Optimization of Direction and Length of Horizontal Wells in Oil Field-X Using Fuzzy Substractive Clustering and Fuzzy Logic Methods

Tutuka Ariadji, Annisa Mayusha, Niken Nissa, Kuntjoro Sidarto and Edy Soewono

Modern Applied Science, 2014, vol. 8, issue 6, 326

Abstract: This study discusses an optimization model to obtain the optimal direction and length of horizontal wells in the oil field X. In the common practice in oil industries, the optimal direction and length are obtained from a trial and error method through a considerably time consuming reservoir simulation runs. Employing the basic reservoir properties data of the porosity, permeability, oil saturation, and location of each grid of the available reservoir model, Fuzzy Subtractive Clustering is used to classify grids. Furthermore, Fuzzy Logic optimization model is built to find the optimal direction and length of the horizontal well. Determination of the optimal direction and length is based on the oil recovery represented by a recovery factor that does not have any simple relationship with the basic reservoir properties data, but, through a reservoir simulation model that basically calculates fluid flows in porous media performances using a finite different formulation of the governing equation, i.e., the diffusivity equation. The filed case discussed in this study is one with the drilling starting point already known. The results of the study show that the methods of Fuzzy Subtractive Clustering and Fuzzy Logic are effective in determining the optimal direction and length simultaneously without running the reservoir simulation.

Date: 2014
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