The application of "Decline Curve Analysis" (DCA) in unconventional reservoirs is almost always problematic. The Arps relations (hyperbolic and exponential relations) have been the standard for evaluating estimated ultimate recovery (EUR) in petroleum engineering applications for more than 80 years. However; with the pursuit of low and ultra-low permeability plays, these relations often yield ambiguous results due to invalid assumptions (e.g., existence of the boundary-dominated flow regime, presumption of a constant bottomhole pressure, etc.).

Misapplications of the Arps’ relations to production data exhibiting long-term, transient flow generally results in significant overestimates of reserves — specifically when the hyperbolic relation is extrapolated unconstrained, using an Arps b-value greater than 1. We note that the "modified hyperbolic" relation — one with an initial (unconstrained) hyperbolic trend used during early times, coupled with an exponential decline trend using a standard terminal decline can be used effectively (with proper care) for predicting EUR and production extrapolations. However; we note that this approach is "non-unique" in the hands of most users, and often yields widely varying estimates of reserves with time, and/or "consistent" estimates of reserves, which are highly biased.

In short, the modified hyperbolic relation can be effectively applied to production data from low/ultra-low permeability reservoirs systems, these analyses must be based on diagnostic interpretations of the data (as we have proposed earlier [Ilk et al. (2008)]), where multiple data functions are used to define the analyses. The use of diagnostics is a necessary, not a sufficient condition — the underlying models must be able to characterize the selected flow regimes, and there must also be constraints applied to production extrapolations and EUR predictions.

The issues related to the use of Arps’ rate decline relations have led various authors [Ilk et al. (Power Law Exponential, 2008), Valko (Stretched Exponential, 2009), Clark et al. (Logistic Growth Model, 2011), and Duong (2011)] to propose various rate decline relations which attempt to properly model the time-rate behavior — specifically early transient and transitional flow behavior. However, none of these equations can be considered sufficient to forecast production for all unconventional plays, due to the characteristics and operational conditions of each play and the behavior of the time-rate equation. In other words, one equation could work very well in a specific play, but could possibly perform poorly in another play. Under these circumstances, it is critical to understand the behavior of each equation, and to apply these relations appropriately for production forecasts.

This work presents guidelines for the application of the various time-rate relations currently being deployed in the petroleum industry. The results of time-rate analyses of wells from three different plays are presented, and the advantages/ disadvantages of each time-rate relation are discussed. Ultimately, our goal in this work is to define and demonstrate a process for the proper application of the time-rate analyses typically performed for production forecasting and EUR prediction.

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