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Bayesian seismic inversion for stratigraphic horizon, lithology, and fluid prediction
Bayesian AVO inversion to rock properties using a local neighborhood in a spatial prior model
Bayesian inversion of CSEM and magnetotelluric data
Model-based fluid factor for controlled source electromagnetic data
Bayesian Dix inversion
Improved resolution in Bayesian lithology/fluid inversion from prestack seismic data and well observations: Part 2 — Real case study
Bayesian Monte Carlo method for seismic predrill prospect assessment
Bayesian lithology and fluid prediction from seismic prestack data
Bayesian lithology/fluid prediction and simulation on the basis of a Markov-chain prior model
Bayesian time-lapse inversion
Bayesian wavelet estimation from seismic and well data
Rapid spatially coupled AVO inversion in the Fourier domain
Bayesian linearized AVO inversion
The impact of common-offset migration on porosity estimation by AVO inversion
Abstract The objective of the present work is to obtain estimates of the P - and S -wave velocities and densities of the subsurface. The inversion is carried out on 952 τ – p transformed CMP gathers, each containing 61 p values ranging from 0.05 to 0.35 s/km. The forward modeling is performed by convolving the reflectivity with the wavelet, and it includes water bottom multiples, transmission effects, absorption and array filter effects. The basic assumption is that the subsurface is close to horizontally layered. A damped Gauss-Newton algorithm is used to minimize a least-squares misfit function. Comparison with the two well logs shows good agreement for the P -wave velocity estimates in the areas where the geology is close to horizontally stratified. In deeper and faulted areas the deviation between estimated and measured P -wave velocities is larger. The same trend holds for the S -wave velocity estimates, while the densities are the poorest resolved seismic parameter.