Prediction of the surface tension of gas-based nanofluids + model oils system by CPA EoS: Implementation in the simulation of by-passed oil recovery from a single block matrix of fractured reservoirs fully-immersed in the nanofluids

Abstract

By increasing oil drainage from the gas-invaded zone of fractured reservoirs, the capillary force resists and a huge volume of the in-place oil is by-passed in the matrix blocks where the main recovery mechanism is gravity drainage. In this work, the effectiveness of the injection of gas-based nanofluids for the recovery of the by-passed oils is analyzed. Asphaltene was extracted from a dead oil sample and characterized. Model oils of asphaltene in n-heptane/toluene (heptol) solutions were prepared and the surface tension of the model oils + air was measured by pendant drop tensiometry. Cubic plus association equation of state (CPA EoS) with tuned parameters exhibits precise predictions of the surface tension data. The asphaltene self-association energy in the gas-liquid interface is found to be lower than that in the bulk of the liquids. This implies that the configuration of the asphaltene molecules in the bulk and the interface is not the same. The CPA EoS exhibits reasonable predictions of the surface tension of gas-based nanofluids + air system. Using the CPA EoS and the principles of the gravity displacement, a mathematical model was developed for the simulation of the by-passed oil recovery from a single matrix block fully-immersed in the gas-based nanofluids. It is found that, although the oil recovery is enhanced slowly by the nanofluids injection, no plateau is observed in the recovery factor curves in short injection times. The diffusion coefficient of the nanoparticles in the matrix block plays a key role in the by-passed oil recovery by the injection scenario.