Traditional rate-transient analysis (RTA) is used to match the past and forecast the future production history of unconventional wells. This approach has several drawbacks: (a) the analysis of a single well is time-consuming, (b) it uses two approximate transformations: rate normalization and material balance time, and (c) the interpretation is subjective. Recently, we have developed a new variable pressure decline-curve analysis (DCA) method. This new approach delivers fast and accurate history matches and forecasts, removing the need for subjective interpretation and avoiding potential errors caused by rate normalization and material balance time transformations. The goal of this paper is to apply of this new variable pressure DCA method to unconventional reservoirs in Argentina.
The new variable pressure DCA technique performs sequential optimizations. In each iteration, the algorithm sequentially estimates: (1) the reservoir model parameters, (2) the pressure change, and (3) the initial reservoir pressure. The outputs of the method are the following: (a) the model's parameters, (b) the production history-match, and (c) estimates of the bottomhole flowing pressure (BHP) and initial reservoir pressure. In addition, the technique allows the user to select any decline-curve model, numerical, analytical, or empirical model. We illustrate the application of the technique for a tight-oil and a shale gas well using three different models: the constant-pressure solution of the diffusivity equation, the logistic growth model, and the Arps hyperbolic relation.
The analysis of production from unconventional wells shows that the new technique provides excellent production history-matches using different reservoir models. We show that the estimated BHP using our technique is in good agreement with the calculated BHP for the wells under study. Furthermore, the technique is computationally fast; it only requires around 20 seconds to analyze and history-match the production of a well. For the tight-oil well, we perform a hindcast analysis using only the flowback data to match the model parameters which were then used to forecast the production history with excellent agreement. The method provides the possibility to history-match and estimate the future behavior of wells under different choke management scenarios.
This work illustrates the application of a recently developed variable pressure DCA technique that efficiently performs automated production history-matches and forecasts of unconventional reservoirs. The technique provides improved estimates of the BHP and initial reservoir pressures. It can be used with any decline model. In addition, the method is computationally inexpensive and does not require the use of diagnostic plots and the interpretation of a practitioner. The major contributions of the present method are its flexibility to incorporate any decline-curve model and its speed to analyze and history-match the production of unconventional wells. Finally, we developed a web-based application to provide readers with a hands-on experience of this new technique.
