Multi-criteria optimization of sucker rod pump operation using AHP-TOPSIS based decision analysis for predictive paraffin control

This study presents an integrated methodological framework for optimizing the operation of sucker rod pumps affected by paraffin deposition through the application of multi-criteria decision-making techniques. Predictive maintenance (PdM) data collected from five production wells were analyzed to evaluate performance indicators before and after implementation of paraffin control procedures. The Analytic Hierarchy Process (AHP) was used to determine the relative importance of key performance criteria (post-PdM downtime, reduction percentage, and post-maintenance operational stability) and the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) ranked the wells according to their overall efficiency and reliability. Results indicated that well K-3 had the highest overall performance, with minimal downtime and low operational variability; wells K-1 and K-5 followed in the ranking. The combined AHP-TOPSIS approach provided a systematic decision support tool for prioritizing investments in automation, monitoring and maintenance strategies within oil production systems. The findings indicate that integrating MCDM methods with predictive maintenance data improves the accuracy of decision making and supports operational optimization in petroleum production environments.