Search Results (28)

The marine controlled-source electromagnetic (CSEM) method serves as an effective tool for detecting hydrocarbon reservoirs. However, it faces a key challenge in shallow water: the airwave, an EM signal lacking subsurface information, often obscures reservoir responses. Conventional CSEM analysis, conducted in the diffusive frequency domain (DFD), only captures the steady-state behavior of the airwave, limiting physical insight into its propagation. In this study, we introduce the fictitious wave domain (FWD) method to reinterpret and visualize the airwaves’ trajectory and attenuation, individually. By transforming diffusive EM fields into fictitious lossless propagating waves, the FWD enables the use of kinematic wave concepts such as reflection, refraction, and travel time. The airwave is clearly identified as a refracted wave generated when a transverse electromagnetic (TEM) mode wave impinges perpendicularly on the air–seawater interface. Its path and arrival time become directly observable, allowing clear separation from other wave types. This approach visualizes and extracts the airwave even in complex inhomogeneous seawater, enabling its accurate transformation back to the DFD. The FWD thus provides a powerful tool for enhancing interpretation in marine EM exploration and offers a theoretical foundation for the development of tailored marine electromagnetic sensors. Full article

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 study presents the first application of a deep-towed transmitter–receiver marine controlled-source electromagnetic (TTR-MCSEM) system for gas hydrate exploration in the Shenhu area of the South China Sea. High-resolution electromagnetic data were acquired along a 13 km transect using dynamic source–receiver offsets and a 500 A transmitter. The results reveal the following: (1) unprecedented near-seafloor resolution (20~100 m) for the precise delineation of hydrate-bearing caprock, surpassing conventional ocean-bottom electromagnetic systems; (2) laterally continuous high-resistivity anomalies (~10 Ω·m) extending from the base of the gas hydrate stability zone to the seafloor, which correlate with seismic bottom-simulating reflector (BSR) distributions and suggest heterogeneous hydrate saturation; and (3) fault-controlled fluid migration pathways that supply hydrate reservoirs and lead to seabed methane seepage at structural highs. Through 2D inversion, we show that the inverted resistivity values (~10 Ω·m) are slightly higher than those obtained from resistivity logs (~5 Ω·m). Saturation values derived from inverted resistivity exhibit remarkable consistency with well-log-based measurements. The high efficiency of the system confirms its potential for the transformative quantitative assessment of hydrate systems, seafloor massive sulfides, and marine geohazards. Full article

The frequency-domain controlled-source electromagnetic method (CSEM) has been widely used in fields such as oil and gas and mineral resource exploration. In areas with a significant IP response, the CSEM signals will be modified by the IP response of the subsurface. Accurately extracting resistivity and polarization information from CSEM signals may significantly improve the exploration interpretations. In this study, we replaced real resistivity with the Cole–Cole complex resistivity model in a forward simulation of the CSEM to obtain electric field responses that included both induced polarization and electromagnetic effects. Based on this, we used the adaptive differential evolution algorithm to perform a 1-d inversion of these data to extract both the resistivity and IP parameters. Inversion of the electric field responses from representative three-layer geoelectric models, as well as from a more realistic seven-layer model, showed that the inversions were able to effectively recover resistivity and polarization information from the modeled responses, validating our methodology. The electric field response of the real geoelectric model, with 20% random noise added, was then used to simulate actual measured CSEM signals, as well as subjected to multiple inversion tests. The results of these tests continued to accurately reflect the resistivity and polarization information of the model, confirming the applicability and reliability of the algorithm. These results have significant implications for the processing and interpretation of CSEM data when induced polarization effects merit consideration and are expected to promote the use of the CSEM in more fields. Full article

Controlled-source electromagnetic method (CSEM), as a significant geophysical exploration technique, plays a crucial role in imaging subsurface structures. To enhance the accuracy and efficiency of CSEM simulations, this paper introduces a 3D unstructured vector finite element numerical simulation method based on the third-type boundary condition. Vector finite elements are particularly suitable for handling discontinuities in the electric field normal. They automatically satisfy tangential field continuity and zero-divergence requirements, providing a solid foundation for forward modeling in the CSEM. The adoption of the third-type boundary condition aims to reduce computational scale while ensuring higher simulation accuracy. Using this method, we conducted detailed numerical simulations on various models, including layered models, single-anomaly models, composite-anomaly models, and layered-anomaly models. The experimental results demonstrate that the algorithm accurately reproduces the electromagnetic responses of various geological models. It also exhibits superior computational accuracy under low-frequency conditions, outperforming traditional simulation methods. In summary, the 3D unstructured vector finite element numerical simulation method proposed in this study offers an efficient and reliable solution for CSEM, which is of great significance for advancing CSEM technology, especially in inversion techniques and data interpretation. Future work will focus on further optimizing algorithm performance and exploring its application potential in complex geological environments. Full article

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

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

Bayan Obo is a well-known polymetallic deposit containing significant quantities of rare earth elements, niobium, thorium, and iron. However, the epoch in which mineralization occurred and the mineralization process are still debated due to the complex nature of its mineralization and geological evolution. Inadequate geophysical exploration has further contributed to this lack of clarity surrounding critical issues, such as the deep link between the main orebody and the eastern orebody, the form and distribution of the extensive dolomite, and the geologic structures in the area. Therefore, we implemented the time-domain controlled-source electromagnetic method (CSEM) to acquire electrical structures at depths down to 2.5 km between the Main and Eastern mines. According to the inverted resistivity structure, in conjunction with existing geological and drilling data, we classified the main lithologies and faults based on their resistivity characteristics. Overall, the mineralized carbonatite reflects high to moderately high resistivity. The mineralized carbonatite dips overall from north to south, with a maximum extension depth not exceeding 1.5 km, and its range of occurrence is controlled by nearly east–west-striking faults distributed along the bounding line between the roof and floor rocks. The Main and Eastern mines are connected at depth, but the morphology and position of the ore bodies have significantly changed due to multiple phases of tectonic activity. The electrical structure does not reveal any obvious syncline structures, further refuting the traditional view that the Bayan syncline controls ore formation. Full article

The Controlled-Source ElectroMagnetic (CSEM) method provides crucial information about reservoir fluids and their spatial distribution. Carbon dioxide (CO₂) storage, enhanced oil recovery (EOR), geothermal exploration, and lithium exploration are ideal applications for the CSEM method. The versatility of CSEM permits its customization to specific reservoir objectives by selecting the appropriate components of a multi-component system. To effectively tailor the CSEM approach, it is essential to determine whether the primary target reservoir is resistive or conductive. This task is relatively straightforward in CO₂ monitoring, where the injected fluid is resistive. However, for scenarios involving brine-saturated (water-wet) or oil-wet (carbon capture, utilization, and storage—CCUS) reservoirs, consideration must also be given to conductive reservoir components. The optimization of data acquisition before the survey involves analyzing target parameters and the sensitivity of multi-component CSEM. This optimization process typically includes on-site noise measurements and 3D anisotropic modeling. Based on our experience, subsequent surveys tend to proceed smoothly, yielding robust measurements that align with scientific objectives. Other critical aspects to be considered are using magnetotelluric (MT) measurements to define the overall background resistivities and integrating real-time quality assurance during data acquisition with 3D modeling. This integration allows the fine tuning of acquisition parameters such as acquisition time and necessary repeats. As a result, data can be examined in real-time to assess subsurface information content while the acquisition is ongoing. Consequently, high-quality data sets are usually obtained for subsequent processing and initial interpretation with minimal user intervention. The implementation of sensitivity analysis during the inversion process plays a pivotal role in ensuring that the acquired data accurately respond to the target reservoirs’ expected depth range. To elucidate these concepts, we present an illustrative example from a CO₂ storage site in North Dakota, USA, wherein the long-offset transient electromagnetic method (LOTEM), a variation of the CSEM method, and the MT method were utilized. This example showcases how surface measurements attain appropriately upscaled log-scale sensitivity. Furthermore, the sensitivity of the CSEM and MT methods was examined in other case histories, where the target reservoirs exhibited conductive properties, such as those encountered in enhanced oil recovery (EOR), geothermal, and lithium exploration applications. The same equipment specifications were utilized for CSEM and MT surveys across all case studies. Full article

To overcome the interference of noise on the exploration effectiveness of the controlled-source electromagnetic method (CSEM), we improved the deep learning algorithm by combining the denoising convolutional neural network (DnCNN) with the residual network (ResNet), and propose a method based on the residual denoising convolutional neural network (ResDnCNN) and shift-invariant sparse coding (SISC) for denoising CSEM data. Firstly, a sample library was constructed by adding simulated noises of different types and amplitudes to high-quality CSEM data collected. Then, the sample library was used for model training in the ResDnCNN, resulting in a network model specifically designed for denoising CSEM data. Subsequently, the trained model was employed to denoise the measured data, generating preliminary denoised data. Finally, the preliminary denoised data was processed using SISC to obtain the final denoised high-quality data. Comparative experiments with the ResNet, DnCNN, U-Net, and long short-term memory (LSTM) networks demonstrated the significant advantages of our proposed method. It effectively removed strong noise such as Gaussian, impulse, and square wave, resulting in an improvement of the signal-to-noise ratio by nearly 20 dB. Testing on CSEM data from Sichuan Province, China, showed that the apparent resistivity curves plotted using our method were smoother and more credible. Full article

Tracking temperature changes by measuring the resulting resistivity changes inside low-enthalpy reservoirs is crucial to avoid early thermal breakthroughs and maintain sustainable energy production. The controlled-source electromagnetic method (CSEM) allows for the estimation of sub-surface resistivity. However, it has not yet been proven that the CSEM can monitor the subtle resistivity changes typical of low-enthalpy reservoirs. In this paper, we present a feasibility study considering the CSEM monitoring of 4–8 $\Omega ·$m resistivity changes in a deep low-enthalpy reservoir model, as part of the Delft University of Technology (TU Delft) campus geothermal project. We consider the use of a surface-to-borehole CSEM for the detection of resistivity changes in a simplified model of the TU Delft campus reservoir. We investigate the sensitivity of CSEM data to disk-shaped resistivity changes with a radius of 300, 600, 900, or 1200 m at return temperatures equal to 25, 30, …, 50 °C. We test the robustness of CSEM monitoring against various undesired effects, such as random noise, survey repeatability errors, and steel-cased wells. The modelled differences in the electric field suggest that they are sufficient for the successful CSEM detection of resistivity changes in the low-enthalpy reservoir. The difference in monitoring data increases when increasing the resistivity change radius from 300 to 1200 m or from 4 to 8 $\Omega ·$m. Furthermore, all considered changes lead to differences that would be detectable in CSEM data impacted by undesired effects. The obtained results indicate that the CSEM could be a promising geophysical tool for the monitoring of small resistivity changes in low-enthalpy reservoirs, which would be beneficial for geothermal energy production. Full article

The marine controlled-source electromagnetic (CSEM) method has been used in different applications, such as oil and gas reservoir exploration, groundwater investigation, seawater intrusion studies and deep-sea mineral exploration. Recently, the utilization of the marine CSEM method has shifted from petroleum exploration to active monitoring due to increased environmental concerns related to hydrocarbon production. In this study, we utilize the various dynamic reservoir properties available through reservoir simulation of the Wisting field in the Norwegian part of the Barents Sea. In detail, we first developed geologically consistent rock physics models corresponding to reservoirs at different production phases, and then transformed them into resistivity models. The constructed resistivity models pertaining to different production phases can be used as input models for a finite difference time domain (FDTD) forward modeling workflow to simulate EM responses. This synthetic CSEM data can be studied and analyzed in the light of production-induced changes in the reservoir at different production phases. Our results demonstrate the ability of CSEM data to detect and capture production-induced changes in the fluid content of a producing hydrocarbon reservoir. The anomalous CSEM responses correlating to the reservoir resistivity change increase with the advance of the production phase, and a similar result is shown in anomalous transverse resistance (ATR) maps derived from the constructed resistivity models. Moreover, the responses at 30 Hz with a 3000 m offset resulted in the most pronounced anomalies at the Wisting reservoir. Hence, the method can effectively be used for production-monitoring purposes. Full article

The marine controlled-source electromagnetic (CSEM) method is an efficient tool for hydrocarbon exploration. The amplitudes of signals decay rapidly with the increasing offset, so signals are easily contaminated by various kinds of noise. A denoising method is critical to improve the data quality, but the diversity of noise makes denoising difficult. Specific frequency signals are transmitted for exploration requirements, and thus traditional filtering methods are not suitable. Symplectic geometry mode decomposition (SGMD), a new method to decompose signals, has an outstanding decomposition performance and noise robustness. Furthermore, it can reduce multiple types of noise by reconstructing the single components. In this study, we introduced SGMD to reduce the noise of marine CSEM data and improved the data quality significantly. The experiments show that SGMD is better than variational mode decomposition and the sym4 wavelet method. Full article

The controlled source electromagnetic (CSEM) method is frequently used as a risk reduction tool in hydrocarbon exploration. This paper aims to provide a comprehensive historical review of the CSEM method’s twenty-year history in the Brazilian continental margin. Since 2003, we have significantly improved our understanding of CSEM resistivity data across various geological scenarios. This review presents a roadmap of the technical advancements in acquisition design and interpretation techniques. As a result, our understanding of the methodology has broadened from traditional to more general use, such as salt imaging, gas hydrates, geohazard mapping, and reservoir characterization. Finally, we indicate the potential upcoming CSEM applications in new energy resources and carbon capture and storage. Full article

The recycling or burial of carbon dioxide in depleted petroleum reservoirs and re-imagining exploration strategies that focus on hydrogen reservoirs (with any associated hydrocarbon gas as the upside potential) are a necessity in today’s environmental and geopolitical climate. Given that geologic hydrogen and hydrocarbon gases may occur in the same or different reservoirs, there will be gains in efficiency when searching for both resources together since they share some commonalities, but there is no geophysical workflow available yet for this purpose. Three-dimensional (3D) marine controlled-source electromagnetic (CSEM) and magnetotelluric (MT) methods provide valuable information on rock-and-fluid variations in the subsurface and can be used to investigate hydrogen and hydrocarbon reservoirs, source rocks, and the migration pathways of contrasting resistivity relative to the host rock. In this paper, a process-oriented CSEM-MT workflow is proposed for the efficient combined investigation of reservoir hydrocarbon and hydrogen within a play-based exploration and production framework that emphasizes carbon footprint reduction. It has the following challenging elements: finding the right basin (and block), selecting the right prospect, drilling the right well, and exploiting the opportunities for sustainability and CO₂ recycling or burial in the appropriate reservoirs. Recent methodological developments that integrate 3D CSEM-MT imaging into the appropriate structural constraints to derive the geologically robust models necessary for resolving these challenges and their extension to reservoir monitoring are described. Instructive case studies are revisited, showing how 3D CSEM-MT models facilitate the interpretation of resistivity information in terms of the key elements of geological prospect evaluation (presence of source rocks, migration and charge, reservoir rock, and trap and seal) and understanding how deep geological processes control the distribution and charging of potential hydrocarbon, geothermal, and hydrogen reservoirs. In particular, evidence is provided that deep crustal resistivity imaging can map serpentinized ultramafic rocks (possible source rocks for hydrogen) in offshore northwest Borneo and can be combined with seismic reflection data to map vertical fluid migration pathways and their barrier (or seal), as exemplified by the subhorizontal detachment zones in Eocene shale in the Mexican Ridges fold belt of the southwest of the Gulf of Mexico, raising the possibility of using integrated geophysical methods to map hydrogen kitchens in different terrains. The methodological advancements and new combined investigative workflow provide a way for improved resource mapping and monitoring and, hence, a technology that could play a critical role in helping the world reach net-zero emissions by 2050. Full article