Shale gas/oil wells are a challenge due to the complex reservoirs and well completion designs. Commercial simulators with new automatic features play an important role in shale reservoir characterization. These commercial simulators include special features for modeling horizontal, multi-fracked shale wells with simplified user interfaces. The primary goal of this paper is to compare the simulation of transient and boundary dominated flow with analytical solutions through specialized rate function plots. These comparisons provide a straightforward means for testing the accuracy of automatic gridding features and the simulation methodology. If simulators can match idealized reservoirs accurately, then confidence improves in the matching of actual field cases that may vary from idealized reservoir behavior. In this work, we tested the accuracy of these simulator features by making numerous simulation runs for various geological and geometric scenarios. We considered different simulation gridding and system models to correctly represent the transient linear flow and its effect on the analysis. Some general gridding rules were developed. This work investigates the use of an effective permeability equation from analytical solution and its application to several wells in reservoirs located in the Bakken, Barnett, and Eagle Ford formations. Simulation was used to confirm the equation’s accuracy and to show its applicability in fractured shale reservoirs. Results from this investigation should help engineers select the best automatic features to accurately represent shale wells and then cross check the results using the analytical solution. This study also expanded our understanding of flow behavior in production data which may be used to improve modeling shale wells for better agreement with the analytical solutions.

Enhanced oil recovery in unconventional plays has been a focus of many E&P operators to increase recovery factors. Conventional displacement-based secondary (e.g. water flooding) and tertiary EOR methods are not viable options due to their low injectivity in these ultra-low permeability formations. As such, huff-n-puff (HnP) EOR techniques involving field gas injection may be the most effective EOR methods to increase the recovery factors from these shale formations. Several numerical reservoir simulation studies have showed the efficiency of CO2 HnP process in shale and tight formations (Yu et al, 2014); however, these studies show little to no field results to support the simulation predictions. This paper describes the conceptual development of the reservoir simulation models to investigate the viability of gas injection HnP in unconventional reservoirs and the results of applying those methods in Eagle Ford field test sites. Single-well and multi-well models with multi-stage hydraulic fractures were constructed and history matched using their primary production period performance. Sensitivity studies were conducted on well communication behavior/impacts, injection gas compositions, injection rates, injection/production cycling, and reservoir fluid types to optimize the pilot project well location(s) and to inform development strategies. Optimal cases from the simulation study were successfully applied to multi-well pads in the Eagle Ford formation across multiple fluid types. The simulation and the field application results were summarized and compared to provide detailed insights of unconventional HnP EOR. This study indicates the importance of confinement of the gases to afford optimal recovery factors during unconventional gas HnP EOR. An optimization engine was used in this study to optimize key operational parameters, such as injection pressures and slug sizes, to maximize recovery and efficiency. The resulting EOR designs were successfully implemented in field operations. Field recovery factors are within 10% of those predicted by simulation, indicating the value of numerical reservoir simulation prior to field trials and subsequent future development.

Analytical models available in Rate-Transient-Analysis (RTA) packages are widely used as tools for history matching and forecasting production in unconventional resources. There has also been an increasing interest in the use of numerical simulation of unconventional reservoirs. In this study, we use both methods to history match the production of hydraulically fractured unconventional wells, followed by forecasting future production to establish a well's EUR (Estimated Ultimate Recovery) for reserves determination purposes. This study's goal is to quantify the differences one might expect to encounter in a well's EUR when using analytical model-based RTA vs numerical simulation-based workflows in unconventional reservoirs.First, we consider an undersaturated shale oil reservoir as a base model for this study. The base case also satisfies all assumptions inherent to analytical solution-based methods such as homogenous reservoir properties and fully-penetrating planar fractures. An excellent match between results of both methods for the base model validates the numerical simulation approach. We then impose a series of real-world deviations from RTA assumptions and investigate reliability of EUR predictions made by both approaches. In all cases, historical data and reference EURs are derived from finely-gridded numerical simulations.Example results show that, in the presence of real-world deviations from RTA assumptions, analytical models can still match the historical production data; however, key reservoir and fracture parameters need to be modified drastically to compensate for the lack of sufficient physics in the analytical models. Results show that the analytical solution-based history-matched models are not predictive for future production, and somewhat surprisingly provide pessimistic EURs in all real-world scenarios investigated in this work. For the cases presented in this study, analytical models under-predict EURs by 6-17% when two years of production history is available for matching. The underestimation of EUR increases drastically (up to 60%) as the length of available historical data decreases from 2 years to 3 months.For all cases, we also apply an efficient numerical simulation-based workflow for probabilistic forecasting of EURs. This workflow provides multiple history-matched models that are constrained by historical production data. The probabilistic forecast method employed in this work provides P90 (conservative), P50 (most likely), and P10 (optimistic) values for EUR. In all examples, the range of P90 to P10 EUR values includes the reference EUR, and the P50 values are within 2.2% of the reference EUR.

Analytical models available in Rate-Transient-Analysis (RTA) packages are widely used as tools for history matching and forecasting production in unconventional resources. There has also been an increasing interest in the use of numerical simulation of unconventional reservoirs. In this study, we use both methods to history match the production of hydraulically fractured unconventional wells, followed by forecasting future production to establish a well's EUR (Estimated Ultimate Recovery) for reserves determination purposes. This study's goal is to quantify the differences one might expect to encounter in a well's EUR when using analytical model-based RTA vs numerical simulation-based workflows in unconventional reservoirs. First, we consider an undersaturated shale oil reservoir as a base model for this study. The base case also satisfies all assumptions inherent to analytical solution-based methods such as homogenous reservoir properties and fully-penetrating planar fractures. An excellent match between results of both methods for the base model validates the numerical simulation approach. We then impose a series of real-world deviations from RTA assumptions and investigate reliability of EUR predictions made by both approaches. In all cases, historical data and reference EURs are derived from finely-gridded numerical simulations. Example results show that, in the presence of real-world deviations from RTA assumptions, analytical models can still match the historical production data; however, key reservoir and fracture parameters need to be modified drastically to compensate for the lack of sufficient physics in the analytical models. Results show that the analytical solution-based history-matched models are not predictive for future production, and somewhat surprisingly provide pessimistic EURs in all real-world scenarios investigated in this work. For the cases presented in this study, analytical models under-predict EURs by 6-17% when two years of production history is available for matching. The underestimation of EUR increases drastically (up to 60%) as the length of available historical data decreases from 2 years to 3 months. For all cases, we also apply an efficient numerical simulation-based workflow for probabilistic forecasting of EURs. This workflow provides multiple history-matched models that are constrained by historical production data. The probabilistic forecast method employed in this work provides P90 (conservative), P50 (most likely), and P10 (optimistic) values for EUR. In all examples, the range of P90 to P10 EUR values includes the reference EUR, and the P50 values are within 2.2% of the reference EUR.

Capital investment and field development plans are based on evaluation of well performance. Numerical simulation models are widely used in that matter to derive estimated ultimate recovery (EUR) and depletion patterns of the stimulated reservoir volume (SRV). The main challenge when building a simulation model of hydraulically fractured wells is to realistically represent the heterogeneous conductivity distribution of the propped volume and its interaction with natural fractures. Field data such as microseismic and chemical tracers show evidence of horizontal and vertical asymmetric geometry of the hydraulic fractures. However, in practice they are modeled using symmetric bi-wing geometry due to over-simplified fracture models, where homogeneous stress field, rock properties and pore pressure are assumed. Simulation results obtained from such over simplistic models would lead to miscalculation of depletion patterns causing deficient spacing plans and performance forecasting. Previously, successful attempts were made to overcome the issue by calculating a volumetric enhanced permeability in two sub regions: in the near vicinity of the well and the SRV region, both extracted from strain derived as a result of the dynamic geomechanical simulation of the interaction between hydraulic and natural fractures. This approach improved the understanding of pressure depletion patterns while accounting for geomechanical heterogeneity between stages and wells in a pad; however, the transition from the dynamic geomechanical simulation of the frac complexity directly to the reservoir flow simulation left out a major tool commonly used in the design of the hydraulic fractures: frac design software and its resulting practical recommendations. To incorporate the frac design in the workflow, this paper illustrates how the frac complexity represented earlier as a volume can be discretized into multiple mathematical hydraulic fracture planes. This planar hydraulic fracture representation is a realistic mathematical approximation of the volumetric frac complexity that has been captured and validated with microseismic data in the dynamic geomechanical simulation. To keep the realism of asymmetric stimulation derived in the dynamic geomechanical simulation, the proposed workflow uses an asymmetric pseudo-3D hydraulic fracture model that accounts for the variation in height considering asymmetric half lengths due to lateral stress gradients in a heterogeneous reservoir. Such a frac design model results in a realistic field validated asymmetrical fracture geometry and conductivity for each activated fracture, calibrated to the proposed fracture treatment, or post-frac data. In this paper, the previous volumetric approach of modeling frac complexity and exporting it directly to reservoir simulation is briefly reviewed and the new workflow that represents the volumetric frac complexity with multiple asymmetric fracture planes is presented. Two scenarios are considered: 1) a coarse approximation of the frac complexity volume with a single fracture per stage and 2) a fine detailed representation of the stimulated volume using multimathematical hydraulic fracture planes per stage solution. The reservoir simulation results indicate that the fine multi fracs per stage representation is able to match the early pressure which contrasts with the coarse single frac per stage approximation unable to represents the complex physics occurring when the early flow is dominated by the high permeability created around the hydraulic fractures. The ease with which the early pressure was matched indicates that the fine multi frac stages approximation of the frac complexity volume is a viable solution to mathematically represent the complex realities of the hydraulic fracturing and its consequences on the asymmetric depletion. In addition of having a validated approach that can 1) predict microseismicity during the dynamic geomechanical simulation, 2) honor the frac treatment data during stimulation and 3) match the early pressure and beyond during production, we must emphasize another major benefit of this workflow is that it uses existing reservoir simulators, requiring from the user no additional reservoir simulation budget expenditures or training.