Electromagnetic field analysis in the marine CSEM detection of homogeneous and inhomogeneous hydrocarbon 3D reservoirs

Persova, Marina G.; Soloveichik, Yuri G.; Domnikov, Petr A.; Vagin, Denis V.; Koshkina, Yulia I.

doi:10.1016/j.jappgeo.2015.05.019

Cited by 23 publications

(4 citation statements)

References 22 publications

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“…According to Reference [13], the electric and magnetic fields within each element can be approximated by either linear or higher order polynomial functions. Researchers in Reference [17] used 3-D finite element (FE) method to compute the EM responses from the reservoir that consists of a set of resistive hydrocarbons separated by conductors in homogeneous and inhomogeneous environments. The resulting computational experiments showed that the presence of the resistive gaps gave a significant impact on the EM fields recorded by the receivers.…”

Section: Available Methods Used In Processing Csem Datamentioning

confidence: 99%

Stochastic Process-Based Inversion of Electromagnetic Data for Hydrocarbon Resistivity Estimation in Seabed Logging

et al. 2021

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This work proposes a stochastic process-based inversion to estimate hydrocarbon resistivity based on multifrequency electromagnetic (EM) data. Currently, mesh-based algorithms are used for processing the EM responses which cause high time-consuming and unable to quantify uncertainty. Gaussian process (GP) is utilized as the alternative forward modeling approach to evaluate the EM profiles with uncertainty quantification. For the optimization, gradient descent is used to find the optimum by minimizing its loss function. The prior EM profiles are evaluated using finite element (FE) through computer simulation technology (CST) software. For validation purposes, mean squared deviation and its root between EM profiles evaluated by the GP and FE at the unobserved resistivities are computed. Time taken for the GP and CST to evaluate the EM profiles is compared, and absolute error between the estimate and its simulation input is also computed. All the resulting deviations were significantly small, and the GP took lesser time to evaluate the EM profiles compared to the software. The observational datasets also lied within the 95% confidence interval (CI) where the resistivity inputs were estimated by the proposed inversion. This indicates the stochastic process-based inversion can effectively estimate the hydrocarbon resistivity in the seabed logging.

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Section: Available Methods Used In Processing Csem Datamentioning

confidence: 99%

Stochastic Process-Based Inversion of Electromagnetic Data for Hydrocarbon Resistivity Estimation in Seabed Logging

et al. 2021

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“…Besides, it was gradually tested in the natural gas hydrates deposits exploration [11]. Some applications of the marine CSEM method successfully improved the rate of drilling [12,13]. For example, Schwalenberg et al, applied marine CSEM method to the exploration of natural gas hydrate in the offshore waters of New Zealand [14,15].…”

Section: Introductionmentioning

confidence: 99%

Sensitivity and Resolution of Controlled-Source Electromagnetic Method for Gas Hydrate Stable Zone

et al. 2021

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Natural gas hydrate is one of the most important clean energies and part of carbon cycle, due to the least carbon content. Natural gas hydrates depend on high pressure and low temperatures, located under seabed or permafrost. Small changes in temperature and pressure may lead gas hydrates to separate into water and gas, commonly as methane. As a powerful greenhouse gas, methane is much stronger than carbon dioxide. Therefore, it is necessary to detect the gas hydrates stable zone (GHSZ) before the methane gas escapes from GHSZ. Marine controlled source electromagnetic method (CSEM) is a useful tool to detect gas hydrate in offshore. The results from 3D CSEM method are a resistivity cube to describe the distribution of gas hydrates. In order to study the detectability of CSEM method, we simulate the sensitivity and resolution of marine CSEM synthetic data. By using the sensitivity and resolution, a simple statement may be quickly judged on the existence and occurrence range of the natural gas hydrate. In this paper, we compare the resolution of marine CSEM method with various transverse resistance. This information may help researchers find out whether the GHSZ exists or not.

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“…Note that for a medium that is horizontally stratified, the subsurface is generally less resistive in the horizontal (parallel) direction than in the vertical (perpendicular) direction [20]. Offshore hydrocarbon reservoirs are normally embedded in a high conductive medium unlike the common case of onshore hydrocarbon reservoirs [21]. Hydrocarbon-filled reservoirs are known to have very high electrical resistivity compared to its surroundings, such as of saline water and sedimentary rocks.…”

Section: Introductionmentioning

confidence: 99%

Gaussian Process Methodology for Multi-Frequency Marine Controlled-Source Electromagnetic Profile Estimation in Isotropic Medium

et al. 2019

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The marine controlled-source electromagnetic (CSEM) technique is an application of electromagnetic (EM) waves to image the electrical resistivity of the subsurface underneath the seabed. The modeling of marine CSEM is a crucial and time-consuming task due to the complexity of its mathematical equations. Hence, high computational cost is incurred to solve the linear systems, especially for high-dimensional models. Addressing these problems, we propose Gaussian process (GP) calibrated with computer experiment outputs to estimate multi-frequency marine CSEM profiles at various hydrocarbon depths. This methodology utilizes prior information to provide beneficial EM profiles with uncertainty quantification in terms of variance (95% confidence interval). In this paper, prior marine CSEM information was generated through Computer Simulation Technology (CST) software at various observed hydrocarbon depths (250–2750 m with an increment of 250 m each) and different transmission frequencies (0.125, 0.25, and 0.5 Hz). A two-dimensional (2D) forward GP model was developed for every frequency by utilizing the marine CSEM information. From the results, the uncertainty measurement showed that the estimates were close to the mean. For model validation, the calculated root mean square error (RMSE) and coefficient of variation (CV) proved in good agreement between the computer output and the estimated EM profile at unobserved hydrocarbon depths.

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Electromagnetic field analysis in the marine CSEM detection of homogeneous and inhomogeneous hydrocarbon 3D reservoirs

Cited by 23 publications

References 22 publications

Stochastic Process-Based Inversion of Electromagnetic Data for Hydrocarbon Resistivity Estimation in Seabed Logging

Stochastic Process-Based Inversion of Electromagnetic Data for Hydrocarbon Resistivity Estimation in Seabed Logging

Sensitivity and Resolution of Controlled-Source Electromagnetic Method for Gas Hydrate Stable Zone

Gaussian Process Methodology for Multi-Frequency Marine Controlled-Source Electromagnetic Profile Estimation in Isotropic Medium

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