Summary Performance prediction of wells producing from tight (microdarcy) formations is a daunting task. Complexities of geology (the presence/absence of naturally occurring fractures and contribution from different lithological layers), completion and fracture geometry complexities (multiple transverse or longitudinal fractures in long horizontal boreholes), and two-phase flow are impediments to simple performance forecasting. We demonstrate the use of various analytical and numerical tools to learn about both short- and long-term reservoir behaviours. These tools include (a) traditional decline-curve analysis (Arps 1945), (b) Valko's stretched-exponential (SE) method (Valko 2009), (c) the Ilk et al. (2008, 2010) power-law exponential (PLE) method, (d) rate-transient-analysis (RTA) and transient-PI analyses to ascertain the stimulated-reservoir volume (SRV), and (e) numerical-simulation studies to gain insights into observed flow regimes. The benefits of collective use of analytical modelling tools in history matching and forecasting both short- and long-term production performance of tight oil reservoirs are demonstrated with the use of real and simulated data. Diagnosing natural fractures, quantifying stimulated-reservoir volume, and assessing reliability of future performance predictions all became feasible by using an ensemble of analytical tools.

Performance prediction of wells producing from tight microdarcy formations is a daunting task. Complexities of geology (the presence/absence of naturally occurring fractures and contribution from different lithological layers), completion and fracture geometry complexities (multiple transverse and/or longitudinal fractures in long horizontal boreholes), and two-phase flow are impediments to simple performance forecasting. We demonstrate the use of various analytical and numerical tools to learn about both short- and long-term reservoir behaviors. These tools include (a) traditional decline-curve analysis (Arps formulation), (b) Valko's stretched-exponential method, (c) Ilk et al's power-law exponential method, (d) rate-transient and transient-PI analyses to ascertain the stimulated- reservoir volume, and (e) numerical simulation studies to gain insights into observed flow regimes. The benefits of collective use of analytical modeling tools in history-matching and forecasting both short- and long-term production performance of tight-oil reservoirs are demonstrated with the use of real and simulated data. Diagnosing natural fractures, quantifying stimulated-reservoir volume, and assessing reliability of future performance predictions, all became feasible by using an ensemble of analytical tools.