Smart Oilfield Data Mining for Reservoir Analysis

Provided by: The International Journals of Engineering & Sciences (IJENS)
Topic: Data Management
Format: PDF
In this paper, the authors randomly generate several well properties and perform reservoir simulations via the Eclipse software in order to obtain the oil recovery factor. Several simulations lead to the formation of a dataset which will be analyzed via a well-known data mining method, the Association RULES (ARULES). ARULES yields several rules that reveals how these parameters interact and contribute to either increase/decrease the oil recovery. Artificial Neural Networks (ANNs) is also used in order to determine the rank of importance (by analysis of its weights) of these parameters, which is useful in detecting the highly reliable rules.

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