An overview of the SEISCOPE project on frequency-domain Full Waveform Inversion Multiparameter inversion and efficient 3D full-waveform inversion

We present an overview of the SEISCOPE project on frequency-domain full waveform inversion (FWI). The two main objectives are the reconstruction of multiple classes of parameters and the 3D acoustic and elastic FWI. The optimization relies on a preconditioned L-BFGS algorithm which provided scaled gradients of the misfit function for each classes of parameter. For onshore applications where body waves and surface waves are jointly inverted, P- and S-wave velocities (VP and VS) must be reconstructed simultaneously using a hierarchical inversion algorithm with two nested levels of data preconditioning with respect to frequency and arrival time. Simultaneous inversion of multiple frequencies rather than successive inversions of single frequencies significantly increases the S/N ratio of the models. For offshore applications where VS can have a minor footprint in the data, a hierarchical approach which first reconstructsVP in the acoustic approximation from the hydrophone component followed by the joint reconstruction of VP and VS from the geophone components can be the approach of choice. Among all the possible minimization criteria, we found that the L1 norm provides the most robust and easy-to-tune criterion as expected for this norm. In particular, it allowed us to successfully reconstruct VP and VS on a realistic synthetic offshore case study, when white noise with outliers has been added to the data. The feasibility of 3D FWI is highly dependent on the efficiency of the seismic modelling. Frequency-domain modelling based on direct solver allows one to tackle small-scale problems involving few millions of unknowns at low frequencies. If the seismic modelling engine embeds expensive source-dependent tasks, source encoding can be used to mitigate the computational burden of multiple-source modelling. However, we have shown the sensitivity of the source encoding to noise in the framework of efficient frequency-domain FWI where a limited number of frequencies is inverted sequentially. Simultaneous inversion of multiple frequencies is required to achieve an acceptable S/N ratio with a reasonable number of FWI iterations. Therefore, time-domain modelling for the estimation of harmonic components of the solution can be the approach of choice for 3D frequency-domain FWI because it allows one to extract an arbitrary number of frequencies at a minimum extra cost.

[1]  S. Operto,et al.  Sensitivity Analysis of Full Waveform Inversion in VTI Media , 2010 .

[2]  S. Operto,et al.  Which data residual norm for robust elastic frequency-domain full waveform inversion? , 2010 .

[3]  P. Jaiswal,et al.  Seismic imaging of the Naga thrust using multiscale waveform inversion , 2009 .

[4]  R. Plessix Three-dimensional frequency-domain full-waveform inversion with an iterative solver , 2009 .

[5]  Marwan Charara,et al.  The domain of applicability of acoustic full-waveform inversion for marine seismic data , 2009 .

[6]  J. Krebs,et al.  Fast full-wavefield seismic inversion using encoded sources , 2009 .

[7]  Romain Brossier Imagerie sismique à deux dimensions des milieux visco-élastiques par inversion des formes d'ondes : développements méthodologiques et applications , 2009 .

[8]  Jean Virieux,et al.  An overview of full-waveform inversion in exploration geophysics , 2009 .

[9]  S. Operto,et al.  Seismic imaging of complex onshore structures by 2D elastic frequency-domain full-waveform inversion , 2009 .

[10]  Jean Virieux,et al.  Finite-difference frequency-domain modeling of viscoacoustic wave propagation in 2D tilted transversely isotropic (TTI) media , 2009 .

[11]  F. Herrmann,et al.  Compressive simultaneous full-waveform simulation , 2009 .

[12]  Jan H. Kommedal,et al.  3D Waveform Inversion on Valhall Wide-azimuth OBC , 2009 .

[13]  Azzam Haidar,et al.  Seismic wave modeling for seismic imaging , 2009 .

[14]  Jean Virieux,et al.  Velocity model building by 3D frequency-domain, full-waveform inversion of wide-aperture seismic data , 2008 .

[15]  L. Sirgue,et al.  3D Frequency Domain Waveform Inversion Using Time Domain Finite Difference Methods , 2008 .

[16]  Azzam Haidar,et al.  Frequency-domain Full-waveform Modeling Using a Hybrid Direct-iterative Solver Based On a Parallel Domain Decomposition Method: a Tool For 3D Full-waveform Inversion? , 2008 .

[17]  S. Operto,et al.  3D finite-difference frequency-domain modeling of visco-acoustic wave propagation using a massively parallel direct solver: A feasibility study , 2007 .

[18]  R. Plessix A review of the adjoint-state method for computing the gradient of a functional with geophysical applications , 2006 .

[19]  Fuchun Gao,et al.  Waveform tomography at a groundwater contamination site: VSP-surface data set , 2006 .

[20]  Barbara Romanowicz,et al.  Towards global earth tomography using the spectral element method: a technique based on source stacking , 2005 .

[21]  Jean Virieux,et al.  Multiscale imaging of complex structures from multifold wide-aperture seismic data by frequency-domain full-waveform tomography: application to a thrust belt , 2004 .

[22]  Louis A. Romero,et al.  Phase encoding of shot records in prestack migration , 2000 .

[23]  Hicks,et al.  Gauss–Newton and full Newton methods in frequency–space seismic waveform inversion , 1998 .

[24]  K. Marfurt Accuracy of finite-difference and finite-element modeling of the scalar and elastic wave equations , 1984 .

[25]  J. Nocedal Updating Quasi-Newton Matrices With Limited Storage , 1980 .

[26]  Jean Virieux,et al.  A Massively Parallel Time-domain Discontinuous Galerkin Method For 3D Elastic Wave Modeling , 2009 .

[27]  Romain Brossier,et al.  Two-dimensional Seismic Imaging of the Valhall Model From Synthetic OBC Data By Frequency Domain Elastic Full-waveform Inversion , 2009 .

[28]  Jean Virieux,et al.  Three-dimensional frequency-domain full waveform inversion with phase encoding , 2009 .

[29]  R. Gerhard Pratt,et al.  Efficient waveform inversion and imaging: A strategy for selecting temporal frequencies , 2004 .

[30]  A. Tarantola Inverse problem theory : methods for data fitting and model parameter estimation , 1987 .