Modeling the permeability of carbonate reservoir using type-2 fuzzy logic systems

In thiswork, theuseof type-2 fuzzy logic systemsas anovel approach forpredictingpermeability fromwell logs has been investigated and implemented. Type-2 fuzzy logic system is good in handling uncertainties, including uncertainties in measurements and data used to calibrate the parameters. In the formulation used, the value of a membership function corresponding to a particular permeability value is no longer a crispvalue; rather, it is associatedwitha rangeof values that canbecharacterizedbya function that reflects the level of uncertainty. In this way, the model will be able to adequately account for all forms of uncertainties associatedwithpredictingpermeability fromwell logdata,whereuncertainties areveryhigh and the need for stable results are highly desirable. Comparative studies have been carried out to compare the performance of the proposed type-2 fuzzy logic system framework with those earlier used methods, usingfivedifferent industrial reservoir data. Empirical results fromsimulation show that type-2 fuzzy logic approach outperformed others in general and particularly in the area of stability and ability to handle data in uncertain situations, which are common characteristics of well logs data. Another unique advantage of the newly proposed model is its ability to generate, in addition to the normal target forecast, prediction intervals as its by-products without extra computational cost. 2010 Elsevier B.V. All rights reserved.