Migration-velocity analysis using image-space generalized wavefields. SEP-141 (2010)
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Table of contents
- Title Pages
- Chapter 1: Introduction
- Chapter 2: Pre-Stack Exploding-Reflector Model
- Chapter 3: Image-space phase-encoded wavefields
- Chapter 4: MVA using image-space generalized sources
- Chapter 5: 3D field-data example
- Chapter 6: Conclusions
- Bibliography
Abstract
An accurate depth-velocity model is the key for obtaining good quality and reliable depth images in areas of complex geology. In such areas, velocity-model definition should use methods that describe the complexity of wavefield propagation, such as focusing and defocusing, multiple arrivals, and frequency-dependent velocity sensi- tivity. Wave-equation tomography in the image space has the ability to handle these issues because it uses wavefields as carriers of information. However, its high cost and low flexibility for parametrizing the model space has prevented its routine industrial use.
This thesis aims at overcoming those limitations by using new wavefields as car- riers of information: the image-space generalized wavefields. These wavefields are synthesized by using a pre-stack generalization of the exploding-reflector model. Cost of wave-equation tomography in the image space is decreased because only a small number of image-space generalized wavefields are necessary to accurately describe the kinematics of velocity errors and because these wavefields can be easily used in a target-oriented way. Flexibility is naturally incorporated into wave-equation tomog- raphy in the image space by using these wavefields because their modeling have as the initial conditions some key selected reflectors, allowing a layer-based parametrization of the model space.
To use the image-space generalized wavefields in wave-equation tomography in the image space, the method is extended from the shot-profile domain to the image-space generalized-sources domain. In this new domain, the velocity updates are very fast. Migration with the optimized velocity model provides good quality and reliable depth images, as can be seen in a 3D-field data example.