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.

The most commonly used technology for development of unconventional liquid-rich and light oil reservoirs is horizontal wells combined with large multi-stage hydraulic fracture treatments. However, even with these technological advancements, primary recovery factors are generally less than 10% (Shoaib and Hoffman, 2009) of the original oil in place (OOIP). Logically, operators have investigated the use of waterflooding to improve recovery in some tight oil reservoirs, but the success has been mixed. Low matrix permeability in some unconventional (tight) oil reservoirs will not allow effective displacement or movement of water through the reservoir. In some cases, even flooding with a gas will be a challenge, if matrix permeabilities are too low. This study investigates the feasibility of enhanced oil recovery (EOR) in a prominent tight oil reservoir in North America using cyclic solvent injection (CSI, sometimes referred to as "huff-n-puff") with carbon dioxide (CO2) as the solvent. CSI is a single well process, with the solvent remaining in the vicinity of the wellbore, as flow of the solvent through the reservoir to another well is not necessary. This type of process may be attractive from a capital cost point-of-view, as large expenditures on specialized facilities, in-field pipelines and well conversions are unnecessary. In this study, the success and profitability of huff-n-puff is evaluated for the Bakken tight oil reservoir. Knowledge gained from a parallel study (Kanfar and Clarkson, 2017) served to provide guidelines for optimizing the huff-n-puff process. Importantly, a genetic algorithm (GA) is utilized to find the optimum huff-n-puff program that maximizes net present value (NPV). Optimized parameters include: the number of cycles; duration of injection, soaking and production periods; and the start time of huff-n-puff operations. The target reservoir for evaluation is the US Bakken deep tight oil reservoir in North Dakota. The huff-n-puff EOR scheme was found to be successful, but only after the aforementioned operational parameters are optimized with GA. In particular, it is important to delay huff-n-puff until production rates decline and boundary-dominated flow (after fracture interference) is reached. Importantly, as with the parallel study (Kanfar and Clarkson 2017), the gridding scheme used in the simulation is found to have a profound impact on results of huff-n-puff.

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Evaluation of enhanced liquid recovery from tight or shale reservoirs is currently of great interest to operators. One reason is the low primary oil recovery of tight/shale reservoirs, which ranges between 5-10% (Shoaib and Hoffman, 2009) even after expensive multi-stage hydraulic fracture stimulation. Enhanced recovery using the "huff-n-puff" process could be an effective solution to increase recovery without drilling new wells. There are a number of published lab and simulation studies that investigate the efficiency of huff-n-puff in tight/shale reservoirs. These studies, however, have yielded contradictory results. For example, Chen et al. (2014) concluded that huff-n-puff has a negative impact on recovery while Yu et al. (2014) concluded that it improves recovery by 2-9%. These conflicting results underscore the need for further research. The current study, therefore, endeavors to investigate possible causes of these discrepancies. Compositional numerical simulation is used to investigate key simulation model setup and reservoir controls on huff-n-puff efficiency in tight reservoirs. Some of these controls have never been investigated for tight reservoirs, such as the influence of grid refinement, in-situ fluid composition, and fracture pore volume/hydraulic fracture representation. One important finding of this work is that grid refinement, and fracture pseudo width, greatly impact huff-n-puff results. The combination of coarse gridding and improper fracture representation through the pseudo width approach can lead to falsely optimistic incremental recovery associated with huff-n-puff relative to primary recovery. While the findings presented herein are useful in explaining possible causes of the discrepancies in results reported in previous work, they can also be used to improve huff-n-puff design. For example, the combination of fine fracture spacing in multi-fractured horizontal wells and increased fracture complexity can positively influence incremental recovery obtained from huff-n-puff. Further, the results suggest that huff-n-puff timing (with respect to primary production operations) should be carefully considered. This study will help simulation engineers improve their evaluations of huff-n-puff in tight/shales reservoirs. Additionally, it will help operators decide which reservoir is suitable for huff-n-puff operations to improve liquids recovery. Application of the findings of this study to actual field scenarios will be presented as a separate work.