New advances in three‐dimensional controlled‐source electromagnetic inversion

SUMMARY New techniques for improving both the computational and imaging performance of the three-dimensional (3-D) electromagnetic inverse problem are presented. A non-linear conjugate gradient algorithm is the framework of the inversion scheme. Full wave equation modelling for controlled sources is utilized for data simulation along with an efficient gradient computation approach for the model update. Improving the modelling efficiency of the 3-D finite difference (FD) method involves the separation of the potentially large modelling mesh, defining the set of model parameters, from the computational FD meshes used for field simulation. Grid spacings and thus overall grid sizes can be reduced and optimized according to source frequencies and source–receiver offsets of a given input data set. Further computational efficiency is obtained by combining different levels of parallelization. While the parallel scheme allows for an arbitrarily large number of parallel tasks, the relative amount of message passing is kept constant. Image enhancement is achieved by model parameter transformation functions, which enforce bounded conductivity parameters and thus prevent parameter overshoots. Further, a remedy for treating distorted data within the inversion process is presented. Data distortions simulated here include positioning errors and a highly conductive overburden, hiding the desired target signal. The methods are demonstrated using both synthetic and field data.

[1]  Gregory A. Newman,et al.  Three-dimensional induction logging problems, Part 2: A finite-difference solution , 2002 .

[2]  Gregory A. Newman,et al.  Three‐dimensional massively parallel electromagnetic inversion—I. Theory , 1997 .

[3]  Frances Bauer,et al.  Finite Difference Scheme , 1984 .

[4]  Sofia Davydycheva,et al.  A Finite Difference Scheme for Elliptic Equations with Rough Coefficients Using a Cartesian Grid Nonconforming to Interfaces , 1999 .

[5]  S. T. McDANIEL,et al.  FINITE DIFFERENCE SCHEMES , 1988 .

[6]  R. Pratt Seismic waveform inversion in the frequency domain; Part 1, Theory and verification in a physical scale model , 1999 .

[7]  Paul T. Boggs,et al.  Solution accelerators for large-scale three-dimensional electromagnetic inverse problems : Electromagnetic characterization of buried obstacles , 2004 .

[8]  G. Michael Hoversten,et al.  Marine magnetotellurics for base-of-salt mapping : Gulf of Mexico field test at the Gemini structure , 2000 .

[9]  K. Yee Numerical solution of initial boundary value problems involving maxwell's equations in isotropic media , 1966 .

[10]  Michael Commer,et al.  New results on the resistivity structure of Merapi Volcano (Indonesia), derived from three-dimensional restricted inversion of long-offset transient electromagnetic data , 2006 .

[11]  Paul T. Boggs,et al.  Solution Accelerators For Large-scale 3D Electromagnetic Inverse Problems , 2004 .

[12]  Hans Erik Foss Amundsen,et al.  Subsurface hydrocarbons detected by electromagnetic sounding , 2005 .

[13]  James J. Carazzone,et al.  Three Dimensional Imaging of Marine CSEM Data , 2005 .

[14]  Lucy MacGregor,et al.  Use of marine controlled‐source electromagnetic sounding for sub‐basalt exploration , 2000 .

[15]  Chester J. Weiss,et al.  Mapping thin resistors and hydrocarbons with marine EM methods: Insights from 1D modeling , 2006 .

[16]  Gregory A. Newman,et al.  Solution strategies for two- and three-dimensional electromagnetic inverse problems , 2000 .

[17]  Gregory A. Newman,et al.  3d modeling of a deepwater EM exploration survey , 2006 .

[18]  G. Newman,et al.  Three-dimensional magnetotelluric inversion using non-linear conjugate gradients , 2000 .

[19]  J. Shadid,et al.  Three‐dimensional wideband electromagnetic modeling on massively parallel computers , 1996 .

[20]  E. Haber,et al.  Joint inversion: a structural approach , 1997 .

[21]  S.,et al.  Numerical Solution of Initial Boundary Value Problems Involving Maxwell’s Equations in Isotropic Media , 1966 .

[22]  Chester J. Weiss,et al.  Mapping thin resistors and hydrocarbons with marine EM methods, Part II -Modeling and analysis in 3D , 2006 .

[23]  Tage Røsten,et al.  Integration of Multiple Electromagnetic Imaging And Inversion Techniques For Prospect Evaluation , 2006 .

[24]  Michael Commer,et al.  An accelerated time domain finite difference simulation scheme for three‐dimensional transient electromagnetic modeling using geometric multigrid concepts , 2006 .

[25]  Svein Ellingsrud,et al.  The Meter Reader—Remote sensing of hydrocarbon layers by seabed logging (SBL): Results from a cruise offshore Angola , 2002 .

[26]  Lucy MacGregor,et al.  Sea Bed Logging (SBL), a new method for remote and direct identification of hydrocarbon filled layers in deepwater areas , 2002 .

[27]  Jorge Nocedal Conjugate Gradient Methods and Nonlinear Optimization , 1996 .