Hydraulic fracturing candidate-well selection by interval type-2 fuzzy set and system

Abstract

Selecting a target formation(s) among a vast numbers of zones/sub-layers within huge numbers of hydrocarbon producing wells in a reservoir, is considered a difficult task, particularly if the selection goes through a group of parameters having different attributes and features; such as geological aspect, reservoir and fluid characteristics, etc. The trend of candidate-well selection (CWS) process for Hydraulic Fracturing (HF) had recognized to be complex, nonlinear, un-equilibrium, and adherent with uncertainty. Interval Type-2 Fuzzy Logic and Systems (lT2-FLSs) are very useful in circumstances where it is difficult to determine an exact membership function (MF) for a Fuzzy Set (FS); hence they are very effective for dealing with uncertainties. Classical FLS which called Tl-FLS is not capable of fully capturing the linguistic and numerical uncertainties in the terms used and the inconsistency of the expert's decision-making. Therefore, the need arises to use a method that could handle uncertainties. The procedure of applying this novel study in the area of HF CWS, will have illustrated through a case study in a carbonate reservoir. The utilization of a modem and right problem-solving tool such as T2-FSS should be considered a great concern to the petroleum industry. Although sizeable clarity has been achieved in this area, no conceptualization such as dealing with uncertainty, has yet answered by the previous studies. New requirements force the previous methods to advance and novel techniques expected to meet the requirements and remove the existing weakness. In highlighting this need, the question has been answered about why IT2-FLSs should be used in this study. Also, its advantages over Tl-FLS will be illustrated. This paper critically assesses the importance of the proposed methodology to develop a reliable model of HF CWS. This investigation is the first research which applied such a cutting-edge approach and tries to fill the gap between recent developments in uncertainty management through utilization of IT2-FLSs in HF candidate-well selection.