PhD opportunities

Anisotropic Migration Velocity Analysis

Area of expertise Gosciences et goingnierie
Doctoral School GRNE - Gosciences, Ressources Naturelles et Environnement
Title Anisotropic Migration Velocity Analysis
Supervisor M. Herv CHAURIS
Co-supervisor
Contact CHAURIS Herv
Research unit Geosciences
Gosciences - Fontainebleau
Keywords Seismic imaging, anisotropy, velocity analysis
Abstract Migration Velocity Analysis (MVA) is a technique to retrieve the background velocity model from seismic data [Sava et al., 2005; Symes, 2008]. The background model contains the long wavelength velocity structure of the Earth. MVA is a focusing technique, considered as a first step before subsequent Full Waveform Analysis. In a classical approach, MVA only relies on short-spread reflected energy.
Recently, MVA has been extended to transmitted waves [Lameloise and Chauris, 2016]. Typical transmitted waves are direct and diving waves. Such an extension is very interesting as short-spread reflected waves and transmitted waves have different paths: the combination of these waves offers the possibility to determine anisotropic velocity models.
The objective of the project is to derive an anisotropic Migration Velocity Analysis approach. Anisotropy is essential in many different geological contexts, in particular in the presence of shale or fractures.
Several anisotropic wave equations have been proposed to model anisotropic wave propagation [Alkhalifah, 2000; Zhou and Zhang, 2006; Zhang et al., 2011]. Here, we are interested in VTI (Vertical Transverse Isotropic) and TTI (Tilted Transverse Isotropic) models under the weak anisotropic assumption. Relying on anisotropic modelling tools, the first objective is to derive the equations indicating how to update the anisotropic coefficients. This will be obtained with the use of the adjoint state method. Then, one needs to determine which parameter(s) can really be retrieved by MVA, to limit the coupling between model parameters (velocity and selected anisotropic coefficients). It is also crucial to establish a strategy for multi-parameter inversion (e.g. first velocity estimation and then introduction of anisotropy). The implementation will be based on an existing 2d isotropic MVA code written in Fortan 90. This extension should be validated on 2d synthetic data to better understand the kind of anisotropy that can be retrieved in a MVA approach.
The student will have to derive the gradient of the objective function to update the anisotropic coefficients. He will have to establish a strategy in terms of model description and of hierarchical inversion. Finally, he will have to extend an existing isotropic MVA code and validate and understand the limits of the approach on 2d synthetic data sets. Beyond good capabilities in maths and programming, a good understanding of the wave propagation is essential.
Funding Autre type de financement
Partnership
Starting date October 1st 2017
Date of first publication April 4th 2017