB

Open AccessArticle

A Scalable and Consistent Method for Multi-Component Gravity-Gradient Data Processing

by Larissa Silva Piauilino, Vanderlei Coelho Oliveira Junior and Valeria Cristina Ferreira Barbosa

Appl. Sci. 2025, 15(15), 8396; https://doi.org/10.3390/app15158396 - 29 Jul 2025

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Abstract

We demonstrate the potential of using the convolutional equivalent layer to jointly process large gravity-gradient datasets. Based on the equivalent-layer principle, we assume a single fictitious physical property distribution on a planar layer can approximate all components of the gravity-gradient tensor. Estimating this [...] Read more.

We demonstrate the potential of using the convolutional equivalent layer to jointly process large gravity-gradient datasets. Based on the equivalent-layer principle, we assume a single fictitious physical property distribution on a planar layer can approximate all components of the gravity-gradient tensor. Estimating this distribution using the classical technique ensures physical consistency among components. However, the classical approach becomes computationally prohibitive for large datasets due to the need to solve a large-scale inversion with a massive sensitivity matrix. To overcome this limitation, we exploit the block-Toeplitz Toeplitz-block structure of the sensitivity matrix for data on a regular horizontal grid. This structure significantly reduces computational cost—by orders of magnitude—compared to the classical method. Applications to synthetic and real datasets show that our method offers a computationally efficient alternative for processing large gravity-gradient data from various acquisition systems (AGG and FTG), even when data are irregularly spaced or flight lines are misaligned. On a standard laptop configuration, our method processed over 290,000 AGG data points in a few tens of seconds. It also handled between 726,000 FTG and 1,250,000 AGG data points within seconds to a couple of minutes, demonstrating practical computational efficiency for large-scale datasets. Full article

(This article belongs to the Special Issue Advances in Geophysical Exploration)

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20 pages, 5976 KB

Open AccessArticle

An Aeromagnetic Compensation Algorithm Based on a Temporal Convolutional Network

by Han Wang and Boxin Zuo

Appl. Sci. 2025, 15(6), 3105; https://doi.org/10.3390/app15063105 - 13 Mar 2025

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Abstract

Aeromagnetic compensation is the main method for eliminating magnetic interference on flight platforms. With the improved sensitivity of aeromagnetic sensors, the generalization and compensation accuracy of existing aeromagnetic compensation methods have become insufficient to meet the needs of current aeromagnetic survey applications. In [...] Read more.

Aeromagnetic compensation is the main method for eliminating magnetic interference on flight platforms. With the improved sensitivity of aeromagnetic sensors, the generalization and compensation accuracy of existing aeromagnetic compensation methods have become insufficient to meet the needs of current aeromagnetic survey applications. In this article, we propose an aeromagnetic compensation method based on temporal convolutional networks to improve both generalization and compensation accuracy. In the proposed method, a neural network based on separable convolution with a residual connection is employed to improve the compensation accuracy and convergence stability, and a gradient correction loss function based on the Tolles–Lawson model is used to improve the generalization ability. We conducted experiments based on both simulated and real datasets and compared typical neural network compensation methods proposed by previous researchers. The results indicate that the method proposed in this article can achieve a lower standard deviation of residual magnetic interference than other neural network methods, demonstrating a better compensation performance and generalization ability. Full article

(This article belongs to the Special Issue Advances in Geophysical Exploration)

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21 pages, 7184 KB

Open AccessArticle

Susceptibility and Remanent Magnetization Estimates from Orientation Tools in Borehole Imaging Logs

by Julio Cesar S. O. Lyrio, Ana Patrícia C. C. Laier, Jorge Campos Junior, Ana Natalia G. Rodrigues and Luciano dos Santos Martins

Appl. Sci. 2025, 15(5), 2873; https://doi.org/10.3390/app15052873 - 6 Mar 2025

Viewed by 1114

Abstract

Orientation tools in borehole imaging logs acquire magnetic information that is currently used for spatial and geographical orientation of the images. We propose to use this magnetic field information to estimate both magnetic susceptibility and remanent magnetization of rocks inside wells. Measurements of [...] Read more.

Orientation tools in borehole imaging logs acquire magnetic information that is currently used for spatial and geographical orientation of the images. We propose to use this magnetic field information to estimate both magnetic susceptibility and remanent magnetization of rocks inside wells. Measurements of these magnetic parameters are not often available in hydrocarbon exploration to support forward modeling of magnetic data, an interpretation tool that has played important role in the exploration risk reduction in the Pre-Salt prospects of Campos Basin, Brazil. The acquired magnetic data requires corrections for tool rotation and diurnal variation of the Earth’s magnetic field before calculation. Then, using a set of simple equations and reasonable assumptions we were able to estimate the magnetic susceptibility of carbonates and basalts, as well as the remanent magnetization of the basalts, from a Pre-Salt well in Campos Basin. When compared to susceptibility values measured in laboratory for the same rock interval, our results show a significant match. This promising result shows the importance of our methodology in providing reliable information that can minimize uncertainties in forward modeling of magnetic data, which contributes to reduction of hydrocarbon exploration risks. Given that direct susceptibility and remanence measurements require oriented samples, a complex and expensive operation in wells, our results offer this rock information without any extra costs since imaging logs are commonly acquired in exploration wells. Besides its use in hydrocarbon exploration, our methodology can be applied to mineral exploration where magnetic susceptibility is an important property for rock identification. Full article

(This article belongs to the Special Issue Advances in Geophysical Exploration)

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13 pages, 12552 KB

Open AccessArticle

Inversion of Elastic and Fracture Parameters in Tilted Transverse Isotropic Media with Parameter Standardization

by Guangzhi Zhang, Shengzhao Dai, Han Li, Hongjian Hao and Tengfei Chen

Appl. Sci. 2025, 15(5), 2792; https://doi.org/10.3390/app15052792 - 5 Mar 2025

Viewed by 629

Abstract

This study addresses inversion challenges in tilted transverse isotropic (TTI) media affected by inclined fractures. A new method is proposed to derive the reflection coefficient for such media, combining scattering theory with the steady-phase method. To enhance inversion accuracy and stability, a scale [...] Read more.

This study addresses inversion challenges in tilted transverse isotropic (TTI) media affected by inclined fractures. A new method is proposed to derive the reflection coefficient for such media, combining scattering theory with the steady-phase method. To enhance inversion accuracy and stability, a scale normalization technique is introduced. The approach improves parameter consistency during the inversion process. The results highlight the potential of this method to offer valuable technical support for fractured reservoir exploration and development. Full article

(This article belongs to the Special Issue Advances in Geophysical Exploration)

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25 pages, 8652 KB

Open AccessArticle

Seismic Prediction of Porosity in the Norne Field: Utilizing Support Vector Regression and Empirical Models Driven by Bayesian Linearized Inversion

by Jorge A. Teruya Monroe, Jose J. S. de Figueiredo and Carlos E. S. Amanajas

Appl. Sci. 2025, 15(2), 616; https://doi.org/10.3390/app15020616 - 10 Jan 2025

Viewed by 874

Abstract

This work aims to improve the characterization of petrophysical properties by accurately estimating subsurface porosity using seismic and well data. The study includes Bayesian Linearized Inversion to obtain elastic parameters (e.g., compressional e shear wave velocities and densities). This reduces processing uncertainty and [...] Read more.

This work aims to improve the characterization of petrophysical properties by accurately estimating subsurface porosity using seismic and well data. The study includes Bayesian Linearized Inversion to obtain elastic parameters (e.g., compressional e shear wave velocities and densities). This reduces processing uncertainty and provides a reliable substitute for the standard Amplitude versus Offset inversion method. Furthermore, incorporating sparse spike wavelets with Bayesian Linearized Inversion refines the inversion output, facilitating the extraction of petrophysical properties. Combined with log data from seventeen wells, these inverted parameters serve as inputs for two porosity prediction models: the empirical Han’s equation and a more adaptable Support Vector Regression model, the latter demonstrating superior precision in most cases due to its flexible fitting and calibration capabilities. Results from the Norne field in the North Sea confirm the approach’s viability, with the Support Vector Regression model achieving a significant Pearson correlation coefficient of 90% in porosity prediction, underscoring the potential of machine learning techniques in improving subsurface exploration results. Full article

(This article belongs to the Special Issue Advances in Geophysical Exploration)

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17 pages, 7747 KB

Open AccessArticle

Three-Dimensional Forward Modeling and Inversion Study of Transient Electromagnetic Method Considering Inhomogeneous Magnetic Permeability

by Chenyu Wang, Yan Dong, Jingyu Gao, Handong Tan, Yingge Wang and Weiyu Dong

Appl. Sci. 2024, 14(24), 11660; https://doi.org/10.3390/app142411660 - 13 Dec 2024

Viewed by 1074

Abstract

Traditional studies on Transient Electromagnetic Method (TEM) typically assume that the subsurface medium is non-magnetic. However, in regions with igneous rock accumulations or where the subsurface is rich in ferromagnetic minerals, neglecting the magnetic properties of the underground medium may lead to erroneous [...] Read more.

Traditional studies on Transient Electromagnetic Method (TEM) typically assume that the subsurface medium is non-magnetic. However, in regions with igneous rock accumulations or where the subsurface is rich in ferromagnetic minerals, neglecting the magnetic properties of the underground medium may lead to erroneous interpretations for TEM data. This paper conducts a 3-D TEM forward modeling and inversion study considering the non-uniformity cases of magnetic permeability. 3-D TEM forward modeling employs an edge-based finite element method using unstructured grids and a second-order implicit backward Euler method, achieving a modeling algorithm that simultaneously considers non-uniform models of magnetic permeability and resis-tivity. The accuracy of the modeling algorithm is verified by comparing it with the analytical solution of a homogeneous half-space model and the solution of a 1-D TEM forward modeling algorithm. 3-D TEM inversion employs the L-BFGS algorithm and synthetic examples considering non-uniform magnetic permeability are presented. The inversion results show good recovery for the resistivity and magnetic permeability models. Comparisons with the inversion results that neglect the non-uniformity of magnetic permeability validate the importance of considering the variation of permeability in 3-D TEM forward modeling and inversion. Full article

(This article belongs to the Special Issue Advances in Geophysical Exploration)

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22 pages, 15600 KB

Open AccessArticle

Modeling of Characteristics of Complex Microstructure and Heterogeneity at the Core Scale

by Yiwei Chen and Pingchuan Dong

Appl. Sci. 2024, 14(23), 11385; https://doi.org/10.3390/app142311385 - 6 Dec 2024

Viewed by 876

Abstract

Complex pore structures and strong matrix heterogeneity distinguish carbonate rocks, but there is a lack of comprehensive methods to describe these characteristics. In this study, a integrated approach is proposed to improve the accuracy and adaptability of velocity prediction methods, using a modified [...] Read more.

Complex pore structures and strong matrix heterogeneity distinguish carbonate rocks, but there is a lack of comprehensive methods to describe these characteristics. In this study, a integrated approach is proposed to improve the accuracy and adaptability of velocity prediction methods, using a modified squirt flow model based on microcrack structures to characterize complicated pore structures, and a mixed random medium model to represent significant heterogeneity. In addition, the microcrack structure is obtained by inversion, but different from the D-Z method, each group of microcracks corresponds to a different equivalent medium model, so as to improve the accuracy of the inversion results. And the modified squirt flow model takes into account the attenuation caused by local flow between microcracks. The random medium model simulates the inhomogeneous body in the core by adjusting the autocorrelation length a and b, the rounding coefficient n, and the angle

θ

. A comparative study of the measured data of five limestone and dolomite samples reveals that the P-wave prediction error of the new model is less than 5%, whereas the Biot model is less than 10%, implying that the prediction accuracy of the new model is better. Full article

(This article belongs to the Special Issue Advances in Geophysical Exploration)

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17 pages, 14845 KB

Open AccessArticle

Spatially Constrained 1D Inversions of Common-Midpoint Marine Controlled-Source Electromagnetic Data to Create a 3D Electrical Model

by Jorlivan Lopes Correa and Cícero Régis

Appl. Sci. 2024, 14(23), 11281; https://doi.org/10.3390/app142311281 - 3 Dec 2024

Viewed by 1015

Abstract

The proposed 3D stitching of spatially constrained Common Midpoint (CMP) 1D inversions is a method that integrates 1D laterally constrained inversion of marine Controlled-Source Electromagnetic (CSEM) data in the CMP domain to generate a cube of resistivities from 3D surveys. An interpretive model [...] Read more.

The proposed 3D stitching of spatially constrained Common Midpoint (CMP) 1D inversions is a method that integrates 1D laterally constrained inversion of marine Controlled-Source Electromagnetic (CSEM) data in the CMP domain to generate a cube of resistivities from 3D surveys. An interpretive model is built in the form of a set of columns of homogeneous cells that form a 3D resistivity grid. The proposed methodology is an iterative process that updates the entire model until it minimizes the data misfit between the real and synthetic data. We connect the model cells by smoothing regularization applied in all three directions, which generates stable solutions. Additionally, we evaluate the inversion result constrained by hard information, for example, well log resistivity data. Two applications to synthetic data and the inversion of a real data set illustrate the method. The synthetic data were generated from 3D models, one with two resistive targets at different depths and a second with a target inside a conductive layer over a resistive basement. The real data were gathered off the southeast coast of Brazil, in an area of gas hydrate accumulation. The results indicate that the method can generate useful approximations to the resistivity structures under the survey area in a much shorter time than that of a full 3D inversion. Full article

(This article belongs to the Special Issue Advances in Geophysical Exploration)

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19 pages, 1900 KB

Open AccessArticle

CSEM Optimization Using the Correspondence Principle

by Adriany Valente, Deivid Nascimento and Jessé Costa

Appl. Sci. 2024, 14(19), 8846; https://doi.org/10.3390/app14198846 - 1 Oct 2024

Viewed by 961

Abstract

Traditionally, 3D modeling of marine controlled-source electromagnetic (CSEM) data (in the frequency domain) involves high-memory demand, requiring solving a large linear system for each frequency. To address this problem, we propose to solve Maxwell’s equations in a fictitious dielectric medium with time-domain finite-difference [...] Read more.

Traditionally, 3D modeling of marine controlled-source electromagnetic (CSEM) data (in the frequency domain) involves high-memory demand, requiring solving a large linear system for each frequency. To address this problem, we propose to solve Maxwell’s equations in a fictitious dielectric medium with time-domain finite-difference methods, with the support of the correspondence principle. As an advantage of this approach, we highlight the possibility of its implementation for execution with GPU accelerators, in addition to multi-frequency data modeling with a single simulation. Furthermore, we explore using the correspondence principle to the inversion of CSEM data by calculating the gradient of the least-squares objective function employing the adjoint-state method to establish the relationship between adjoint fields in a conductive medium and their counterparts in the fictitious dielectric medium, similar to the approach used in forward modeling. We validate this method through 2D inversions of three synthetic CSEM datasets, computed for a simple model consisting of two resistors in a conductive medium, a model adapted from a CSEM modeling and inversion package, and the last one based on a reference model of turbidite reservoirs on the Brazilian continental margin. We also evaluate the differences between the results of inversions using the steepest descent method and our proposed momentum method, comparing them with the limited-memory BFGS (Broyden–Fletcher–Goldfarb–Shanno) algorithm (L-BFGS-B). In all experiments, we use smoothing by model reparameterization as a strategy for regularizing and stabilizing the iterations throughout the inversions. The results indicate that, although it requires more iterations, our modified momentum method produces the best models, which are consistent with results from the L-BFGS-B algorithm and require less storage per iteration. Full article

(This article belongs to the Special Issue Advances in Geophysical Exploration)

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16 pages, 13178 KB

Open AccessArticle

Testing the Efficacy of Indirect Methods on Characterization of Sedimentary Basins by Correlation of Direct Data and Geophysical Techniques

by Javier Rey, Rosendo Mendoza, M. Carmen Hidalgo and Bruna Marinho

Appl. Sci. 2024, 14(16), 7308; https://doi.org/10.3390/app14167308 - 19 Aug 2024

Cited by 2 | Viewed by 1411

Abstract

The information obtained from direct data (geological mapping and boreholes) and indirect techniques (reflection seismology, time-domain electromagnetics and magnetometry) is combined to analyse the northern limit of the Bailén basin (southeastern Spain). This Triassic–Neogene basin is confined by a graben-type structure, limited by [...] Read more.

The information obtained from direct data (geological mapping and boreholes) and indirect techniques (reflection seismology, time-domain electromagnetics and magnetometry) is combined to analyse the northern limit of the Bailén basin (southeastern Spain). This Triassic–Neogene basin is confined by a graben-type structure, limited by two normal faults in the SW–NE direction (the Baños de la Encina-La Carolina fault and Guarromán fault). The movement of these faults was complex, with different pulses occurring over time. Therefore, the subsidence of the basin and the sedimentary filling of the graben were different, giving rise to lateral changes in the facies and thicknesses. This study focuses on the Baños de la Encina fault, chosen as the experimental site to analyse the effectiveness and accuracy of these geophysical techniques to reveal the basement structure and geometry. Seismic reflection allows to detect two faults that caused the subsidence of the eastern sector of the graben. The TDEM method made it possible to calculate the depth of the Palaeozoic basement, as well as reveal the presence of the two aforementioned faults. Magnetic total field data highlight variations in the basement depth that can be used to infer previously unknown fractures, in this case, in the NW–SE direction. Full article

(This article belongs to the Special Issue Advances in Geophysical Exploration)

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