Comparison of Empirical Decline Curve Methods for Shale Wells

Abstract

Analyzing shale wells using traditional decline curve methods is problematic because of the nature of reservoir properties and flow behavior in typical shale wells. New empirical methods were developed to model the special production decline of shales. These methods were formulated using different mathematical and statistical bases and result in different forecasts. Hence, engineers have a variety of methods that may give different estimates for ultimate recovery when analyzing shale wells. In this work, four recently developed decline curve methods, along with the traditional Arps method, were compared. The four recent methods compared here were empirically formulated for shale wells and tight gas wells. They are: a) the Power Law Exponential Decline, b) the Stretched Exponential Decline, c) Duong’s Method, and d) the Logistic Growth Model. Each method has different tuning parameters and equation forms. In this work, the methods were programmed and automated by using nonlinear regression to match the production "history" of a well. In addition, they were compared in terms of "goodness of fit" to the history data and reliability of automation as well as production forecast and ultimate recovery estimation. These methods were compared with simulation models in addition to field data from Barnett Shale, Bakken Shale, and the Eagle Ford Shale. Each of these methods may have application for different cases. It may be advisable to program each of these methods for optional usage in applications. But this current paper should allow engineers to understand better the characteristics of each method and to choose the method that best models their wells under various circumstances.

Production Decline Curves of Tight Oil Wells in Eagle Ford Shale

“…The advantages of these decline curves lie in their strong empirical compliance and ease of use. Some important properties of the hyperbolic and the stretched exponential curves are expressed in Table 1, from Valkó (2009), Hö ö k et al (2014), Satter et al (2008) and Kanfar (2013). Q(t) is the cumulative production at time t, and EUR is the estimated ultimate recovery of the well.…”

Methods of Decline Curve Analysis for Shale Gas Reservoirs

“…Their results show that the PLE model does not appear to provide any significant tangible advantage over the MHD model. Kanfar and Wattenbarger [12] proved that the PLE model is reliable for linear flow, bilinear flow followed by linear flow, and linear flow followed by BDF, or bilinear flow followed by linear flow and finished with BDF flow. Meyet et al [28] illustrated that the PLE model varies the least with respect to length of production history for all wells, and the PLE and LGA models usually return similar results.…”

“…Kanfar and Wattenbarger [12] showed that the Duong model is more accurate for linear flows and bilinear-linear flows. Meyet et al [28] showed that the EURs determined with PLE and Duong model vary the least with respect to the length of production history for all wells among all of the DCA methods in their study, and other DCA methods tend to converge towards the modified Duong model and PLE model.…”

“…Kanfar and Wattenbarger [12] compared five DCA methods explained in our study: Arps, PLE, SEPD, Duong, and LGM models. These models were compared by matching field data from Barnett shale and Eagle Ford shale.…”

“…These models start from the classical Arps model and end with the new Fractional Decline Curve model. There have been previous review works or comparison works for different DCA models, such as Kanfar and Wattenbarger [12], Joshi and Lee [13], Lee [14], and Hu et al [15], but there are a few new models proposed during the past several years and there is a need to include new applications of these DCA models in an updated review. This work will provide the most current theory and applications of DCA models in shale gas reservoirs.…”