Estimation of oil reservoir parameters from temperature data for water injection

Fluids and oil flow rate, oil saturation and reservoir porosity as well as their measure method play a key role in petroleum engineering. Based on analysis of heat and mass transfer for hot water injection reservoir, this study presents a novel method to estimate the above parameters of oil reservoir simultaneously just from temperature data. The proposed method is an inversion method coupling with Monte Carlo stochastic approximation method. Firstly, a two-phase flow and heat transfer model in core flooding for hot water injection reservoir was built to simulate the reservoir temperature. Then, based on the built model, the concerned parameters were estimated sequentially by the inversion method from the reservoir temperature data which was obtained in a built experiment. Moreover, for determining sequence of parameters inversion, sensitivity analysis was performed to investigate correlation between the estimated parameters and reservoir temperature. Lastly, applying the presented method to two experimental water injection reservoirs, the transient flow rate, oil saturation and porosity during oil displacement were obtained. The prediction errors of oil flow rate and oil saturation for were less than 10% at all times, especially, the mean prediction accuracy for oil flow rate could reach 1.9%, and the mean accuracy for the oil saturation was about 2.0%.