Business/economics

Comparison of Empirical and Analytical Methods for Production Forecasting

Decline-curve analysis (DCA) is arguably the most commonly used method for forecasting reserves in unconventional reservoirs. This paper discusses its basic theory and application, together with the potential pitfalls of using simple empirical production-forecasting methods in complex reservoirs.

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Fig. 1—Forecasts for Barnett wells after 8.6 years of production.

Decline-curve analysis (DCA) is arguably the most commonly used method for forecasting reserves in unconventional reservoirs. This paper discusses its basic theory and application, together with the potential pitfalls of using simple empirical production-forecasting methods in complex reservoirs. Production data from several US unconventional plays are analyzed, and production forecasting is carried out with the traditional Arps methods as a basis for comparison. The results are compared with analytical models developed for each play to determine the suitability of each DCA method.

DCA Theory

At the most fundamental level, DCA involves fitting an empirical model of the trend in production decline from a well’s history and projecting the trend into the future to determine the well’s economic life and forecast cumulative production.

Arps Curves. The Arps decline model is established from the empirical observation that the loss ratio (the rate of change of the reciprocal of the instantaneous decline rate) is constant with time.

Power-Law Exponential (PLE) Method. The PLE relation draws on the classical Arps decline curves but uses a different description of the nominal decline-rate parameter (D). The PLE method assumes the loss ratio (1/D) is approximated by a decaying power-law function with a constant behavior at early time.

Duong Method. This rate-decline approach was developed specifically for fractured shale-gas reservoirs.

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