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Conditioning of the 3D Marine Controlled Source Electromagnetic Inversion

Andrew Pethick, Brett D. Harris

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Abstract

Three dimensional inversion of Marine Controlled Source Electromagnetic data (MCSEM) data is complex. Achieving an acceptable outcome in a reasonable time frame requires considerable manual input to the problem. We proposed a methodology for preconditioning the inversion for integral equation approximated forward modeller. Both preconditioning of the inversion process and feed-back during the inversion process are used to streamline the overall 3D MCSEM inversion process. We demonstrate the influence each of the components (Ex, Ey, Ez, Hx, Hy and Hz) have on inversion. We demonstrate how preconditioning and iterative analysis of MCSEM data can lead to a more satisfactory result for 3D inversion.

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What this paper is about

Three dimensional inversion of Marine Controlled Source Electromagnetic data (MCSEM) data is complex. Achieving an acceptable outcome in a reasonable time frame requires considerable manual input to the problem. We proposed a methodology for preconditioning the inversion for integral equation approximated forward modeller. Both preconditioning of the inversion process and feed-back during the inversion process are used to streamline the overall 3D MCSEM inversion process. We demonstrate the influence each of the components (Ex, Ey, Ez, Hx, Hy and Hz) have on inversion. We demonstrate how preconditioning and iterative analysis of MCSEM data can lead to a more satisfactory result for 3D inversion.

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Available abstract

Three dimensional inversion of Marine Controlled Source Electromagnetic data (MCSEM) data is complex. Achieving an acceptable outcome in a reasonable time frame requires considerable manual input to the problem. We proposed a methodology for preconditioning the inversion for integral equation approximated forward modeller. Both preconditioning of the inversion process and feed-back during the inversion process are used to streamline the overall 3D MCSEM inversion process. We demonstrate the influence each of the components (Ex, Ey, Ez, Hx, Hy and Hz) have on inversion. We demonstrate how preconditioning and iterative analysis of MCSEM data can lead to a more satisfactory result for 3D inversion.

Key concepts: Inversion (geology), Computer science, Inverse transform sampling, Geology, Algorithm, Seismology, Telecommunications, Tectonics

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