Abstract

Cyclic Solvent Injection (CSI) is the most promising process for a post-CHOPS reservoir (Chang and Ivory 2012). Experimental studies suggest that oil recovery can reach up to 62% at the lab scale, which indicates the potential viability of the CSI process. This paper summarizes experimental results of six CSI tests with three physical models with different scales. Typical western Canadian heavy oil sample with a viscosity of 4830 cp at the reservoir conditions was used. Numerical simulation models were established to simulate these tests. The uncertainties in upscaling CSI process, such as relative permeability curve, capillary pressure, reaction rate in foamy oil model and dispersion coefficient were investigated by numerical simulation. In history-matched cases, the same relative permeability curves were obtained for these six CSI tests only with different capillary pressure. Sensitivity analysis illustrates that adding an appropriate capillary pressure in each test could refine the match results between simulation and experimental data. Generally, the larger the model is, the smaller the capillary pressure is. Therefore, the capillary pressure may be neglected in field scale applications. In addition, the location of the wormholes may affect the magnitude of capillary pressure employed in history-matched cases.

A typical western Canadian heavy oil post-CHOPS reservoir (M-reservoir) was employed to study the uncertainties during the CSI process by numerical simulation. The uncertain parameters include oil relative permeability, gas relative permeability, capillary pressure and dispersion coefficient. The Design of Experiments (DOE) method was utilized to define the simulation matrix, and 18 simulation cases, with 7 factors in 3 levels, were run. The multiple inferences were covered as much as possible. The oil recovery factor for ten-year production was selected as the response variable. The range between 18 estimates and "standard" value (14.611%) in terms of the recovery factor was from 0.04% to 1.42%. After that, the multiple-linear regression was performed to construct the response surface in DOE and the proxy equations were then generated. Three thousand Monte-Carlo simulations, in total, were performed to generate the probability distribution functions, which indicated that the P90, P50 and P10 estimates of the oil recovery factors were 14.08%, 14.69% and 15.33%, respectively. This study demonstrates that through simulating experiments from physical models with different scales, the uncertainties in predicting the field-scale CSI performance can be significantly reduced.

You can access this article if you purchase or spend a download.