Application of Artificial Intelligence to Predict Enhanced Oil Recovery Using Silica Nanofluids

Nasr, Mahdi Shayan; Nasr, Hossein Shayan; Karimian, Milad; Esmaeilnezhad, Ehsan

doi:10.1007/s11053-021-09829-1

Cited by 15 publications

(1 citation statement)

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“…After primary production, approximately two-thirds of the initial oil in place is expected to remain in the reservoirs. Enhanced oil recovery (EOR) methods which have become a main subject in petroleum engineering to meet the demand for energy will extract enough oil to fulfill a significant portion of the global oil demand [ 1 ]. As an EOR method, chemical flooding has been a popular strategy for improving oil recovery in mature oil fields that is now carried out using a variety of chemical agents and it has been shown to be successful [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

Artificial Neural Network to Forecast Enhanced Oil Recovery Using Hydrolyzed Polyacrylamide in Sandstone and Carbonate Reservoirs

2021

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Polymer flooding is an important enhanced oil recovery (EOR) method with high performance which is acceptable and applicable on a field scale but should first be evaluated through lab-scale experiments or simulation tools. Artificial intelligence techniques are strong simulation tools which can be used to evaluate the performance of polymer flooding operation. In this study, the main parameters of polymer flooding were selected as input parameters of models and collected from the literature, including: polymer concentration, salt concentration, rock type, initial oil saturation, porosity, permeability, pore volume flooding, temperature, API gravity, molecular weight of the polymer, and salinity. After that, multilayer perceptron (MLP), radial basis function, and fuzzy neural networks such as the adaptive neuro-fuzzy inference system were adopted to estimate the output EOR performance. The MLP neural network had a very high ability for prediction, with statistical parameters of R2 = 0.9990 and RMSE = 0.0002. Therefore, the proposed model can significantly help engineers to select the proper EOR methods and API gravity, salinity, permeability, porosity, and salt concentration have the greatest impact on the polymer flooding performance.

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Section: Introductionmentioning

confidence: 99%