Seafloor bathymetry in deep and shallow water marine CSEM responses of Nigerian Niger Delta oil field: Effects and corrections

Folorunso, Adetayo Femi; Li, Yuguo

doi:10.1016/j.jappgeo.2015.10.014

Cited by 7 publications

(1 citation statement)

References 22 publications

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“…To compute the EM fields in the virtual receivers, Stratton-Chu type integral transformation was used in the research study. Next, 2.5-D FE method was used by researchers in Reference [19] as its forward modeling code for marine CSEM application in Niger Delta. Adaptive FE method has been known as a robust numerical modeling approach in complex environment.…”

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%