Expert systems in exploration: can they be cost-effective
PROSPECTOR is the best-known application of an expert system in exploration. Others exist for gamma-ray well logging analysis but are in general company-restricted and not in the open literature. PROSPECTOR, however, is comprised of a large set of elegant subprograms, each designed for a specific goal - generally for hard minerals. The program is expensive, costly to run, and requires a mainframe (usually a LISP machine) for operation. Recently, a microcomputer-based version (u-PROSPECTOR) has become available, but it still follows the formal artificial intelligence (AI) syntax of PROSPECTOR. In the Remote Sensing Laboratory at Stanford, they have been experimenting with low-end ($100-$1000) AI programs. The development of these has been driven by (1) the explosion of availability of microcomputers and (2) the realization by developers that the marketplace has many more Fortran and C-language machines available than the dedicated (and expensive) LISP units. This paper will discuss those commercially available, low-priced AI shells as applied to several of the simplest exploration problems - spectral pattern recognition and texture in radar imagery - and extrapolate their usefulness to more complex decision-making steps in exploration practice.
- Research Organization:
- Stanford Univ., CA
- OSTI ID:
- 6185886
- Report Number(s):
- CONF-870606-
- Journal Information:
- AAPG (Am. Assoc. Pet. Geol.) Bull.; (United States), Vol. 71:5; Conference: American Association of Petroleum Geologists annual meeting, Los Angeles, CA, USA, 7 Jun 1987
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
EXPERT SYSTEMS
COST BENEFIT ANALYSIS
PETROLEUM DEPOSITS
EXPLORATION
C CODES
COMPUTERS
DECISION MAKING
FORTRAN
GAMMA LOGGING
LISP
COMPUTER CODES
GEOLOGIC DEPOSITS
MINERAL RESOURCES
PROGRAMMING LANGUAGES
RADIOACTIVITY LOGGING
RESOURCES
WELL LOGGING
020200* - Petroleum- Reserves
Geology
& Exploration