Applications of soft computing in petroleum engineering

Andrew H. Sung

doi:10.1117/12.367696

1 November 1999 Applications of soft computing in petroleum engineering

Andrew H. Sung

Proceedings Volume 3812, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation II; (1999) https://doi.org/10.1117/12.367696
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1999, Denver, CO, United States

Abstract

This paper describes several applications of neural networks and fuzzy logic in petroleum engineering that have been, or are being, developed recently at New Mexico Tech. These real-world applications include a fuzzy controller for drilling operation; a neural network model to predict the cement bonding quality in oil well completion; using neural networks and fuzzy logic to rank the importance of input parameters; and using fuzzy reasoning to interpret log curves. We also briefly describe two ongoing, large-scale projects on the development of a fuzzy expert system for prospect risk assessment in oil exploration; and on combining neural networks and fuzzy logic to tackle the large-scale simulation problem of history matching, a long- standing difficult problem in reservoir modeling.

Citation Download Citation

Andrew H. Sung "Applications of soft computing in petroleum engineering", Proc. SPIE 3812, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation II, (1 November 1999); https://doi.org/10.1117/12.367696

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