Diagnostic Expert Systems: Encoding Geological Knowledge for an Exploration Play Analysis
Betty M. Miller
Abstract
Betty M. Miller
Abstract
The U.S. Geological Survey is currently exploring the feasibility of applying diagnostic expert systems and knowledge-based acquisition techniques to the geologic analysis of sedimentary basins and petroleum exploration plays. This paper describes a unique approach to the design and application of a rule-based expert system to the analysis of exploration plays, a methodology commonly used to assess petroleum resources in a basin. This technique consists of using various geologic models and Monte Carlo simulation or probabilistic methods for analyzing geologic and reservoir conditions favorable to the occurrence of petroleum resources. Work is in progress to adapt the geologic model used in the play analysis to an expert-systems and knowledge base, the object being to capture the logic and reasoning used to characterize the geologic model and to evaluate the play. Expert systems techniques now being developed are capable of dealing with inexact reasoning or reasoning under uncertainty by incorporating degrees of uncertainty to deal effectively with incomplete, inferred, or interpretive data involved in the knowledge base. The goal of this study is to provide an embedded diagnostic expert-system approach for characterizing the geologic model to expand upon the play-analysis system. Such a system provides the geologist with capabilities to documentmore » major basin components, such as stratigraphy, structural geology, and sedimentation, and to analyze the traditional concepts of source, reservoir, and trapping mechanisms. This expert system will assist the geologist in compiling and interpreting the geologic and reservoir engineering data necessary for running the probabilistic methods to calculate the amount of probable petroleum resources within each play. Diagnostic expert-systems technology can provide challenging new tools in knowledge acquisition and data interpretation in petroleum geology.« less
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The U.S. Geological Survey is currently exploring the feasibility of applying diagnostic expert systems and knowledge-based acquisition techniques to the geologic analysis of sedimentary basins and petroleum exploration plays. This paper describes a unique approach to the design and application of a rule-based expert system to the analysis of exploration plays, a methodology commonly used to assess petroleum resources in a basin. This technique consists of using various geologic models and Monte Carlo simulation or probabilistic methods for analyzing geologic and reservoir conditions favorable to the occurrence of petroleum resources. Work is in progress to adapt the geologic model used in the play analysis to an expert-systems and knowledge base, the object being to capture the logic and reasoning used to characterize the geologic model and to evaluate the play. Expert systems techniques now being developed are capable of dealing with inexact reasoning or reasoning under uncertainty by incorporating degrees of uncertainty to deal effectively with incomplete, inferred, or interpretive data involved in the knowledge base. The goal of this study is to provide an embedded diagnostic expert-system approach for characterizing the geologic model to expand upon the play-analysis system. Such a system provides the geologist with capabilities to documentmore » major basin components, such as stratigraphy, structural geology, and sedimentation, and to analyze the traditional concepts of source, reservoir, and trapping mechanisms. This expert system will assist the geologist in compiling and interpreting the geologic and reservoir engineering data necessary for running the probabilistic methods to calculate the amount of probable petroleum resources within each play. Diagnostic expert-systems technology can provide challenging new tools in knowledge acquisition and data interpretation in petroleum geology.« less
Key concepts: Expert system, Geologist, Knowledge base, Probabilistic logic, Geology, Computer science, Sedimentary basin, Stratigraphy