Browsing by Subject "Subsurface imaging"

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Full-waveform inversion in three-dimensional PML-truncated elastic media : theory, computations, and field experiments
(2015-05) Fathi, Arash; Kallivokas, Loukas F.; Dawson, Clinton N; Demkowicz, Leszek F; Ghattas, Omar; Manuel, Lance; Stokoe II, Kenneth H
We are concerned with the high-fidelity subsurface imaging of the soil, which commonly arises in geotechnical site characterization and geophysical explorations. Specifically, we attempt to image the spatial distribution of the Lame parameters in semi-infinite, three-dimensional, arbitrarily heterogeneous formations, using surficial measurements of the soil's response to probing elastic waves. We use the complete waveforms of the medium's response to drive the inverse problem. Specifically, we use a partial-differential-equation (PDE)-constrained optimization approach, directly in the time-domain, to minimize the misfit between the observed response of the medium at select measurement locations, and a computed response corresponding to a trial distribution of the Lame parameters. We discuss strategies that lend algorithmic robustness to the proposed inversion schemes. To limit the computational domain to the size of interest, we employ perfectly-matched-layers (PMLs). The PML is a buffer zone that surrounds the domain of interest, and enforces the decay of outgoing waves. In order to resolve the forward problem, we present a hybrid finite element approach, where a displacement-stress formulation for the PML is coupled to a standard displacement-only formulation for the interior domain, thus leading to a computationally cost-efficient scheme. We discuss several time-integration schemes, including an explicit Runge-Kutta scheme, which is well-suited for large-scale problems on parallel computers. We report numerical results demonstrating stability and efficacy of the forward wave solver, and also provide examples attesting to the successful reconstruction of the two Lame parameters for both smooth and sharp profiles, using synthetic records. We also report the details of two field experiments, whose records we subsequently used to drive the developed inversion algorithms in order to characterize the sites where the field experiments took place. We contrast the full-waveform-based inverted site profile against a profile obtained using the Spectral-Analysis-of-Surface-Waves (SASW) method, in an attempt to compare our methodology against a widely used concurrent inversion approach. We also compare the inverted profiles, at select locations, with the results of independently performed, invasive, Cone Penetrometer Tests (CPTs). Overall, whether exercised by synthetic or by physical data, the full-waveform inversion method we discuss herein appears quite promising for the robust subsurface imaging of near-surface deposits in support of geotechnical site characterization investigations.
Processing and imaging of multi-component ocean bottom cable data in the plane wave domain
(2001) Al-Saelh, Saleh M.; Stoffa, Paul L., 1948-; Sen, Mrinal K.
Conventional 3-D seismic reflection surveys typically use only compressional wave energy reflected from subsurface layers. Surveys deploying multi-component Ocean Bottom Cables (4-C OBC) are an emerging technology for marine seismic surveys that are enhancing oil and gas exploration because of the added advantage of incorporating shear waves to the analysis of sediment properties. Multi-component seismic methods use both compressional (P-) and shear (S-) waves for the analysis of the subsurface rock properties. 4-C OBC receivers are deployed directly on the seafloor to record both P-waves and converted shear waves. In this thesis, I focus on the processing of 2-D multi-component OBC data to improve the data quality and to remove unwanted energy like coherent noise and multiples (sea surface and inter-bed multiples) to obtain better images of the subsurface targets. I apply processing techniques in the τ-p (plane wave) domain where multiples are periodic and hence easier to remove. Further, in τ-p domain, it is easier to discriminate between events that travel with velocities lower than P-wave velocity like converted shear waves and the faster P-waves. In shallow water environments, free surface multiples often mask the desired signals. I investigate two approaches to remove these multiples. In the first approach, I apply a predictive deconvolution to remove the periodic sea-surface multiples. As a result of the first approach, I also apply a second of single channel spiking deconvolution to expand the bandwidth, compress the wavelet, and improve the temporal resolution. Then a multi-channel spiking deconvolution is applied, where the filter operator is estimated from more than one channel, to further compress the wavelet and remove the filtering effects of the earth. In the second approach, I apply a band reject filter to suppress the multiples then a pass of multi-channel spiking deconvolution. Comparisons of the two approaches show that the second approach is more effective and efficient in suppressing the multiples and the unwanted energy. After improving data quality by frequency filtering the data and removing most of the multiples I migrate the data. Seismic migration attempts to image the earth’s subsurface with reflections migrated to their true spatial position. There are two steps in migration: the first step is propagating the wavefields into their true subsurface locations and in the second step the imaging condition is applied. The method that I use is Prestack Plane Wave Kirchhoff Depth Migration to propagate the wavefield into their true subsurface locations by calculating the travel time for upgoing and downgoing waves. After migration, I obtain a CIG (common image gather) for each imaging point and then stack all the ray-parameters to obtain one trace from each CIG to form a stack image. Using multi-component data has advantages during both primary exploration, and during expensive enhanced recovery projects. I found that processing the data in τ-p domain is effective in suppressing the multiples and unwanted energy to improve the data quality. Further, Prestack Plane Wave Kirchhoff Depth Migration is an efficient method to migrate and image multicomponent data by applying the velocity model appropriate for each component