Perpustakaan Digital ITB

Oil extraction from diminishing resources, especially waxy crude oil reservoirs, requires enhanced oil recovery (EOR) procedures. Effective enhanced oil recovery (EOR) requires precise interfacial tension measurement. This study forecasts interfacial tension in waxy crude oil from Indonesia's T-KS Field using advanced machine learning methods, specifically the ANN algorithm. The work aims to provide a cost-effective and reliable interfacial tension estimate method that overcomes traditional methods' drawbacks. To ensure accurate predictions, the suggested artificial neural network (ANN) strategy uses creative preprocessing, rigorous model evaluation, and a large dataset. The suggested artificial neural network (ANN) strategy uses creative preprocessing, rigorous model evaluation, and a large dataset to ensure accurate predictions. The ANN model beats current methods, suggesting it could greatly enhance interfacial tension estimate efficiency and accuracy. This work advances enhanced oil recovery (EOR) and oil extraction in waxy crude oil reservoirs. This study can revolutionize oil and gas interfacial tension estimation. More efficient and cost-effective oil recovery (EOR) operations will help the sector meet rising global energy needs.