Bayesian inversion of marine CSEM data with a trans-dimensional self parametrizing algorithm

Geophysical Journal International

Volumn 191, Issue 3, 2012, Pages 1135-1151

  Ray, Anandaroop ^a   Key, Kerry ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Australia; Electromagnetic theory; Inverse theory; Marine electromagnetics

Indexed keywords

AUSTRALIA; BAYESIAN APPROACHES; BAYESIAN INVERSION; CONTROLLED SOURCE; EARTH MODELS; ELECTROMAGNETIC DATA; ELECTROMAGNETIC FIELD COMPONENTS; ELECTROMAGNETIC THEORIES; ELECTROMAGNETICS; GAS FIELDS; GEOPHYSICAL DATA; GEOPHYSICAL INVERSE PROBLEMS; GRADIENT BASED; INVERSE THEORY; MODEL PROBABILITIES; NONUNIQUENESS; NUMBER OF LAYERS; POSTERIOR DISTRIBUTIONS; REGULARIZATION PARAMETERS; RESOLUTION CAPABILITY; REVERSIBLE JUMP MARKOV CHAIN MONTE CARLO; SEA FLOOR; SEISMIC STRATIGRAPHY; SURVEY DATA; WELL LOGS;

ANISOTROPY; BAYESIAN NETWORKS; ELECTRIC FIELDS; ELECTROMAGNETIC FIELDS; GAS INDUSTRY; INVERSE PROBLEMS; STRATIGRAPHY; WELL LOGGING;

ALGORITHMS;

ALGORITHM; BAYESIAN ANALYSIS; ELECTROMAGNETIC FIELD; GAS FIELD; GEOPHYSICAL METHOD; INVERSE PROBLEM; MARKOV CHAIN; MONTE CARLO ANALYSIS; SCANNING ELECTRON MICROSCOPY; SEAFLOOR;

AUSTRALIA;

EID: 84869083143     PISSN: 0956540X     EISSN: 1365246X     Source Type: Journal    
DOI: 10.1111/j.1365-246X.2012.05677.x     Document Type: Article

References (44)

1. Abubakar, A., Habashy, T.M., Druskin, V.L., Knizhnerman, L. & Alumbaugh, D., 2008. 2.5D forward and inverse modeling for interpreting low-frequency electromagnetic measurements, Geophysics, 73(4), F165-F177.
2. Agostinetti, N.P. & Malinverno, A., 2010. Receiver function inversion by trans-dimensional monte carlo sampling, Geophys. J. Int., 181(2), 858-872.
3. Andriéu, C., de Freitas, N., Doucet, A. & Jordan, M.I., 2003. An introduction to MCMC for machine learning, Mach. Learn., 50, 5-43, doi:10.1023/A:1020281327116.
4. Backus, G.E., 1988. Bayesian inference in geomagnetism, Geophys. J., 92(1), 125-142.
5. Bayes, T., 1763. An essay towards solving a problem in the doctrine of chances, Phil. Trans. R. Soc. Lond., 53, 370-418.
6. Bodin, T. & Sambridge, M., 2009. Seismic tomography with the reversible jump algorithm, Geophys. J. Int., 178(3), 1411-1436.
7. Bodin, T., Sambridge, M., Tkalcic, H., Arroucau, P., Gallagher, K. & Rawlinson, N., 2012. Transdimensional inversion of receiver functions and surface wave dispersion, J. geophys. Res., 117(B02031), 1-24.
8. Brown, V., Hoversten, M., Key, K. & Chen, J., 2012. Resolution of reservoir scale electrical anisotropy from marine CSEM data, Geophysics, 77(2), E147-E158.
9. Buland, A. & Kolbjornsen, O., 2012. Bayesian inversion of CSEM and magnetotelluric data, Geophysics, 77(1), E33-E42.
10. Chen, J., Hoversten, G.M., Vasco, D., Rubin, Y. & Hou, Z., 2007. A Bayesian model for gas saturation estimation using marine seismic AVA and CSEM data, Geophysics, 72(2), WA85-WA95.
11. Chew, W., 1995. Waves and Field in Inhomogeneous Media, Wiley IEEE Press, New York, NY.
12. Chib, S. & Greenberg, E., 1995. Understanding the metropolis-hastings algorithm, Am. Stat., 49(4), 327-335.
13. Collins, M.D. & Fishman, L., 1995. Efficient navigation of parameter landscapes, Acoust. Soc. Am. J., 98, 1637-1644.
14. Constable, S., 2010. Ten years of marine CSEM for hydrocarbon exploration, Geophysics, 75(5), 75A67-75A81.
15. Constable, S.C. & Weiss, C.J., 2006. Mapping thin resistors and hydrocarbons with marine EM methods: insights from 1D modeling, Geophysics, 71(2), G43-G51.
16. Constable, S.C., Parker, R.L. & Constable, C.G., 1987. Occam's inversion - a practical algorithm for generating smooth models from electromagnetic sounding data, Geophysics, 52(03), 289-300.
17. Dettmer, J., Dosso, S. & Holland, C., 2010. Trans-dimensional geoacoustic inversion, J. acoust. Soc. Am., 128, 3393-3405.
18. Dosso, S.E. & Dettmer, J., 2011. Bayesian matched-field geoacoustic inversion, Inv. Probl., 27(5), 055009, doi:10.1088/0266-5611/27/5/055009.
19. Ellingsrud, S., Eidesmo, T., Johansen, S., Sinha, M.C., MacGregor, L.M. & Constable, S., 2002. Remote sensing of hydrocarbon layers by seabed logging (SBL): results from a cruise offshore Angola, Leading Edge, 21, 972-982.
20. Green, P., 1995. Reversible jump MCMC and Bayesian model selection, Biometrika, 82, 711-732.
21. Gunning, J., Glinsky, M.E. & Hedditch, J., 2010. Resolution and uncertainty in 1D CSEM inversion: a Bayesian approach and open-source implementation, Geophysics, 75(6), F151-F171.
22. Hastings, W.K., 1970. Monte carlo sampling methods using markov chains and their applications, Biometrika, 57(1), 97-109.
23. Hou, Z., Rubin, Y., Hoversten, G.M., Vasco, D. & Chen, J., 2006. Reservoir-parameter identification using minimum relative entropy-based Bayesian inversion of seismic AVA and marine CSEM data, Geophysics, 71(6), O77-O88.
24. Huelsenbeck, J.P., Larget, B. & Alfaro, M.E., 2004. Bayesian phylogenetic model selection using reversible jump Markov chain Monte Carlo, Mol. Biol. Evol., 21(6), 1123-1133.
25. Key, K., 2009. 1D inversion of multicomponent, multifrequency marine CSEM data: methodology and synthetic studies for resolving thin resistive layers, Geophysics, 74(2), F9-F20.
26. Key, K., 2012a. Is the fast Hankel transform faster than quadrature? Geophysics, 77(3), F21-F30.
27. Key, K., 2012b. Marine electromagnetic studies of seafloor resources and tectonics, Surv. Geophys., 33(1), 135-167.
28. Key, K. & Lockwood, A., 2010. Determining the orientation of marine CSEM receivers using orthogonal procrustes rotation analysis, Geophysics, 75(3), F63-F70.
29. Li, Y. & Dai, S., 2011. Finite element modelling of marine controlled-source electromagnetic responses in two-dimensional dipping anisotropic conductivity structures, Geophys. J. Int., 185, 622-636.
30. Liang, F., Liu, C. & Carrol, R.J., 2010. Advanced Markov Chain Monte Carlo Methods: Learning from Past Samples, Wiley Series in Computational Statistics, Wiley, New York, NY.
31. Løseth, L.O. & Ursin, B., 2007. Electromagnetic fields in planarly layered anisotropic media, Geophys. J. Int., 170(1), 44-80.
32. Malinverno, A., 2002. Parsimonious Bayesian Markov chain Monte Carlo inversion in a nonlinear geophysical problem, Geophys. J. Int., 151, 675-688.
33. Minsley, B.J., 2011. A trans-dimensional Bayesian Markov chain Monte Carlo algorithm for model assessment using frequency-domain electromagnetic data, Geophys. J. Int., 187(1), 252-272.
34. Neal, R.M., 2003. Slice sampling, Ann. Stat., 31(3), 705-767.
35. Newman, G.A. & Alumbaugh, D.L., 2000. Three-dimensional magnetotelluric inversion using non-linear conjugate gradients, Geophys. J. Int., 140(2), 410-424.
36. Ramananjaona, C., MacGregor, L. & Andréis, D., 2011. Sensitivity and inversion of marine electromagnetic data in a vertically anisotropic stratified earth, Geophys. Prospect., 59(2), 341-360.
37. Scales, J.A. & Snieder, R., 1997. To Bayes or not to Bayes?, Geophysics, 62(4), 1045-1046.
38. Sen, M. & Stoffa, P.L., 1995. Global Optimization Methods in Geophysics, Elsevier, Amsterdam.
39. Smith, K., Gatica-Perez, D. & Odobez, J.-M., 2005. Using particles to track varying numbers of interacting people, in Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Vol. 1, pp. 962-969, San Diego, CA.
40. Tarantola, A., 2005. Inverse Problem Theory and Methods for Model Parameter Estimation, Society of Industrial and Applied Mathematics, Philadelphia, PA.
41. Tilbury, L.A. et al., 2009. Pluto - a major gas field hidden beneath the continental slope (dvd), APPEA J., 49, 243-265.
42. Tompkins, M.J., Fernández Martínez, J.L., Alumbaugh, D.L. & Mukerji, T., 2011. Scalable uncertainty estimation for nonlinear inverse problems using parameter reduction, constraint mapping, and geometric sampling: marine controlled-source electromagnetic examples, Geophysics, 76(4), F263-F281.
43. Trainor-Guitton, W. & Hoversten, G.M., 2011. Stochastic inversion for electromagnetic geophysics: practical challenges and improving convergence efficiency, Geophysics, 76(6), F373-F386.
44. Um, E.S. & Alumbaugh, D.L., 2007. On the physics of the marine controlled-source electromagnetic method, Geophysics, 72(2), WA13-WA26.