Integrated optimization of oil well maintenance and production scheduling using dual-model knapsack-heuristic approach under rig resource constraints

Purpose This study addresses the challenge of optimizing maintenance and production scheduling in oil fields with limited workover rig availability, aiming to reduce production loss while meeting output targets. Design/methodology/approach A dual-model framework is introduced. The Production Target Decision (PTD) is formulated as a multiple-choice multiple knapsack problem and solved using a branch-and-bound algorithm with surrogate relaxation. The Production Loss Problem (PLP) is approached using a heuristic based on the Weighted Shortest Processing Time rule, enhanced by local search. Findings Applied to real-world data from four oil field regions, the model identifies the minimum number of rigs needed for feasible scheduling and significantly reduces production loss. The heuristic achieves near-optimal performance with minimal computational time. Originality/value Unlike prior studies that treat rig allocation and scheduling separately, this research presents an integrated, scalable optimization framework validated on operational datasets, bridging theory and practice in oilfield maintenance planning.