Quick Search:    advanced search

GSW Home   GeoRef Home   My GSW Alerts   Contact GSW   About GSW   Journals List   Help

This Article Figures Only Full Text Full Text (PDF) Submit a response Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via Google Scholar Google Scholar Articles by Buur, J. N. Articles by Kühnel, T. Search for Related Content GeoRef GeoRef Citation

Improving depth imaging by automated model updating

Shell International Exploration and Production B.V., Rijswijk, The Netherlands

Corresponding author: Jack.Buur@shell.com

The first 20% of the full text of this article appears below.

As exploration and production move ever faster into ever more geologically complex areas, very accurate imaging of subsurface structure becomes critical to successful well positioning and reserve estimations. Currently, the only tool that can achieve this is prestack depth migration (PSDM).

The continuing improvements of personal computers, which are now capable of high-performance computing due to the introduction of Linux-based clusters, have resulted in the development of PC-based processing systems that are widely accepted in the seismic industry. We foresee that this new source of ubiquitous, cheap compute power will be applied to depth imaging of increasingly larger data sets. This is an important development, but are there other ways to make good use of ample processing power?

In this article, we suggest that new ideas can be applied at various stages of the prestack depth migration loop to improve overall quality and, more significant perhaps, reduce the need for human intervention to a bare minimum.

We believe that automated velocity model building and updating could be the key to improving the depth migration process, because more iterations could be run in less time and, it is assumed, that increasing the number of iterations will result in better convergence of the model with the earth.

The Sakhalin data example in this article incorporates several of these ideas in a commonly used prestack depth migration cycle.

Figure 1, the PSDM cycle, indicates the areas where we have developed new ways of working. The initial velocity model is a grid representing the seismic velocities and is used to perform a prestack depth migration. The step requires that the migration operators and the prestack seismic data be fed into the Kirchhoff summation migration engine (Berkhout, 1984; Schleicher et al., 1993), which produces image gathers. The residual moveout on the common image gathers . . . [Full Text of this Article]