Abstract
Abstract
Pore-scale dependent phase behavior describes a decrease in the hydrocarbon phase envelope as pore throat size decreases. This phenomenon is well documented in terms of confining effects on phase behavior with several analytical fluid models proposed that account for these effects. Results from a limited number of numerical reservoir models show the effects pore-scale phase behavior has on total production. However, fewer studies consider fluid transfer between different scale pore networks as a function of scale-dependent phase behavior. This work investigates fluid transfer between different scale pore networks related to scale-dependent phase behavior and the affects it has on production and fluid composition in the pore networks.
A commercially available reservoir simulator is used with a dual porosity/permeability grid and scale-dependent fluid models to study the fluid transfer between pore networks. Fluid tracking is used to trace fluid phases and components that originate in both the nanoscale and macroscale pore networks. Fluid transfer between pore networks is considered at both the pore network scale and at the well stream scale by tracking the fluid components from nano-scale pores into macro-scale pores and ultimately to the well bore. The results from the model are used to quantify fluid transfer between pore networks.
The results of the study show how the confining effects on fluid phase behavior affect fluid production rates and gas-oil ratios by linking the pore scale processes to the well stream scale production. For example, as fluid moves from the nanoscale pores, where the bubble point is suppressed and the fluid retains the initial solution gas-oil ratio (Rs), into the macro scale pores, the fluid in the macroscale pores is enriched by the nanoscale pore fluid.
This work provides three main contributions to an improved understanding and characterization of unconventional plays. The first is demonstrating the ability to simulate the confining effects on fluid phase behavior using commercially available reservoir simulators. Second is the ability to capture some of the unique production trends observed for tight oil reservoirs, e.g., extended periods of stable GOR, when modeling these reservoirs. The third contribution is in tight oil EOR, providing insight into the composition of the fluid that remains in the pore networks following primary depletion or at the onset of an EOR process.