3D Inversion of Large Scale Marine Controlled-Source Electromagnetics. Issue 1 (1st December 2018)

• Record Type: Journal Article
• Authors: Haber, Eldad; McMillan, Mike; Kary, Ben; Marchant, Dave
• Is Part Of: ASEG Extended Abstracts (Online). Volume 2018:Issue 1(2018)
• Page Start: 1
• Page End: 5
• Publication Date: 2018-12-01
• Subjects: Inversion -- Electromagnetics -- Marine; Prospecting -- Geophysical methods -- Periodicals; Prospecting -- Geophysical methods; Periodicals
• DOI: 10.1071/ASEG2018abP071
• Languages: English
• ISSNs: 2202-0586

Abstract

Abstract : Three-dimensional controlled-source electromagnetic (CSEM) surveys can be a useful technique for oil and gas hydrate detection in marine environments. Electromagnetic waves are emitted from sources, and the ensuing electric and/or magnetic fields are recorded at one, or more receivers. The number, frequency, and position of sources and the placement of receivers depends on the particular application. The solution of an inverse problem is required to recover the earth's conductivity, which can be either isotropic or anisotropic in nature. A major issue with either an isotropic or anisotropic CSEM inversion is the computational cost associated with the solution of many linear systems of equations. This is a result of a large spatial domain potentially containing complicated bathymetry, as well as the existence of thousands of source and frequency combinations. Overall, there could be thousands or even millions of systems of equations to solve on expansive meshes. To assist with these numerical issues, we use ideas developed for airborne electromagnetic inversions. First, we incorporate a locally refined mesh for the forward problem, specifically optimized for a source and set of receivers. Second, we use stochastic programming techniques to solve the CSEM problem with many sources and receivers. These methods dramatically reduce the numerical cost of each forward model as well as the total number of simulations. In this work we describe the methods used to overcome these computational difficulties.