Recently it has been demonstrated that flowback data obtained immediately after fracture stimulation of multi-fractured horizontal wells (MFHWs) completed in tight/shale reservoirs may be analyzed quantitatively for hydraulic fracture properties. However, the initial conditions of fluid pressures and saturations at the start of flowback, which are a critical starting point for flowback simulation, are generally unknown and must be approximated. In order to properly initialize flowback simulations, the pre-flowback fracture stimulation treatment, as well as post-treatment shut-in period, should first be modeled in order to provide a reasonable estimate of fluid pressures and saturations within the hydraulic fracture and adjacent reservoir. In recent work, the authors developed a semi-analytical model to history-match flowback and early-time production data of MFHWs completed in tight oil reservoirs using the "dynamic drainage area" (DDA) concept. The model assumes that each fracture stage consists of a primary hydraulic fracture (PHF) region, and an adjacent enhanced fracture region (EFR) or non-stimulated region (NSR) in the reservoir. However, initial fracture fluid pressure in the PHF, and fluid pressure/saturation distributions in the adjacent EFR/NSR are required for the model initialization and are highly uncertain. In the current work, flowback data from a previously-analyzed MFHW horizontal well completed in a tight oil reservoir is revisited to determine if flowback initial conditions could be constrained rigorously. For this purpose, frac modeling (net-pressure analysis) was first performed using fracture treatment data for the well and commercial and publically-available simulators to constrain PHF property input for the DDA flowback model. The DDA model, run in injection mode, was then used to calculate the frac fluid leakoff rate from the PHF to the NSR during the fracture treatment, using the field frac pressures as input. Importantly, leakoff is modeled more rigorously using the DDA model than for the frac simulator, because it accounts for two-phase flow and stress-dependent permeability. Leakoff after the fracture treatment and before the flowback period was also modeled using the DDA approach to estimate the pre-flowback NSR fluid saturations and pressures, which served as the initial conditions for flowback modeling. The amount of leakoff estimated with the model is relatively small in this case, in part due to the small volumes of fluid used in the fracture treatment and low permeability of the reservoir. The resulting flowback history-match (also performed using the DDA model, in flowback mode) is similar to that achieved previously because the pre-flowback leakoff modeling resulted in only a slightly elevated water saturation estimate over virgin reservoir conditions. The results of this innovative approach to flowback modeling should be of interest to those petroleum engineers interested in quantitative analysis of flowback data to obtain fracture properties, but who are concerned about correct initialization of models for flowback simulation leading to more realistic results.
After hydraulic fracture treatment, wells typically produce significant volumes of water, which is primarily recovered fracturing fluid. The amount of fracturing fluid produced back is called load recovery. Single phase water production may continue for several days before oil breakthrough from the formation occurs. A wide range of load recoveries (15%–80%) are reported in the literature, depending on various reservoir, fracture, pumping and operational parameters. This study conducts a comprehensive numerical and statistical analysis to identify the most important parameters affecting load recovery. The sensitivity of oil breakthrough time to these parameters is also investigated. A fit-for-purpose model was created using a commercial coupled reservoir flow/geomechanics simulator to simulate fracturing treatment and flowback operations. Water and oil production trends, and flow regimes observed in the model, are verified using rate-transient analysis (RTA). The effect of twenty parameters including pumping rate, shut-in time, producing bottomhole pressure, production rate constraint, matrix porosity and permeability, matrix and hydraulic fracture compressibility, relative permeability end points and capillary pressure on load recovery and oil breakthrough time is investigated by utilizing Design of Experiment (DOE). The developed model considers non-uniform leak-off during pumping, providing a better understating of water retention, while the application of the DOE method allows the effect of various parameters and their interaction to be studied rigorously. A critical finding is that the majority of total load recovery occurs within the first three months of production. Furthermore, matrix permeability, shut-in time, connate water saturation and fracture compressibility, were found to be the most dominant factors, which can impact the load recovery by up to 22%, 15%, 14%, and 13%, respectively. Matrix permeability, production rate constraint, fracture residual oil saturation and shut-in time are four of the prominent parameters affecting oil breakthrough time. Understanding the impact of operational parameters such as shut-in time and production rate can help industry to implement recycling/disposal options and ultimately optimize load recovery. This can also create significant environmental compliance benefits for operators in addition to benefitting operational efficiency.
Recently, several authors have explored new methods for quantitatively analyzing multi-phase flowback data from multi-fractured horizontal wells (MFHW) to extract both fracture and reservoir parameters. These techniques provide much of the same information as long-term rate-transient analysis (RTA), although in a much shorter period of time. Flowback analysis is complicated by a rapidly changing fracture network and wellbore environment, multi-phase flow in the fractures (and possibly the reservoir), completion heterogeneity, as well as other effects which are often not present, or are ignored, when analyzing long-term (online) production data. For quantitative flowback analysis, the current authors have previously presented data-driven, pseudo-analytical methods for estimating key fracture properties (i.e. conductivity and half-length) from high-frequency, short-duration production test data. Models have been developed for both oil and gas wells representing a variety of reservoir and operating conditions. In this work, the models and procedures are extended to apply to more challenging reservoir/completion scenarios and are used in the analysis of several case studies from Canada. Each of the case studies demonstrate either the potential value add of the developed techniques, or a unique extension to the basic analysis methods. The case studies analyzed herein focus on light tight oil plays and consider layered reservoirs, multi-well flowback, and oil fracs in oil reservoirs. Further, the potential capital savings associated with conducting quantitative flowback analysis of early-time production test data is demonstrated. Each case study therefore presents a unique set of challenges that are often encountered in the real world. Numerical simulations are used to validate the sequence of flow-regimes depicted in the models. The methods presented in this paper will serve to partially satisfy the demands of industry to develop new methods for characterizing hydraulic fractures and forecasting production, particularly early in the well life. Through the use of several unique case studies, the wide-spread applicability and versatility of the techniques is demonstrated.
A fit-for-purpose, fully coupled stress-pore pressure simulation model (Abaqus®) is used to simulate diagnostic fracture injection tests (DFITs) and generate before closure pressure responses. The simulated responses are used to explain field observations, and to propose a new concept: progressive fracture closure. The cohesive zone model (CZM) is used to model fracture propagation and closure associated with DFITs. The customized model in Abaqus® is capable of modeling all the physical processes involved in a typical DFIT including: porous media deformation? fluid flow inside the reservoir? hydraulic fracture initiation, propagation and closure? compliance change before and after closure; residual fracture conductivity? and fluid flow inside the fracture and fluid interaction between the fracture and reservoir (leakoff). A key result obtained is that the previously-introduced fracture compliance method is demonstrated to be the most reliable approach to identify fracture closure. Depending on the pressure distribution around the fracture, the closure pressure is usually found to be higher than the minimum principal stress. Based on the continuity equation, the compliance method is expanded to include the progressive fracture closure (PFC) concept. PFC refers to the scenario where fracture closure occurs gradually along the length of fracture, from the tip of the fracture to near the wellbore. Different estimates of closure pressure will be obtained early and late in this process. Several field cases are presented which exhibit progressive fracture closure. A consistent closure signature can be identified for these cases using the primary pressure derivative. This study further suggests that wellbore storage can mask the closure signature. Therefore, reducing the wellbore storage effect by using downhole shut-in makes it easier to identify fracture closure, in addition to accelerating the test. A common DFIT fracture closure referred to as "fracture height recession" is reinterpreted to be caused by the PFC phenomenon. This finding has tremendous implications for interpretation of before closure flow regimes and associated reservoir behavior. This study also confirms that the compliance method, which corresponds to fracture tip closure, provides more of a true measure of closure pressure than conventional approaches which correspond to fracture closure near the well.
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