Special Section — Marine Controlled-Source Electromagnetic Methods Rigorous 3D inversion of marine CSEM data based on the integral equation method
Alexander V. Gribenko, Michael S. Zhdanov
Abstract
Alexander V. Gribenko, Michael S. Zhdanov
Abstract
Marine controlled-source electromagneticMCSEMsurveys have become an important part of offshore petroleum exploration. However, due to enormous computational difficultieswithfull3Dinversion,practicalinterpretationofMCSEM data is still a very challenging problem. We present a new approach to 3D inversion of MCSEM data based on rigorous integral-equation IE forward modeling and a new IE representation of the sensitivity Frechet derivative matrix of observed data to variations in sea-bottom conductivity. We develop a new form of the quasi-analytical approximation for models with variable background conductivity QAVBandapplythisformformoreefficientFrechetderivative calculations. This approach requires just one forward modeling on every iteration of the regularized gradient-type inversion algorithm, which speeds up the computations significantly. We also use a regularized focusing inversion method,whichprovidesasharpboundaryimageofthepetroleum reservoir. The methodology is tested on a 3D inversion of the synthetic EM data representing a typical MCSEM surveyconductedforoffshorepetroleumexploration.
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Marine controlled-source electromagneticMCSEMsurveys have become an important part of offshore petroleum exploration. However, due to enormous computational difficultieswithfull3Dinversion,practicalinterpretationofMCSEM data is still a very challenging problem. We present a new approach to 3D inversion of MCSEM data based on rigorous integral-equation IE forward modeling and a new IE representation of the sensitivity Frechet derivative matrix of observed data to variations in sea-bottom conductivity. We develop a new form of the quasi-analytical approximation for models with variable background conductivity QAVBandapplythisformformoreefficientFrechetderivative calculations. This approach requires just one forward modeling on every iteration of the regularized gradient-type inversion algorithm, which speeds up the computations significantly. We also use a regularized focusing inversion method,whichprovidesasharpboundaryimageofthepetroleum reservoir. The methodology is tested on a 3D inversion of the synthetic EM data representing a typical MCSEM surveyconductedforoffshorepetroleumexploration.
Key concepts: Inversion (geology), Computation, Algorithm, Integral equation, Synthetic data, Computer science, Geology, Applied mathematics