Applications of type-2 fuzzy logic system: handling the uncertainty associated with candidate-well selection for hydraulic fracturing. Issue 7 (October 2016)

• Record Type: Journal Article
• Authors: Zoveidavianpoor, Mansoor; Gharibi, Abdoullatif
• Is Part Of: Neural computing & applications. Volume 27:Issue 7(2016)
• Page Start: 1831
• Page End: 1851
• Publication Date: 2016-10
• Subjects: Interval type-2 fuzzy logic system -- Uncertainty -- Hydraulic fracturing -- Candidate-well selection; Neural networks (Computer science) -- Periodicals; Neural circuitry -- Periodicals; Artificial intelligence -- Periodicals; Neural Networks (Computer) -- Periodicals; Réseaux neuronaux (Informatique) -- Périodiques; Réseaux nerveux -- Périodiques; Intelligence artificielle -- Périodiques; 006.32
• DOI: 10.1007/s00521-015-1977-x
• Languages: English
• ISSNs: 0941-0643

Abstract

Abstract The problem of selecting a target formation(s) in a reservoir among a vast number of zones/sub-layers within huge number of hydrocarbon producing wells for hydraulic fracturing (HF) by using interval type-2 fuzzy logic system (IT2-FLS) to maximize their net present value is studied in this paper. Classical fuzzy system which is called type-1 fuzzy logic system is not capable of accurately capturing the linguistic and numerical uncertainties in the terms used and the inconsistency of the expert's decision-making. IT2-FLS is very useful in circumstances where it is difficult to determine an exact membership function for a fuzzy set; hence it is very effective for dealing with uncertainties. In highlighting this need, the question has been answered why IT2-FLS should be used in this study. The procedure of applying this study in the area of HF candidate-well selection is illustrated through a case study in an oil reservoir.