Modelling of Gas Exsolution and Transport in a Live Heavy Oil Reservoir

摘要

Depressurization causes the exsolution of dissolved gases as bubbles within the live heavy oil reservoirs. The exsolution of bubbles increases the fluid volume within the reservoir, forcing both oil and bubbles to the well. Subsequently, growth and coalescence lead different sizes of gas bubbles accumulation in the producing zone which mainly controlled by viscous and capillary forces. Laboratory data show a significant amount of gas bubbles become trapped in the flow system. This entrapment of the gas phase results in higher critical gas saturation. Modelling of gas bubble exsolution and transport is vitally important in designing production technology for improving oil recovery. This project was devoted to develop a mechanistic foamy oil model for quantifying gas exsolution and transport which can operate within the commercial reservoir simulator. The foamy oil model has been completed in two parts: In Part 1, a kinetic model with five components and four reactions was developed to simulate gas exsolution in a live heavy oil reservoir. The kinetic model coupled with the commercial simulator (CMG STARS) was applied to history matching of several laboratory gas exsolution experimental data. Performance of the model in special form under different flow regimes has been presented at the 2005 SPE/PS-CIM/CHOA Symposium. In Part 2, we developed a set of analytical functions to quantify gas bubbles partition and gas-oil relative mobility in reservoir porous media as function of capillary number. In this paper, the foamy oil model in generalized form is systematically presented: (1) history matches of mercury withdrawal experiments – studying the gas exsolution parameters with capillary number, (2) analysis of micro-model tests – developing a gas bubbles partition function depending on capillary number, and (3) history matches of radial drainage pressure depletion experiments – developing a set of relative permeability alteration functions depending on grid block capillary number for field scale modeling.