Optimal Selection of Stimulation Wells Using a Fuzzy Multicriteria Methodology

Abstract

Choosing the most appropriate wells for stimulation is one of the greatest challenges affecting reservoir production and economic development. In this paper, an integrated fuzzy decision-making methodology is developed to choose the most appropriate stimulation wells based on a number of criteria. The presented approach is able to determine the final decision priorities for multiple candidate wells considering uncertainty, incomplete information, and the large number of factors involved. The proposed modelling framework works as a stepwise procedure to fuse several different methods with combined benefits. The analytic hierarchy process (AHP) method is adopted to build the factor framework. Grey theory is introduced to determine the influence weights of factors, and combined with the fuzzy logic concept, these values are used to rank candidate wells. A field application shows that the presented method is able to identify the wells with the highest potential for enhanced production.

Well Selection for CO2 Huff-n-Puff in Unconventional Oil Reservoirs Based on Improved Fuzzy Method

“…Due to the inherent uncertainty in well selection evaluation methods, fuzzy methods are commonly employed to establish evaluation systems [18][19][20]. This involves normalizing using membership functions and obtaining weighting factors for each influencing factor through expert scoring.…”