An ensemble of multi-model regression framework based on fuzzy clustering using inference system architecture for reservoir permeability prediction. (2018)

• Record Type: Journal Article
• Authors: Nguyen, Van Huan; Pham, Truong Duy; Duong, Trong Hai
• Is Part Of: International journal of intelligent information and database systems. Volume 11:Number 4(2018)
• Page Start: 255
• Page End: 265
• Publication Date: 2018
• Subjects: neural networks -- ANFIS -- reservoir permeability prediction -- multi-model regression; Database management -- Computer programs -- Periodicals; Information retrieval -- Computer programs -- Periodicals; Information storage and retrieval systems -- Computer programs -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligent agents (Computer software) -- Periodicals; 006.33
• Languages: English
• ISSNs: 1751-5858

Abstract

One of the critical engineering problems in optimisation reservoir development is petroleum reservoir description and characterisation. Also, the successful applications of fuzzy inference system (FIS) and ensemble learning method in reservoir characterisation have been reported. In this study, we proposed an ensemble of multi-model regression framework based on FIS architecture to tackle the challenge of permeability prediction using logs data properties. The study demonstrates the capability of the ensemble model when tested in well log properties which is practical data of Oligocene geological types from Cuu Long basin. Empirical results indicate that our proposed algorithm framework is efficient and has the significant improvement compare to each existing standard single model.