Determination of seismic velocities is a fundamental step in seismic data processing. One commonly used tool for obtaining seismic velocities is the velocity spectrum. A velocity spectrum consists of a map of coherency of seismic events versus time when various velocities are assumed. The velocity function is obtained by binding velocity-spectrum extrema corresponding to primary reflections. However, seismic data contain not only primary reflections but also interfering events and noise. Consequently, the geophysicist has to select the proper velocity-spectrum extrema in order to define a velocity function consistent with the geology. This task, which requires an experienced geophysicist, is a time consuming step in seismic data processing. Productivity would be greatly improved by automating this task.
An expert system for aid in the interpretation of velocity spectra is presented. The problem is how to find the best path in the graph made up of the velocity-spectrum extrema (peaks), where no definite starting and arrival point exists. The resulting velocity function must be sufficiently smooth and consistent with the geological and geophysical context. The generating of the search space and its filtering are therefore carried out with heuristics specific to geophysical criteria and adapted to the velocity analysis problem. The expert system is implemented in OPS5, with external functions in Fortran and C. The raw velocity spectra computed by conventional seismic data processing software and a simplified description of the geological and geophysical context of the survey are input data for the system. In the present state of the system, the assumption is made that the velocity field varies smoothly between neighboring analyses.
The expert system automatically delivers a set of velocity functions on a profile. The system ensures the results are coherent with the geology and the consistency of the velocity functions on the profile. The geophysicist, by controlling the results with the help of the warning messages produced by the system, can obtain an important gain of human work time.
Field data examples are presented where velocity functions obtained by manual picking and by the expert system picking compare favorably.
Figures & Tables
“So far as the laws of mathematics refer to reality they are not certain; and so far as they are certain, they don’t refer to reality.” This quote from Albert Einstein explains the difficulties associated with a mathematical description of many subjective rules used by human experts in reaching a decision. This fact, combined with the multidisciplinary nature of oil exploration, has prevented wide spread use of expert systems in the oil industry. Alternative approaches, that can account for uncertainty and are better equipped for integrating data and rules from different disciplines, should be used to allow expert systems to become viable tools in our applications.
This book examines a diverse set of petroleum exploration problems that properly designed expert systems can help solve. Chapter 1 provides an extensive review of current state-of-the-art expert systems as pertains to oil industry problems. Emphasis is given to how uncertainty and inexactness of data and rules from different disciplines could be handled by expert systems. The chapter suggests that fuzzy logic, evidential reasoning, and neural networks will prove essential in the design of many expert systems that are capable of solving more practical exploration problems. The problem of automatic picking of stacking velocities, using a rule based system, is addressed in Chapter 2. The expert system automates the task of picking the extreme of the velocity spectrum. The system incorporates common sense rules to distinguish primary reflection related peaks in the spectrum from those related to multiples and noise.