Using Improved Decline Curve Models for Production Forecasts in Unconventional Reservoirs

Abstract

Abstract The flow behavior in nano-darcy shales neighbored by high conductivity induced natural fractures violates the assumptions behind Arps' decline models that have been successfully used in conventional reservoirs for decades. Current decline curve analysis models such as Logistic Growth Analyses, Power Law Exponential and Duong's model attempt to overcome the limitations of Arps' model. This study compares the capability of these models to match the past production of hundred shale oil wells from the Eagle Ford and investigate how the choice of residual function affects the estimate of model parameters and subsequently the well life, pressure depletion and ultimate recovery. Using the proposed residual functions increased the tendency of deterministic models to have bounded estimates of reserves. Results regarding well performance, EUR, drainage area and pressure depletion are obtained quickly and show realistic distributions supported by production hindcasts and commercial reservoir simulators. Overall, the PLE and Arps' hyperbolic models predicted the lowest/pessimistic and highest/optimistic remaining life/reserves respectively. The newly proposed residual functions were thereafter used with the Arps' hyperbolic and LGA models. We found that the use of rate-time residual functions increased the likelihood of the value of hyperbolic exponent being less than 1 by 87.5%. The proposed residual functions can be used to provide optimistic and conservative estimations of remaining reserves and remaining life using any of the above decline models for economic analysis. The key results provided by the modified DCA models help in long-term planning of operations necessary for optimal well completions and field development, accomplished in a fraction of the time currently required by other complex software and workflows.