Extended exponential decline curve analysis

Abstract Over the last few years, the hydrocarbon production from shale plays has grown dramatically around the world. These unconventional resources have presented many challenges to the oil and gas industry. One of the biggest challenges for evaluators is to predict long-term shale production performance, especially in a timely and reliable manner. For traditional reservoirs, the most common practice of reserve evaluation is Decline Curve Analysis (DCA), a method with decided advantages; it is not only the simplest and least time-consuming method, but it also accommodates the historical field uncertainties by honoring observed performance trends. However, applying the traditional DCA method to shale wells, engineers commonly encounter the difficulties of simultaneously matching the high initial production rate, the extremely sharp decline rate in the transient flow period, and the shallow decline resulting from boundary-dominated flow (BDF) in late-life. This suggests that traditional DCA may not be suitable for evaluating shale reservoirs. As a result, numerical simulation seems to be the best solution to provide reliable results but at the expense of extensive manpower, cost, time, and data requirements. We propose an alternate DCA approach, which overcomes the shortcomings of traditional DCA or numerical simulation, to estimate the recoverable hydrocarbons. We suggest that a mechanism of “growing drainage volume” is an excellent way to conceptualize and model the performance of shale wells. This paper presents a new extended exponential form of the production decline analytical equation. Three empirical depletion terms, βe, βl, and n, have been used in the equation. The parameter βe represents the early, sharp decline in the transient period immediately after the well is put on production; the βl parameter represents the comparatively shallow decline in late-life when the progress of “growing drainage volume” plays the dominant role on the production performance; the parameter n is an empirical exponent. The overall decline rate can be calculated by a relationship involving, βe, βl, n, and time t. Even though the new method is not always more accurate than peer models, it is likely as accurate, and does not require the analyst to guess when to switch to a boundary-dominated flow model nor to force a switch to exponential decline. We have tested and verified this new empirical DCA by both extensive field data and detailed numerical simulation results for seven wells. For each of these data sets, the comparisons between traditional DCA methods, and in some cases simulations, indicate the relative advantages of this new approach. Later, we applied this method to over 2000 wells in the Eagle Ford shale. The analysis resulted in a relatively symmetric distribution for the empirical parameter n.