Ganjdanesh, Reza (The University of Texas at Austin) | Yu, Wei (The University of Texas at Austin) | Fiallos Torres, Mauricio Xavier (The University of Texas at Austin) | Sepehrnoori, Kamy (The University of Texas at Austin) | Kerr, Erich (EP Energy) | Ambrose, Raymond (EP Energy)
As the pressure drops below dew point in an unconventional gas-condensate reservoir, the liquid drops out of gas phase and forms an oil phase in matrix and fracture. The volume of oil phase formed in the matrix mostly stays below the residual oil saturation, i.e., the oil will be trapped in matrix permanently if enhanced oil recovery techniques are not applied. The huff-n-puff process has been performed and shown the potential of improving the recovery from tight oil reservoirs. The objective of the study was to investigate the feasibility of huff-n-puff EOR in a gas condensate reservoir in Eagle Ford. The studied section of the field contains 13 horizontal producers. The wells have been producing for 4 to 8 years and the oil production rate of each well declined below 10 barrels per day.
Compositional reservoir simulation was used to predict the performance of enhanced oil recovery. A sector model was built for the area selected as the prospective candidate for gas injection. The embedded discrete fracture model (EDFM) was used for modeling the fractures. A Peng-Robinson equation-of-state model was prepared based on the early produced samples from the wells. The only available gas for injection was the produced gas from the surrounding producers. A thorough phase behavior analysis was conducted to understand the miscibility of the injected gas and the in-situ fluid.
The field production data was used to history match the sector model. The field data of the initial huff-n-puff cycles were incorporated into the history match to fine tune the model. The robust sector model was employed to forecast the performance of gas huff-n-puff in 4 infill wells for 5 years of EOR operation.
Xu, Feng (RIPED / CNODC) | Li, Xianbing (RIPED) | Gong, Yiwen (The Ohio State University) | Lei, Cheng (RIPED) | Li, Xiangling (RIPED) | Yu, Wei (The University of Texas at Austin / Texas A&M University) | Miao, Jijun (The University of Texas at Austin / SimTech LLC) | Ding, Yutao (CNODC)
Natural fractures are commonly observed in the unconventional reservoir. Production history indicates that natural fractures have been playing an important role in the oil and gas development progress by improving the permeability of the reservoir and increasing the well productivity. In addition, inappropriate development strategies result in the unreasonable single well oil rate, early water breakthrough, severe damages to the unconventional reservoir and overwhelming economic losses when the fracture properties and distributions are not well understood before the development. Hence, it is of great importance to propose a powerful and efficient workflow to describe the fracture distribution clearly, including building a 3D fracture model, performing history matching and forecasting productions of the unconventional reservoir. In this study, we present a powerful and practical workflow through using Fracflow software and EDFM (Embedded Discrete Fracture Model) to build the 3D DFN (Discrete Fracture Network) model. The main methodology used to perform the fracture modelling allows rigorously handling of both hydraulic fractures and natural fractures that can be identified in an unconventional reservoir. This modelling allows computing the real geometrical fracture attributes (mainly orientation and density) and the spatial distribution of fractures. Fracture conductivity values will be calibrated through a comparison of the Kh(permeability thickness) from the well test to the Kh model computed from the upscaling of the fracture model. The mentioned model above will be built by means of a stochastic simulation constrained by the results of the static and dynamic fracture characterization. In the reservoir simulation phase, EDFM processor combining commercial reservoir simulators is fully integrated to perform history matching and production performance forecast of the unconventional reservoir. With a new set of formulations used in EDFM, the non-neighboring connections (NNCs) in the EDFM are converted into regular connections in traditional reservoir simulators, and the NNCs factors are linked with gridblock permeabilities. EDFM provides three kinds of NNC pairs, transmissibility factors, and the connections between fractures and wells. With the aid of the EDFM processor, we can obtain the number of additional grids, the properties of fracture grids, and the NNCs as the simulation input. From the proposed workflow, complex dynamic behaviors of natural fractures can be captured. This will further ensure the accuracy of DFMs and the efficiency offered by structured gridding. The practical workflow for the unconventional reservoir from modelling to simulation highlights the model constrained by the results of the static and dynamic fracture characterization, and the high efficiency to model discrete fractures through the revolutionary EDFM processor. Through this workflow, we can perform history matching effectively and simulate complex fractures including hydraulic fractures and naturally fractures. It potentially can be integrated into existing workflow for unconventional reservoirs for sensitivity analysis and production forecasting.
An integration of fracture model and reservoir model with complex fracture geometry plays an important role in understanding the impacts of fracture complexity on optimization of well spacing. In this study, we applied the non-intrusive EDFM (Embedded Discrete Fracture Model) technology to couple fracture and reservoir models to perform shale gas simulation with and without considering natural fractures. First, we applied a complex fracture propagation model to predict hydraulic fracture geometry. For the first time, the impact of non-uniform natural fracture distribution with a larger fracture intensity nearby the wellbore region on fracture complexity was investigated. Two horizontal wells with and without natural fractures were simulated to generate simple and complex fractures. Complex fractures include hydraulic fractures and complex activated natural fractures. Well interference due to hydraulic fracture hits of both fracture geometries were analyzed and compared. After that, both simple and complex fractures were directly transferred to a shale-gas two-phase reservoir model through the non-intrusive EDFM technology. Both fracture geometries can be easily embedded into the structured matrix grids. Fluid flow between fracture and matrix grids can be exactly handled by non-neighboring connections and transmissibility. During the shale-gas production simulation, key effects such as non-Darcy flow in fractures, gas desorption, and pressure-dependent matrix permeability, hydraulic fracture permeability, and activated natural fracture permeability were considered. Additionally, different relative permeability curves for matrix and fractures were assigned in the reservoir model. We compared the well performance of 30 years under the constant flowing bottomhole pressure constraint between simple and complex fractures. The simulation results show that complex fractures can perform much better in terms of cumulative gas and water production than the simple fractures. The simple fractures are easier to cause well interference due to hydraulic fracture hits than the complex fractures under the same completion condition. Furthermore, the simple fractures have a much smaller drainage area and less drainage efficiency than the simple fractures. Finally, the simple fractures have a much larger pressure difference from the fracture center to its neighboring shale matrix than the complex fractures, which indicates that the smaller cluster spacing might be suggested in order to maximize the drainage efficiency if ignoring the natural fracture effect. This study provides critical insights into understanding the impact of non-uniform natural fractures on fracture propagation and shale-gas production simulation.
Ganjdanesh, Reza (The University of Texas at Austin) | Yu, Wei (The University of Texas at Austin) | Fiallos, Mauricio Xavier (The University of Texas at Austin) | Kerr, Erich (EP Energy) | Sepehrnoori, Kamy (The University of Texas at Austin) | Ambrose, Raymond (EP Energy)
As the pressure drops below dew point in an unconventional gas-condensate reservoir, the liquid drops out of gas phase and forms an oil phase in matrix and fracture. The volume of oil phase formed in the matrix mostly stays below the residual oil saturation, i.e., the oil will be trapped in matrix permanently if enhanced oil recovery techniques are not applied. The gas huff-n-puff process has been performed and shown the potential of improving the recovery from tight oil reservoirs. The objective of the study was to investigate the feasibility of huff-n-puff EOR in a gas condensate reservoir. The studied section of the field contains 13 horizontal producers. The wells have been producing for 4 to 8 years and the oil production rate of each well declined below 10 barrels per day.
Compositional reservoir simulation was used to predict the performance of enhanced oil recovery. A sector model was built for the area selected as the prospective candidate for gas injection. The embedded discrete fracture model (EDFM) was used for modeling the fractures, improving the CPU time by an order of magnitude compared to the local grid refinement method. A Peng-Robinson equation-of-state model was prepared based on the early produced samples from the wells. The only available gas for injection was the produced gas from the surrounding producers. A thorough phase behavior analysis was conducted to understand the miscibility of the injected gas and the in-situ fluid.
The well interference through fracture hits plays an important role in the studied reservoir. The image logs from the surrounding wells show the abundance and extent of the long fractures connecting multiple producers. The long fractures can impede the pressure buildup during gas injection and hamper the gas huff-n-puff performance. Several long fractures were added to the reservoir model to capture the characteristics of well interference.
Tripoppoom, Sutthaporn (The University of Texas at Austin / PTT Exploration and Production PLC) | Yu, Wei (The University of Texas at Austin) | Sepehrnoori, Kamy (The University of Texas at Austin) | Miao, Jijun (The University of Texas at Austin / Sim Tech LLC)
Production data which is always available at no additional cost can give an invaluable information of fracture geometry and reservoir properties. However, in unconventional reservoirs, it is insufficient to characterize hydraulic fractures geometry and reservoir properties by only one realization because it cannot capture the non-uniqueness of history matching problem and subsurface uncertainties. Therefore, the objective of this study is to obtain multiple realizations in shale reservoirs by adopting Assisted History Matching (AHM).
We used Neural Network-Markov Chain Monte Carlo (NN-MCMC) algorithm in the proposed AHM workflow for shale reservoirs. The reason is that MCMC, one of AHM in the Bayesian statistics, has benefits of quantifying uncertainty without bias or being trapped in any local minima. Also, using MCMC with neural network (NN) as a proxy model unlocks the limitation of an infeasible number of simulation runs required by a traditional MCMC algorithm. The proposed AHM workflow also utilized the benefits of Embedded Discrete Fracture Model (EDFM) to model fractures with a higher computational efficiency than a traditional local grid refinement (LGR) method and more accuracy than the continuum approach.
We applied the proposed AHM workflow to an actual shale-gas well. We performed history matching on two cases including hydraulic fractures only and hydraulic fractures with natural fractures. The uncertain parameters for history matching consist of fracture geometry, fracture conductivity, matrix permeability, matrix and fracture water saturation, and relative permeability curves. For the case with natural fractures, we included number, length and conductivity of natural fractures as the additional uncertain parameters.
We found that, in this case, the NN-MCMC algorithm find the history match solutions around 30% from a total number of simulation runs. Also, we obtained the posterior distribution of each fracture parameter and reservoir property for both cases. Moreover, we found that the presence of natural fractures affects the posterior distribution. We observed significantly lower fracture height, lower fracture conductivity, higher fracture water saturation than the case without natural fractures because more fluid flow is enhanced by natural fractures. Lastly, the proposed AHM workflow using NN-MCMC algorithm can characterize fracture geometry, reservoir properties, and natural fractures in a probabilistic manner. These multiple realizations can be further used for a probabilistic production forecast, future fracturing design improvement, and infill well placement decision.
Fiallos Torres, Mauricio Xavier (The University of Texas at Austin) | Yu, Wei (The University of Texas at Austin) | Ganjdanesh, Reza (The University of Texas at Austin) | Kerr, Erich (EP Energy) | Sepehrnoori, Kamy (The University of Texas at Austin) | Miao, Jijun (SimTech LLC) | Ambrose, Raymond (EP Energy)
Optimizing spacing of infill wells and fractures can lead to large rewards for shale field operators, and these considerations have influences on primary and tertiary development of the field. Although several studies have been employed to show the existence of well interference, few models have also implemented Huff-n-Puff and injection containment methods to optimize further hydraulic fracture designs and pressure containment to improve the efficiency of Enhanced Oil Recovery (EOR). This study has performed a rigorous workflow for estimating the impacts of spatial variations in fracture conductivity and complexity on fracture geometries of interwell interference. Furthermore, we applied a non-intrusive embedded discrete fracture model (EDFM) method in conjunction with a commercial compositional reservoir simulator to investigate the impact of well interference through connecting fractures by multi-well history matching to propose profitable opportunities for Huff-n-Puff application. First, based on a robust understanding of fracture properties, updated production data and multi-pad wellbore image logging data from Eagle Ford, the model was constructed to perform nine wells sector model history matching. Later, inter-well connecting fractures were employed for enhanced history matching where results varied significantly from unmeasured fracture sensitivities. The result is the implementation of Huff-n-Puff models that capture inter-well interference seen in the field and their affordable impact sensitivities focused on variable injection rates/locations and multi-point water injection to mimic pressure barriers. The simulation results strengthened the understanding of modeling complex fracture geometries with robust history matching and support the need to incorporate containment strategies. Moreover, the simulation outcomes show that well interference is present and reduces effectiveness of the fracture hits when connecting natural fractures. As a result of the inter-well long fractures, the bottom hole pressure behavior of the parent wells tends to equalize, and the pressure does not recover fast enough. Furthermore, the EDFM application is strongly supported by complex fracture propagation interpretation and ductility to be represented in the reservoir. Through this study, multiple containment scenarios were proposed to contain the pressure in the area of interest.
The model has become a valuable template to inform the impacts on well location and spacing, completion design, initial huff-n-puff decisions, subsequent containment strategies (e.g. to improve cycle timing and efficiency), and to expand to other areas of the field. The simulation results and understandings afforded have been applied to the field satisfactorily to support pressure containment benefits that lead to increased pressure build, reduced gas communication, reduced offset shut-in volumes, and ultimately, improvements in net utilization and capital efficiency.
US unconventional resource production has developed tremendously in the past decade. Currently, the unconventional operators are trying many strategies such as refracturing, infill drillings and well spacing optimization to improve recovery factor of primary production. They are also employing big data and machine learning to explore the existed production data and geology information to screen the sweet spot from geology point of view. However, current recovery factor of most unconventional reservoirs is still very low (4~10%). A quick production rate decline pushes US operator to pursue gas EOR for unconventional reservoirs, lifting the ultimate recovery factor to another higher level. The goal of this work is to improve oil recovery by implementing gas Huff and Puff process and optimizing injection pattern for one of the US major tight oil reservoirs - Eagle Ford basin. Gas diffusion is regarded as critical for gas Huff and Puff process of tight oil reservoirs. Utilizing the dual permeability model, gas diffusion effect is systematically analyzed and compared with the widely used single porosity model to justify its importance. Transport in natural fractures is proved to be dominated recovery mechanism using dual permeability model. Uncertainty studies about reservoir heterogeneity and nature fracture permeability are performed to understand their influences on well productivity and gas EOR effectiveness. Moreover, three alternative gas injectant compositions including rich gas, lean gas and nitrogen are investigated in gas Huff and Puff processes for Eagle Ford tight oil fractured reservoir. The brief economic evaluation of Huff and Puff project is conducted for black oil region of the Eagle Ford basin.
Field data have shown the decline of fracture conductivity during reservoir depletion. In addition, refracturing and infill drilling have recently gained much attention as efficient methods to enhance recovery in shale reservoirs. However, current approaches present difficulties in efficiently and accurately simulating such processes, especially for large-scale cases with complex hydraulic and natural fractures.
In this study, a general numerical method compatible with existing simulators is developed to model dynamic behaviors of complex fractures. The method is an extension of an embedded discrete-fracture model (EDFM). With a new set of EDFM formulations, the nonneighboring connections (NNCs) in the EDFM are treated as regular connections in traditional simulators, and the NNC transmissibility factors are linked with gridblock permeabilities. Hence, manipulating block permeabilities in simulators can conveniently control the fluid flow through fractures. Complex dynamic behaviors of hydraulic fractures and natural fractures can be investigated using this method.
The proposed methodology is implemented in a commercial reservoir simulator in a nonintrusive manner. We first present one synthetic case study in a shale-oil reservoir to verify the model accuracy and then combine the new model with field data to demonstrate its field applicability. Subsequently, four field-scale case studies with complex fractures in two and three dimensions are presented to illustrate the applicability of the method. These studies involve vertical- and horizontal-well refracturing in tight reservoirs, infill drilling, and fracture activation in a naturally fractured reservoir. The proposed approach is combined with empirical correlations and geomechanical criteria to model stress-dependent fracture conductivity and natural-fracture activation. It also shows convenience in dynamically adding new fractures or extending existing fractures during simulation. Results of these studies further confirm the significance of dynamic fracture behaviors and fracture complexity in the analysis and optimization of well performance.
Fiallos, Mauricio Xavier (The University of Texas at Austin) | Yu, Wei (The University of Texas at Austin) | Ganjdanesh, Reza (The University of Texas at Austin) | Kerr, Erich (EP Energy) | Sepehrnoori, Kamy (The University of Texas at Austin) | Miao, Jijun (SimTech LLC) | Ambrose, Raymond (EP Energy)
Shale field operators have vested interest in optimal spacing of infill wells and further fracture optimization, which ideally should have as little interference with the existing wells as possible. Although proper modeling has been employed to show the existence of well interference, few models have forecasted the impact of multiple inter-well fractures on child wells production to optimize further hydraulic fracture designs. This study presented a rigorous workflow for estimating the impacts of spatial variations in fracture conductivity and complexity on fracture geometries of inter-well interference. Furthermore, we applied a non-intrusive embedded discrete fracture model (EDFM) method in conjunction with a commercial black oil reservoir simulator to investigate the impact of well interference through connecting fractures by multi-well history matching, based on a robust understanding of fracture properties, real production data and wellbore image logging. First, according to updated production data from Eagle Ford, the model was constructed to perform four (parent) wells history matching including five inner (child) wells. Later, fracture diagnostic results from well image logging were employed to perform sensitivity analysis on properties of long interwell connecting fractures such as number, conductivity, geometry, and explore their impacts on history matching. Finally, optimal cluster spacing was recommended considering interwell interference. The simulation results show that well interference is present and reduces effectiveness of the fracture hits when the connecting fracture conductivity, primary fracture conductivity, and number of connecting fractures increase. Because of these interwell long fractures, the bottomhole pressure behavior of the parent wells tends to equalize. Furthermore, the EDFM application is strongly supported by complex fracture propagation interpretation from image logs through the child wells in the reservoir. Through this study, three possible scenarios are shown with robust history matching of the model considering more than 20 complex dominant long interwell fracture hits and more than 2000 hydraulic fractures.
The model became a valuable stencil to decide the well location and spacing, the completion staging, and to optimize the hydraulic fracture treatment design as well as its sequence so that it can be expanded to other areas of the field. The simulation results were applied to the field successfully to afford significant reductions in offset frac interference by up to 50% and reduce completion costs up to 23% while improving new well capital efficiency.
Yu, Wei (Texas A&M University and University of Texas at Austin) | Zhang, Yuan (China University of Geosciences, Beijing) | Varavei, Abdoljalil (University of Texas at Austin) | Sepehrnoori, Kamy (University of Texas at Austin) | Zhang, Tongwei (University of Texas at Austin) | Wu, Kan (Texas A&M University) | Miao, Jijun (SimTech)
Although numerous studies proved the potential of carbon dioxide (CO2) huff ’n’ puff, relatively few models exist to comprehensively and efficiently simulate CO2 huff ’n’ puff in a way that considers the effects of molecular diffusion, nanopore confinement, and complex fractures for CO2. The objective of this study was to introduce a numerical compositional model with an embedded-discrete-fracture-model (EDFM) method to simulate this process in an actual Eagle Ford tight oil well. Through nonneighboring connections (NNCs), the EDFM method can properly and efficiently handle any complex fracture geometries. We built a 3D reservoir model with six fluid pseudocomponents. We performed history-matching with measured flow rates and bottomhole pressure (BHP). Good agreements between field data, EDFM, and local grid refinement (LGR) were achieved. However, the EDFM method performed faster than the LGR method. After that, we evaluated the CO2-enhanced-oil-recovery (EOR) effectiveness for molecular diffusion and nanopore confinement effects. The traditional phase equilibrium calculation was modified to calculate the critical fluid properties with nanopore confinement. The simulation results showed that the CO2 EOR with larger diffusion coefficients performed better than the primary production. In addition, both effects were favorable for the CO2 huff ’n’ puff effectiveness. The relative increase of cumulative oil production after 20 years was approximately 12% for this well. Furthermore, when considering complex natural fractures, the relative increase of cumulative oil production was approximately 8%. This study provided critical insights into a better understanding of the impacts of CO2 molecular diffusion, nanopore confinement, and complex natural fractures on well performance during the CO2-EOR process in tight oil reservoirs.