Journal ArticleDOI
Virtual-Intelligence Applications in Petroleum Engineering: Part 1—Artificial Neural Networks
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TLDR
Intelligent hybrid systems that incorporate an integration of two or more of these paradigms and their application in the oil and gas industry are also discussed in these articles.Abstract:
This is the first article of a three-article series on virtual intelligence and its applications in petroleum and natural gas engineering. In addition to discussing artificial neural networks, the series covers evolutionary programming and fuzzy logic. Intelligent hybrid systems that incorporate an integration of two or more of these paradigms and their application in the oil and gas industry are also discussed in these articles. The intended audience is the petroleum professional who is not quite familiar with virtual intelligence but would like to know more about the technology and its potential. Those with a prior understanding of and experience with the technology should also find the articles useful and informative.read more
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Journal ArticleDOI
Applications of hybrid models in chemical, petroleum, and energy systems: A systematic review
TL;DR: Different sub-models, hybridization strategies, structural designs, screening criteria, and new directions in hybrid modeling are reviewed, with focus on the corresponding applications in chemical, petroleum, and energy systems.
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Reservoir properties determination using fuzzy logic and neural networks from well data in offshore Korea
TL;DR: In this article, the authors proposed an intelligent technique using fuzzy logic and neural network to determine reservoir properties from well logs, which can make more accurate and reliable reservoir properties estimation compared with conventional computing methods.
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Performance forecasting for polymer flooding in heavy oil reservoirs
TL;DR: In this article, the authors utilized an extensive data set from the half-century review of laboratory to field scales polymer flooding in heavy oil reservoirs provided by Saboorian-Jooybari et al.
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Recent Developments in Application of Artificial Intelligence in Petroleum Engineering
TL;DR: This article covers some of the most recent and advanced uses of intelligent systems in the oil and gas industry and discusses their potential role in the industry’s future.
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Forecasting PVT properties of crude oil systems based on support vector machines modeling scheme
TL;DR: Support vector machines are proposed a new intelligence framework for predicting the PVT properties of crude oil systems and solve most of the existing neural networks drawbacks.