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Analyzing production data from tight oil wells

By: Publication details: may. 2011Description: 11 p. ; 48-58 In: Journal of Canadian Petroleum Technology 50Summary: Transcripción del resumen del autor. 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.
Item type: Artículo de Revista
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Biblioteca Alejandro Angel Bulgheroni Not for loan 200057526

Transcripción del resumen del autor. 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.

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