Employing Regression Analysis to Demonstrate the Impact of Hyperbolic Decline Curve Parameters on Long-Term Production Forecast Accuracy for Unconventional Oil and Gas Production in the Bakken and Barnett

Abstract

Forecasting production from unconventional reservoirs is challenging because of the uncertainty that arises from intricate fracture networks, complex transport mechanisms, and convoluted flow configurations. The accuracy of decline curve analysis for such reservoirs has been questioned due to the limited amount of long-term production data available. That being so, some unconventional reservoirs, such as the Bakken and the Barnett, have produced for 15-20 years, providing an adequate amount of data to validate the accuracy of the hyperbolic decline curve method, shed light on proper parameters – b and Di, and determine the amount of production history necessary to trust regression techniques. To test this, an extensive and versatile regression analysis model was built in Python using least squares optimization to match specific durations of production data – first 6 months, first year, first two years, etc. The model outputs the optimal parameters – b and Di –to match the specific duration. Additionally, fixed b values from 0.5 to 1.5 are tested where only Di is optimized through the model. To understand how accurately the models predict production, they are validated against the most recent 5 years of data, which was not included in the matching period. For a statistically significant sample size, around 700 wells in the Bakken and 1800 wells in the Barnett with start dates between 2005 and 2010 were used. The results show that in order to have confidence in the model's ability to predict production, more than 3 years of production data must be available. If 3 years of data is not available, the hyperbolic exponent, b, should be set close to 1.0 for Bakken wells (and likely other unconventional liquid rich wells) and between 1.0 and 1.2 for Barnett wells (and likely other unconventional gas wells). Additionally, the initial nominal decline rate, Di, should be chosen in accordance with the hyperbolic exponent. Not only do these guidelines result in satisfactory, long-term predictions, but they mitigate any significant error influenced by the underlying relationships between b and Di. These curve-altering relationships induce both positive and negative impacts on the predictions. If b is improperly chosen, overestimation in late-life production profiles may ensue. Alternatively, if Di is improperly chosen, early-life production may be too high. Since production forecasting is a necessity for a company to determine its present value, this paper provides knowledge and guidance regarding forecasting procedures and parameter settings for North American unconventional operators. Using decline curve analysis to accurately predict oil and gas rates is pertinent to the longevity of these unconventional reservoirs.