Application of artificial intelligence to reservoir characterization: An interdisciplinary approach. [Quarterly progress report], October 1--December 30, 1993
This basis of this research is to apply novel techniques from Artificial Intelligence and Expert Systems in capturing, integrating and articulating key knowledge from geology, geostatistics, and petroleum engineering to develop accurate descriptions of petroleum reservoirs. The ultimate goal is to design and implement a single powerful expert system for use by small producers and independents to efficiently exploit reservoirs. The first task under each of the concurrent phases of developing large-scale and small-scale reservoir descriptions is to identify the main knowledge sources. This task involves the identification of the critical variables that have an impact on large-scale heterogeneities. Because of the interdisciplinary nature of the project, we have had to develop a common vocabulary among the researchers to accomplish this identification task of Phases I and II. It was necessary for the computer science faculty and students to familiarize themselves with the information processed in geology geostatistics, and petroleum engineering. In addition, the geology and petroleum engineering researchers required instruction in the process of building expert systems. As part of the simulation task of Phase I and II, we have decomposed the design of the expert system into smaller component parts to get a clearer picture of what expert knowledge is needed. This decomposition will facilities that validation and verification of a complex expert system. We will develop concurrently three small prototype systems that will interface with a central repository of reservoir descriptions. The three component systems will be representative of how each of the experts in geology, geostatistics, and engineering characterizes the reservoir. The repository will hold all descriptions that are consistent with the currently known information.
- Research Organization:
- Tulsa Univ., OK (United States)
- Sponsoring Organization:
- USDOE, Washington, DC (United States)
- DOE Contract Number:
- AC22-93BC14894
- OSTI ID:
- 10138249
- Report Number(s):
- DOE/BC/14894-1; ON: DE94009240; BR: AC0535000/AC0540000
- Resource Relation:
- Other Information: PBD: [1993]
- Country of Publication:
- United States
- Language:
- English
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