Opus: An integrated assistance system for oil production

Hoffmann, F.; Valentin, E.

doi:10.1111/j.1468-0394.1987.tb00213.x

Cited by 4 publications

(1 citation statement)

References 2 publications

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“…The system determines the underground mining methods, open-pit mining transportation systems, and mining machinery for given conditions and integrates fuzzy sets and optimization methods. Other examples of automated systems developed for selection in process design include the selection of activation systems in oil production [10] and selection of solvent for removal of acidic gases [4,5]. In comparison to these studies that focus on automation of the selection task in the process industries, however, research that focus on applying a knowledge-based approach to automating the selection task in the problem domain of petroleum waste management is scarce.…”

Section: Introductionmentioning

confidence: 99%

Development of an Expert System for the Remediation of Petroleum-Contaminated Sites

Chen

Huang

Chan

et al. 2003

Environmental Modeling & Assessment

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Groundwater and soil contamination caused by light nonaqueous phase liquids (LNAPLs) spills and leakage in petroleum industry is currently one of the major environmental concerns in North America. Numerous site remediation technologies, generally classified as ex situ and in situ remediation techniques, have been developed and implemented to clean up the contaminated sites in the last two decades. One of the problems associated with ex situ remediation is the cost of operation. In recent years, in situ techniques have acquired popularity. However, the selection process of the desired techniques needs a large amount of knowledge. Insufficient expertise in the process may result in unnecessary inflation of expenses. In this study, petroleum waste management experts and Artificial Intelligence (AI) researchers worked together to develop an expert system (ES) for the management of petroleum contaminated sites. Various AI techniques were used to construct a useful tool for site remediation decision-making. This paper presents the knowledge engineering processes of knowledge acquisition, conceptual design, and system implementation in the project. The expert system was applied to a real-world case study and the results show that the expert system can generate desired remediation alternatives to assist decision-makers. The application case study constitutes partial validation of the prototype expert system.

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Section: Introductionmentioning

confidence: 99%