Machine learning approaches for estimating interfacial tension between oil/gas and oil/water systems: a performance analysis

Abstract

Interfacial tension (IFT) is a key physical property that affects various processes in the oil and gas industry, such as enhanced oil recovery, multiphase flow, and emulsion stability. Accurate prediction of IFT is essential for optimizing these processes and increasing their efficiency. This article compares the performance of six machine learning models, namely Support Vector Regression (SVR), Random Forests (RF), Decision Tree (DT), Gradient Boosting (GB), Catboosting (CB), and XGBoosting (XGB), in predicting IFT between oil/gas and oil/water systems. The models are trained and tested on a dataset that contains various input parameters that influence IFT, such as gas-oil ratio, gas formation volume factor, oil density, etc. The results show that SVR and Catboost models achieve the highest accuracy for oil/gas IFT prediction, with an R-squared value of 0.99, while SVR outperforms Catboost for Oil/Water IFT prediction, with an R-squared value of 0.99. The study demonstrates the potential of machine learning models as a reliable and resilient tool for predicting IFT in the oil and gas industry. The findings of this study can help improve the understanding and optimization of IFT forecasting and facilitate the development of more efficient reservoir management strategies.

Sandstone chemical consolidation and wettability improvement using furan polymer-based nanofluid

“…Typically, the surface of sandstone rock formations tends to be water-wet, while carbonates tend to be oil-wet 37 . In chemical consolidation operations, wettability alteration may be induced as a result of chemical reactions and ion exchange between the rock and consolidation fluid 38 . Therefore, where the infiltration of chemical fluids can cause formation damage and permeability reduction, monitoring changes in wettability is necessary, as shifting toward water-wettability in the formation rock can enhance the relative permeability of water, increase oil production, and partially compensate the damage caused by the chemical fluid curing in the pores.…”

A comparative study of brine solutions as completion fluids for oil and gas fields

“…This has a huge effect on how badly formations are damaged in oil reservoirs. Predicting how wettability will affect formation damage is hard because it changes over time and is affected by interactions between rocks and fluids as well as changes in the conditions of the reservoir 45 , 46 . Wettability, characterized by contact angles and correlated with surface tension, plays a pivotal role in oil reservoirs.…”