Controlled-Source Electromagnetic Data Inversion Using the Model Compression Scheme

We present a model compression scheme for improving the efficiency of the regularized Gauss-Newton inversion algorithm for marine controlled-source electromagnetic applications. In this scheme, the unknown model parameters (the conductivity/resistivity distribution) are represented in terms of a basis such as Fourier, cosine, or wavelet. By applying a proper truncation criterion, the model may then be approximated by a reduced number of basis functions, which is usually much less than the number of the model parameters. Furthermore, because the controlled-source electromagnetic measurements have low resolution, we will show that, for inversion, it is sufficient to only keep the low-spatial-frequency part of the image. This model compression scheme accelerates the computational time as well as reduces the memory usage of the Gauss-Newton method. For demonstration purposes, we show both synthetic and field data inversions. The results show that we are able to significantly reduce the algorithm computational complexity without compromising the quality of the inverted models.

[1]  M. Virgilio,et al.  Simultaneous Joint Inversion of MMT and Seismic Data for Sub-basalt Exploration on the Atlantic Margin, Norway , 2009 .

[2]  Alan D. Chave,et al.  Offshore Electromagnetic Surveying Techniques , 1986 .

[3]  R. N. Edwards,et al.  12. Electrical Exploration Methods for the Seafloor , 1991 .

[4]  Leonard J. Srnka,et al.  Special Section — Marine Controlled-Source Electromagnetic Methods An introduction to marine controlled-source electromagnetic methods for hydrocarbon exploration , 2007 .

[5]  V. Pascazio,et al.  An adaptive wavelet-based approach for non-destructive evaluation applications , 2000, IEEE Antennas and Propagation Society International Symposium. Transmitting Waves of Progress to the Next Millennium. 2000 Digest. Held in conjunction with: USNC/URSI National Radio Science Meeting (C.

[6]  Aria Abubakar,et al.  2.5D forward and inverse modeling for interpreting low-frequency electromagnetic measurements , 2008 .

[7]  M. Zhdanov,et al.  Rigorous 3D inversion of marine CSEM data based on the integral equation method , 2007 .

[8]  Mark E. Everett,et al.  Electric dipole fields over an anisotropic seafloor: theory and application to the structure of 40 ma pacific ocean lithosphere , 1999 .

[9]  René-Édouard Plessix,et al.  Resistivity imaging with controlled-source electromagnetic data: depth and data weighting , 2008 .

[10]  Aria Abubakar,et al.  Hybrid finite-difference integral equation solver for 3D frequency domain anisotropic electromagnetic problems , 2011 .

[11]  Aria Abubakar,et al.  Inversion algorithms for large-scale geophysical electromagnetic measurements , 2009 .

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

[13]  Michael Commer,et al.  New advances in three‐dimensional controlled‐source electromagnetic inversion , 2007 .

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

[15]  P. M. Berg,et al.  Contrast Source Inversion Method: State of Art , 2001 .

[16]  Gene H. Golub,et al.  Matrix computations (3rd ed.) , 1996 .

[17]  A. Abubakar,et al.  A General Framework for Constraint Minimization for the Inversion of Electromagnetic Measurements , 2004 .

[18]  Aria Abubakar,et al.  Joint MT and CSEM data inversion using a multiplicative cost function approach , 2011 .

[19]  P. M. Berg,et al.  Extended contrast source inversion , 1999 .

[20]  Vito Pascazio,et al.  Multiresolution techniques in microwave tomography and subsurface sensing , 1999, IEEE 1999 International Geoscience and Remote Sensing Symposium. IGARSS'99 (Cat. No.99CH36293).

[21]  Trond Mannseth,et al.  Identification of three-dimensional electric conductivity changes from time-lapse electromagnetic observations , 2011, J. Comput. Phys..

[22]  S. Constable.  Ten years of marine CSEM for hydrocarbon exploration , 2010 .