Forecasting Oil Production Rates in Primary Depletion using the Physics-based Residual Kriging functional approach

44/2022

Forecasting Oil Production Rates in Primary Depletion using the Physics-based Residual Kriging functional approach

Sunday 26th June 2022

Peli, R.; Dovera, L.; Fighera, G.; Menafoglio, A.; Secchi, P.

In this work, we illustrate a novel functional data analysis approach for the forecast of oil production rates in a mature single-phase reservoir. This model is based on the recently developed Physics-based Residual Kriging predictor, which represents oil rates as functional data and decomposes them as the sum of the predictions of a physical model and the geostatistical modelization of its residuals. In this context, we use the recently introduced FlowNet model to build up the physical term which, through a network-based representation of the reservoir, avoids the burden of three-dimensional full-physics simulations. Furthermore, we propose an extension of the Physics-based Residual Kriging predictor in presence of ensemble of physical models, i.e. when the uncertainty in the model parameters is accounted for by simulating several models corresponding to different parameters samples. The Physics-based Residual Kriging predictor is here applied to the oil rates produced in a realistic reservoir. We analyze three different scenarios in terms of wells drilling schedule, from a simple to a realistic scheme. In each scenario, we compare the predictions given by Physics-based Residual Kriging to the ones obtained with FlowNet and a pure geostatistical approach.