Abstract
Recently, as a result of the increasing exploration and production activity in unconventional plays, new decline curve models have been developed. The main purpose of these newer models—e.g., SEPD, Duong, Logistic Growth, Power Law, Dual-Models—is to overcome the boundary-dominated flow assumption required for validity of the basic Arps’ model, which restricts its application in ultra-low permeability reservoirs exhibiting long-duration transient flow. These new decline curve analysis (DCA) methods are still ordinarily applied only to rate-time data, and thus rely on the assumption of stable (constant) flowing pressure. Since this stabilized state is not reached rapidly in most unconventional wells, the applicability of these methods and the reliability of their forecasts may be compromised. In addition, production performance predictions cannot be disassociated from the operational constraints that existed when production history was observed.
This paper introduces a modified decline curve analysis method we call Pressure Normalized Decline Curve Analysis (PN-DCA) to provide a solution to these problems. Unlike traditional DCA methodology, which analyzes only production rates, this method analyzes pressure-normalized rates. To validate the applicability of this technique, we used hindcasting analysis of real production data from four different shale plays in the US (Eagle Ford, Woodford, Marcellus and Bakken). We found that this technique can be used as a reliable production forecasting technique suited to interpret unconventional well data in specific situations such as unstable operating conditions, limited availability of production data (short production history), and high-pressure, rate-restricted wells. Moreover, this method has proved to have the important ability to dissociate the estimation of future production performance from past operation constraints.
This work also proposes an innovative decline curve analysis workflow, which includes a multi-method approach to optimize the flow regimes identification process. This methodology integrates different diagnostic plots that have been improved by incorporating important concepts such as MBT, pseudo-variables (for gas wells) and pressure-normalized rates. Each DCA model has been designed assuming specific flow regimes. Therefore, a proper identification of dominant flow regimes will help us to perform decline curve analyses with more confidence and to avoid unrealistic production forecasts.
In general, incorporating pressure-normalized rates in decline curve analysis offers the possibility of producing improved forecasting results, which implies greater accuracy in production performance predictions and more reliable reserves estimations. The petroleum industry may become more confident in reserves estimates, which are the basis for the design of development plans, investment decisions, and valuation of companies’ assets.
