Integrated Optimization of Hybrid Steam-Solvent Processes in a Post-CHOPS Reservoir With Consideration of Wormhole Networks

Abstract

Abstract In this paper, an integrated technique has been developed to evaluate and optimize performance of hybrid steam-solvent processes in a post-CHOPS reservoir with consideration of wormhole networks. A reservoir geological model is developed and calibrated by history matching reservoir pressure with the oil, gas, and water production rates as the input constraints, while its wormhole network is characterized with a newly developed pressure-gradient-based (PGB) sand failure criterion. Once calibrated, the reservoir geological model incorporated with the wormhole network is then employed to evaluate and optimize performance of hybrid steam-solvent processes under various conditions, during which the net present value (NPV) is maximized with an integrated optimization algorithm by taking injection time, soaking time, production time, and injected fluid composition as controlling variables. It is found that a huff-n-puff process imposes a positive impact on enhancing oil recovery when wormhole network is fully generated and propagated. Among all solvent-based methods, a pure CO2 huff-n-puff process shows a better performance than flue gas, while the addition of alkane solvents leads to a higher oil recovery compared with that of the CO2 only method. Since the addition of C3H8 and n-C4H10 will significantly decrease heavy oil viscosity and enhance oil swelling, all hybrid steam-solvent injection achieves high oil recovery by taking advantage of both thermal energy and solvent dissolution. It is found that the NPV reaches its maximum of C$5.36 × 107 when the steam temperature is 200°C for the optimized hybrid steam-solvent scenario.