Jurnal Institusi
Copyright (c) 2024 ComniTech : Journal of Computational Intelligence and Informatics
The variation in the performance of the oil wells in the Limau Field of Pertamina Hulu Rokan Regional 1 Zone 4 poses a challenge to the management and operational decision making. Basic segmentation and lack of visualization of well groupings based on their production potential characteristics can lead to inefficient resource allocation and improper decisions. This study aims to segment oil wells using K-means clustering to improve management effectiveness. The data used include gross production, net production, and water content (BSW). Clustering is performed to group wells based on their production potential characteristics in order for managerial decisions to be based on data-driven decision making. The evaluation process using Elbow Method and Davies-Bouldin Index showed optimal results with three clusters as the best number of centroids. The segmentation results provide a deeper insight into the well's production potential and support the optimization of resource allocation to improve well performance. It is anticipated that this research will make a substantial contribution to the improvement of operational efficiency and strategizing future oil well management with a data-driven approach.
ComniTech : Journal of Computational Intelligence and Informatics ; Vol. 1 No. 2 (2024): ComniTech : Journal of Computational Intelligence and Informatics; 67-75
Penerbit: Universitas Lancang Kuning