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The objective of this study is to develop a new method that leads to diagnostic charts that quantify the pressure response between two interfering wells. Analytical linear flow models for single hydraulic fracture are used to develop a fracture hit model, which is next verified with a numerical model for validity. An analytical two-fracture model is then developed to simulate flowing bottomhole pressure (BHP) of a shut-in well, which interferes with the other well through a fracture hit, during well-testing for a short-term period. From the insight of two-fracture analytical model, a dimensionless pressure scalar, which is proportional to square root of time, is proposed to summarize the interference level between two wells. Utilizing such proportionality between the defined dimensionless pressure scalar and square root of time, a diagnostic chart for quick assessment of the production interference level between wells is developed. Such diagnostic chart is also applied to interference caused by multifracture hits that a multistage fractured horizontal well with history match performed from the Eagle Ford formation is considered as a parent well for production interference quantification. A new identical horizontal well, which is just fractured but is not in production, is assumed parallel to the pre-existing well. The result shows that when the percentage of fracture connection increases, the slope of dimensionless pressure scalar vs. square root of time increases proportionally to the percentage of fracture connection. Because the slope of dimensionless pressure scalar vs. square root of time is between 0 and 1, it can be used to quantify the well production interference level under different situations.
Kang, Xiaodong (State Key Laboratory of Offshore Oil Exploitation) | Li, Baozhen (State Key Laboratory of Offshore Oil Exploitation) | Zhang, Jian (State Key Laboratory of Offshore Oil Exploitation) | Wang, Xudong (State Key Laboratory of Offshore Oil Exploitation) | Yu, Wei (Texas A&M University)
In this study SAGP (steam and gas push) technology was designed to improve the thermal recovery efficiency in L oil-sand field, where traditional steam flooding efficiency was unfavorable with high steam oil ratio and expensive operation cost. The optimization of SAGP process were performed with numerical simulation and response surface method "Box-Behnken", which could be done with acceptable accuracy by performing a limited number of runs, hence, reducing the engineering time and effort. With the simplified equation between the EOR and different SAGP parameters including Injection gas type, injection time, injection gas mol% and volume, operators could determine the best combination of all the factors according different conditions efficiently. This study provides critical insights for understanding the SAGP flooding mechanism and its effect on SAGD flooding effectiveness in the oil sand field, which also delivers a good reference for improving the development efficiency of oil sands with better economic benefits.
Currently many lean gas EOR pilot projects are implemented in Eagle Ford shale. The major component of lean gas is methane. From the field feedback, there is always large discrepancy between production forecast (or reservoir simulation) and the field results. The natural fracture system is complex and the communication between natural fracture, matrix and hydraulic fractures is even more complicated. Comparing connecting natural fracture between wells with short and low fracture conductivity, the well interference and the resulted optimal well spacing significantly change. In this study, according to field feedback, some connecting natural fractures with high fracture conductivity are mapped between wells to better represent the field geology and production status.
A composition reservoir simulation model is built for Eagle Ford shale. Typical production curve of Eagle Ford shale is matched for the first three years of primary production, lean gas Huff and Puff (HNP) process is simulated for the next three years for the parent wells and child wells. As the main composition of lean gas is methane, different methane adsorption effects are quantified between wells to investigate its influence on production. For lean gas Huff and Puff process, normally the Minimum Miscibility Pressure (MMP) is above 4000 psi. During lean gas cycling process, methane is adsorbed and desorbed, and the effective methane amount used to enhance miscibility between gas and oil phases is reduced, thus the reservoir pressure is not elevated to as high as no gas adsorption case. The methane adsorption effect significantly affects the oil and gas production. Relative permeability hysteresis and capillary pressure hysteresis (gas trapping effect) are the first time systematically studied to quantify the gas EOR performance in pad level production of unconventional reservoirs. Considering gas trapping effects, the cumulative gas injection amount and production amount is much better matched to the field pilot results. The oil incremental benefit of gas Huff and puff process considering gas trapping effect is quantified.
To our best knowledge, this is the first time that both methane adsorption and gas trapping effects are studied for pad level Huff and Puff process with the realistic connecting natural fractures between wells. Better matching of the production data with pilot results confirms the successful application of these two mechanisms. Considering the realistic complex natural fracture effects also greatly contributes to the correct production forecast and efficient design of gas EOR project for unconventional reservoirs such as Eagle Ford shale and other major basins.
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.
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.
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.
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.
ABSTRACT: It is important to determine well spacing for maximizing oil recovery in shale reservoirs with complex hydraulic and natural fracture geometries. The optimal number of well placement should be achieved to minimize well interference. Although there are many simulation studies to optimize well spacing, very few studies have been performed to combine the fracture propagation model and reservoir simulation considering complex fracture configurations. The goal of this study is to fill this gap by integrating a complex fracture model and reservoir model through a non-intrusive embedded discrete fracture model (EDFM) method. The fracture model was applied to predict complex fracture geometries. After that, such fractures were swiftly transferred to traditional reservoir simulators based on the non-intrusive EDFM technology. We applied the workflow to examine the effect of well number with varying well spacing on well performance in the Permian basin with and without considering natural fractures. Finally, the optimal well spacing was discussed. This study can provide key insights into optimization strategies for well spacing in shale reservoirs.
The optimal well number or well spacing plays an important role in economically developing shale or tight unconventional reservoirs. Well interference due to fracture hits often occurs if the well spacing becomes smaller, which should be minimized or avoided in order to maximize well productivity and economics (Lawal et al., 2013; King and Valencia, 2016; Kurtoglu and Salman, 2015; Liang et al., 2017; Yu et al., 2016, 2018a). Although there are many simulation studies to optimize well spacing (Díaz de Souza et al., 2012; Yu and Sepehrnoori, 2013; Tung et al., 2016; Manestar and Thompson, 2017; Mehranfar et al., 2018; Shahkarami et al., 2018) in unconventional reservoirs, most of them assume simple planar hydraulic fractures and did not consider the dynamic fracture propagation model to predict fracture geometry. In addition, the role of natural fracture in well spacing optimization is often ignored and poorly understood. Hence, it is of great importance to combine the fracture propagation model and reservoir simulation to evaluate the impacts of well spacing and complex hydraulic and natural fractures on well performance.
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)
Summary Although numerous studies proved the potential of carbon dioxide (CO 2) huff'n' puff, relatively few models exist to comprehensively and efficiently simulate CO 2 huff'n' puff in a way that considers the effects of molecular diffusion, nanopore confinement, and complex fractures for CO 2 . 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 CO 2 -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 CO 2 EOR with larger diffusion coefficients performed better than the primary production. In addition, both effects were favorable for the CO 2 huff'n' puff effectiveness. The relative increase of cumulative oil production after 20 years was approximately 12% for this well.