Seismic inversion and the data normalization for optimal transport

Joint Bayesian Stochastic Inversion of Well Logs and Seismic Data for Volumetric Uncertainty Analysis

Here in, an application of a new seismic inversion algorithm in one of Iran’s oilfields is described. Stochastic (geostatistical) seismic inversion, as a complementary method to deterministic inversion, is perceived as contribution combination of geostatistics and seismic inversion algorithm. This method integrates information from different data sources with different scales, as prior informat...

An optimal transport approach for seismic tomography: application to 3D full waveform inversion

The use of optimal transport distance has recently yielded significant progress in image processing for pattern recognition, shape identification, and histograms matching. In this study, the use of this distance is investigated for a seismic tomography problem exploiting the complete waveform; the full waveform inversion. In its conventional formulation, this high resolution seismic imaging met...

The Application of Optimal Wavelets in Seismic Inversion

The current emphasis in seismic stratigraphy has This process of wavelet extraction, followed by the focussed on velocity inversion and the generation of derivation of the reflectivity sequence, allows the the pseudo-acoustic log from the seismic trace. ideal pre-conditioning for seismic velocity inverThere are several published methods on wavelet sion. extraction which invariably make assumpti...

Constrained inversion of P-S seismic data

A method to estimate S-wave interval velocity, using P-S seismic data is presented. The method is composed of three steps. First, the P-S data are converted to a relative change in S-velocity section. The section is then linearized. Constrained inversion is used to convert this last section to S-interval velocity. To illustrate the method, the S velocity of a field data set was derived, and a V...

cDNA Microarray Data Normalization