<![CDATA[Inefficient well restart scheduling is often caused by the limitations of conventional methods in handling operational and field complexity. This study proposes a solution in the form of implementing a backtracking algorithm in compiling an oil well restart schedule that is experiencing off-time. This algorithm is chosen because of its ability to systematically explore solutions through depth-first search and forward checking mechanisms to meet various operational constraints such as crew availability, geological conditions, and interconnectedness between wells. The purpose of this study is to develop a Constraint Satisfaction Problem (CSP)-based scheduling model that is able to minimize off-time and optimize resource utilization. The main contribution of this study is the integrative approach between the CSP model and the backtracking algorithm which has not been widely applied in the context of oil and gas operations. The interim results of simulations on historical data show that this method is able to reduce the average off-time by 25%, increase resource utilization efficiency by 28.6%, and accelerate the scheduling process by 66.7% compared to conventional methods. This approach shows significant potential in improving operational efficiency and supporting the digitalization of scheduling in the oil industry.]]>
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