Abstract
This paper aims to address the challenges faced in selecting the most
suitable oil and gas (OG) well alternative for stimulation operations to
improve production and recovery possibilities in hydrocarbon reservoirs.
To achieve this, a novel combination of multiple criteria
decision-making (MCDM) models has been proposed, and an illustrative
study has been carried out in Iranian hydrocarbon reservoirs. Fourteen
criteria based on engineering and managerial perspectives have been
identified, and the appropriate weights of these criteria have been
determined using a novel interval-valued spherical fuzzy (IVSF) entropy
method. Four fuzzy ranking algorithms have been established to select
the proper well, and the achieved results have been combined using the
Borda method. To evaluate the robustness of experimental results, a
sensitivity analysis has been implemented. The proposed method not only
enhances the accuracy of OG reservoir selection but also reduces the
risk associated with conventional economic predictions for carbonate
reservoirs by considering the influencing factors of the development
process. Overall, this paper offers an efficient and effective approach
for selecting the best OG well alternative in the National Iranian Oil
Company (NIOC), which can be valuable for both managerial and technical
perspectives in the oil and gas sector.