An Intelligent Selection Model for Optimum Artificial Lift Method Using Multiple Criteria Decision-Making Approach

Abstract

The urge to design a selection model for a proper artificial lift system is noticeably escalating. It becomes prudent for the operator to consider most, if not all, of the available evaluation and selection methods. The concept behind it is to yield improved production at better conditions than could be expected. The artificial lift includes five methods, and it is very crucial to select the best method considering the field conditions. In this paper, the best artificial lift is selected using multiple criteria decision-making model which is composed of the combination of Technique for Order Preference by the Similarity to Ideal Solution (TOPSIS) and the Analytic Hierarchy Process (AHP). This new user-friendly model undertakes 15 essential technical factors sorted into three sets (well data, reservoir data, and quantitative data) each factor has its own weight in the final selection decision. Furthermore, the Results depicted in bar graph for further illustration. It is important to note that the final decision is entirely based on technical manners. Additional economic evaluation and detailed cost analysis are required when the model results in close outputs between alternatives. Lastly, this integrated model was tested on 12 wells from block-4 and Block-6 in Sudan, inputs were real-time data from initial and status. Successfully, in the end, it yielded its theoretical results.