Modeling of fluid flow in unconventional reservoirs requires accurate characterization of complex flow mechanisms because of the interactions between reservoir rocks, microfractures, and hydraulic fractures. The pore size distribution in shale and tight sand reservoirs typically ranges from nanometers to micrometers resulting in ultralow permeabilities. In such extremely low permeability reservoirs, desorption and diffusive processes play important roles in addition to heterogeneity-driven convective flows.

For modeling shale and tight oil and gas reservoirs, we can compute the well drainage volume efficiently using a Fast Marching Method (FMM), and by introducing the concept of “Diffusive Time of Flight” (DTOF). Our proposed simulation approach consists of two decoupled steps - drainage volume calculation and numerical simulation using DTOF as a spatial coordinate. We first calculate the reservoir drainage volume and the DTOF using the FMM, and then, the numerical simulation is conducted along the 1D DTOF coordinate. The approach is analogous to streamline modeling whereby a multidimensional simulation is decoupled to a series of 1-D simulation resulting in substantial savings in computation time for high resolution simulation. However, instead of a convective time of flight, a ‘diffusive time of flight’ is introduced to model the pressure front propagation.

For modeling physical processes, we propose a triple continua whereby the reservoir is divided into three different domains: micro-scale pores (hydraulic fractures and microfractures), nano-scale pores (nanoporous networks), and organic matters. The hydraulic fractures/microfractures primarily contribute to the well production, and are affected by rock compaction. The nanoporous networks contain adsorbed gas molecules, and gas flows into fractures by convection and Knudsen diffusion processes. The organic matters act as the source of gas. Our simulation approach enables high resolution flow characterization of unconventional reservoirs because of its efficiency and versatility. We demonstrate the power and utility of our approach using synthetic and field examples

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