Assessing the accuracy of empirical decline curve techniques for forecasting production in unconventional reservoirs: a case study of Haynesville, Marcellus, and Marcellus Upper Shale

Abstract

Abstract Decline curve analysis (DCA) is a widely used method to estimate the production performance and ultimate recovery of conventional and unconventional reservoirs. Due to the unconventional nature of shale wells, traditional decline curve methods are not ideal for analyzing their production decline behavior. In response, different empirical methods have been developed and used which rely on different mathematical and statistical approaches and can result in varying forecasts. This study compares fourteen decline curve methods, along with the traditional Arps method, in terms of their ability to match production history, sensitivity to data size, effect of flow type, production forecast, and ultimate recovery estimation. The methods were tested on three wells from Haynesville Shale (Lorikeet Field), Marcellus Shale (Ostrich Field), and Marcellus-Upper Shale (Penguin Field) respectively. The study concludes that each method may be useful in different cases, and engineers should choose the method that best models their wells based on their specific characteristics and circumstances. Recommendations were also provided for an effective evaluation of uncertainty and application of DCA. The primary objective of this study is to improve the accuracy and reliability of DCA predictions for different reservoir types with different declining modes.

Keywords

• Decline curve analysis production performance
• Ultimate recovery
• Oil and gas reservoirs, unconventional reservoirs
• Shale gas
• Uncertainty evaluation
• Haynesville shale