David Yingst

On the connection between artifact filtering in reverse-time migration and adjoint tomography

Finite-frequency sensitivity kernels in seismic tomographydefinethevolumesinsidetheearththatinfluenceseismic wavesastheytraversethroughit.Ithasrecentlybeennumerically observed that an image obtained using the impedance kernel is much less contaminated by low-frequency artifacts due to the presence of sharp wave-speed contrasts in the background model, than is an image obtained using reversetime migration. In practical reverse-time migration, these artifacts are routinely heuristically dampened by Laplacian filtering of the image. Here we show analytically that, for an isotropic acoustic medium with constant density, away from sources and receivers and in a smooth background medium, Laplacian imagefiltering is identical to imaging with the impedance kernel. Therefore, when imaging is pushed toward using background models with sharp wave-speed contrasts, the impedance kernel image is less prone to develop low-frequency artifacts than is the reverse-time migration image, due to the implicit action of the Laplacian that amplifies the higher-frequency reflectors relative to the low-frequency artifacts.Thus,theheuristicLaplacianfilteringcommonlyused in practical reverse-time migration is fundamentally rooted inadjointtomographyand,inparticular,closelyconnectedto theimpedancekernel.

Comparing common‐offset Maslov, Gaussian Beam, and coherent state migrations

Several techniques to circumvent limitations in produc tion Kirchho migration have recently been proposed Kirchho migration can be extended to handle phases through caustics as well as true amplitude inversion For large scale production work however where Green s function information is often precomputed storage of traveltimes phases and amplitudes for multiple arrivals can become prohibitive Wave eld extrapolation tech niques are also being used although these techniques can be computationally expensive

3D Waveform Inversion Based On Reverse Time Migration Engine

Accurate seismic imaging offers major challenges for geophysical data processing both algorithmically and computationally. To reduce computational cost, the oneway wave equation is often used at the expense of the quality available from the two-way wave equation as used in prestack reverse time migration. Recently RTM has become commercially viable and is proving to be an invaluable tool for enhancing image quality, more so more than other migration techniques (excluding gains from human experience and intervention).

Practical Strategies for Waveform Inversion

The term “waveform inversion” refers to a collection of techniques that use the information from the times and waveform shapes of seismic data to derive high fidelity velocity models for seismic imaging. Waveform inversion was first introduced by Lailly, Tarantola, and Mora(Lailly, 1983; Tarantola, 1984; Mora, 1988). Since these pioneering efforts many researchers have attempted to use various strategies and computational schemes to make waveform inversion implemented either in the time or the frequency domain a processing tool for real data sets. The attractiveness of waveform inversion lies mainly in its lack of approximations, at least in a formal theoretical sense, in contrast to other traditional velocity determination techniques such as semblance or tomography. However, a whole raft of approximations must be made to make the technique viable with today’s computing technology and restrictions of seismic data acquisition. Some of these approximations are rather severe, such as restriction to acoustic waveform inversion while others are made simply to speed up the process. These are collectively referred to as “waveform inversion strategies”, which turn the whole process into a very manpower intensive art form. This paper discusses these various strategies and their influences on the velocity models that are obtained from waveform inversion. One cannot exhaustively test all the choices of strategies, and for that reason the paper focuses on the choices that in our experience create the most difficulties. These approaches will be illustrated on data from offshore Brazil.

Practical strategies for waveform inversion

The term “waveform inversion” refers to a collection of techniques that use the information from the times and waveform shapes of seismic data to derive high fidelity velocity models for seismic imaging. Waveform inversion was first introduced by Lailly, Tarantola, and Mora(Lailly, 1983; Tarantola, 1984; Mora, 1988). Since these pioneering efforts many researchers have attempted to use various strategies and computational schemes to make waveform inversion implemented either in the time or the frequency domain a processing tool for real data sets.