Abstract
ABSTRACTIn the implementation of thermal enhanced oil recovery (TEOR) techniques, the temperature impact on relative permeability in oil–water systems (Krw and Kro) is of special concern. Hence, developing a fast and reliable tool to model the temperature effect on Krw and Kro is still a major challenge for precise studying of TEOR processes. To reach the goal of this work, two promising soft-computing algorithms, namely Group Method of Data Handling (GMDH) and Gene Expression Programming (GEP) were employed to develop reliable and simple to use paradigms to predict the temperature dependency of Krw and Kro. To do so, a large database encompassing wide-ranging temperatures and fluids/rock parameters, was considered to establish these correlations. Statistical results and graphical analyses disclosed the high degree of accuracy for the proposed correlations in emulating the experimental results. In addition, GEP correlations were found to be the most consistent with root mean square error (RMSE) values of 0.0284 and 0.0636 for Krw and Kro, respectively. Lastly, the performance comparison against the preexisting correlations indicated the large superiority of the newly introduced correlations. The findings of this study can help for better understanding the temperature dependency of Krw and Kro in TEOR.
Highlights
Nowadays, energy demand is expected to rise significantly with the increased prosperity in different sectors of industry and with the higher and continues consumption (Tillerson and others 2008)
This Group Method of Data Handling (GMDH) version corresponds to the earliest model that was introduced by Ivakhnenko
The temperature dependency of oil - water relative permeability correlations are developed with respect to the aforementioned inputs as follows: Kro = f(Sw, T, μo, μw, K)
Summary
Energy demand is expected to rise significantly with the increased prosperity in different sectors of industry and with the higher and continues consumption (Tillerson and others 2008). As fossil source is still the dominant spring of energy, there have been noticeable and significant efforts to promote the standards techniques to improve the outcomes from oil reservoirs (Olayiwola and Dejam 2019). Due to this fact, extraction of oil from unconventional reservoirs and oil with low API gravity has turned into quite important ways to compensate the expected need in the fossil energy (Meyer, Attanasi, and Freeman 2007). These temperature-based techniques for oil recovery are assembled beneath the umbrella of the so-called Thermal Enhanced Oil Recovery (TEOR)
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