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.
Sun, Zheng (China University of Petroleum at Beijing, Texas A&M University) | Shi, Juntai (China University of Petroleum at Beijing) | Wu, Keliu (China University of Petroleum at Beijing) | Gong, Dahong (CNPC Bohai Drilling Engineering Company Limited Directional Well Technology Services Branch) | Peng, Hui (CNPC Bohai Drilling Engineering Company Limited Mud Logging 2) | Hou, Yuhua (NO.2 Logging Branch of Bohai Drilling Engineering Co., Ltd., PetroChina Group) | Ma, Hongyan (CNPC Bohai Drilling Engineering Company Limited Directional Well Technology Services Branch) | Wang, Daning (CNPC Bohai Drilling Engineering Company Limited Directional Well Technology Services Branch) | Ramachandran, Hariharan (The University of Texas at Austin) | Liu, Yisheng (China University of Petroleum at Beijing) | Liu, Wenyuan (China University of Petroleum at Beijing) | Wang, Suran (China University of Petroleum at Beijing) | Li, Xiangfang (China University of Petroleum at Beijing)
With respect to the sharp increase in population all around the world, more and more energy and fuels are expected to achieve the counterbalance between supply and demand. Deeply attracted by its considerable and prospect recovery reserve, the exploitation, development and related research contents regarding coalbed methane (CBM), i.e., one of the unconventional gas reservoirs, are currently heat and essential topics. Without any doubt, precise determination of coal permeability will dramatically contribute to the development efficiency of CBM reservoirs. It should be noted that the permeability in CBM reservoirs possesses unique heterogeneous characteristics, especially for the different permeability at directions of face cleats and butt cleats, which will inevitably result in greatly shape-change for fluid flow field and eventually the production performance. To my best knowledge, nearly all the previous methods proposed for evaluating coal permeability assume the homogeneous permeability feature in CBM reservoirs, which show fairly great discrepancy compared with that of the realistic situation. In this work, in order to address this urgent issue, a novel permeability evaluation method is developed for the first time, which is able to generate precisely heterogeneous characteristics of coal permeability based on the water production rate versus production time curve at the early production stage. First of all, considering both orthotropic heterogeneous permeability and pressure propagation behavior in CBM reservoirs, single water phase productivity equation is seriously derived. Secondly, for simply usage purpose in field application, the obtained equation is transformed through linearization treat. Finally, combining the water production performance with the linearized equation, efficient iteration calculation procedures are given to determine the heterogeneous permeability feature. Also, the skin factor of corresponding CBM well can be determined. The applicability and accuracy of the proposed method have been successfully verified through field application. In sum, the proposed method can serve as a simple as well as an accurate tool to determine the crucial heterogeneous permeability feature in CBM reservoirs. More importantly, during the determination process, the method just requires the water production performance at the early production stage, which means that the obtained permeability characteristics can be utilized to guide production strategy adjustment in the following gas production stage. As a result, the proposed method can be regarded as a necessary preparatory work before gas production takes place in CBM reservoirs, which will play a positive and active role in optimization of ultimate gas recovery and well configuration.
Chemical enhanced oil recovery (EOR) methods have received increased attention in recent years since they have the ability to recover the capillary trapped oil. Successful chemical flooding application requires accurate numerical models and reliable forecast across multiple scales: core scale, pilot scale, and field scale. History matching and optimization are two key steps to achieve this goal.
For history matching chemical floods, we propose a general workflow for multi-stage model calibration using an Evolutionary Algorithm. A comprehensive chemical flooding simulator is used to model important physical mechanisms including phase behavior, cation exchange, chemical and polymer adsorption and capillary desaturation. First, we identify dominant reservoir and process parameters based on a sensitivity analysis. The history matching is then carried out in a stage-wise manner whereby the most dominant parameters are calibrated first and additional parameters are incorporated sequentially until a satisfactory data misfit is achieved. Next, a diverse subset of history matched models is selected for optimization using a Pareto-based multi-objective optimization approach. Based on the concept of dominance, Pareto optimal solutions are generated representing the trade-off between increasing oil recovery while improving the efficiency of chemical usage. These solutions are searched using a Non-dominated Sorting Genetic Algorithm (NSGA-II). Finally we implement a History Matching Quality Index (HMQI) with Moving Linear Regression Analysis to evaluate simulation results from history matching process. The HMQI provides normalized values for all objective functions having different magnitude and leads to a more consistent and robust approach to evaluate the updated models through model calibration.
Significant advances have been made in chemical enhanced oil recovery (EOR) in recent years including the development of hybrid methods that combine surfactants, polymers, alkali, co-solvents, gas and heat in novel ways. New and improved chemical and physical property models have been developed to more accurately simulate these processes at the field scale. We present improved models for relative permeability, capillary pressure, the effect of polymer viscoelasticity on residual oil saturation, the effect of pH on surfactant adsorption, polymer partitioning between aqueous and microemulsion phases, and the effect of co-solvent on microemulsion viscosity. Several simulations are presented to demonstrate how the models can be used to match experimental data.
Coupled reservoir flow and geomechanics has numerous important applications in the oil & gas industry, such as land subsidence, hydraulic fracturing, fault reaction and hydrocarbon recovery etc. High fidelity numerical schemes and multiphysics models must be coupled in order to simulate these processes and their interactions accurately and efficiently. Specifically, in the applications of CO2 sequestration, the effect of geomechanics on carbon storage estimation is not negligible. However, coupled flow-geomechanics simulations are very computationally expensive and most of the computational time is usually spent for geomechanics calculations. This paper investigates a three-way coupling algorithm that uses an error indicator to determine when displacement must be updated and whether fixed-stress iterative coupling technique is required. Numerical experiments with coupled nonlinear single-phase flow and linear poromechanics shows that the three-way coupling algorithm can speed up 4 times comparing to fixed-stress iterative coupling algorithm. Extensions to coupled compositional flow with poromechanics also shows a speed-up for 5 times for continuous CO2 sequestration applications and 2 times for surfactant-alternating-gas applications (SAG). The substantial speed up makes the three-way coupling algorithm of flow and geomechanics feasible in the large-scale optimizations. Based on the three-way coupling of compositional flow and geomechanics, we experimented two black box optimization algorithms, covariance-matrix adaptation evolution strategy (CMA-ES) and genetic algorithm (GA), for the optimization of well controls during SAG process to maximize CO2 storage volume. CMA-ES outperforms GA in that it is more robust, and it achieves higher objective function value in less simulation runs. The optimized SAG process achieves 27.55% more CO2 storage volume and reduces water and surfactant consumption by 54.84%.
A novel approach is introduced for simulation of multiphase flow, geomechanics, and fracture propagation on very general semi-structured grids. Complex networks consisting of both natural and hydraulically stimulated fractures are able to be represented using a diffusive zone model in large scale reservoirs. A mass conservative method called the enhanced velocity mixed finite element method is used to model multiphase flow with a fully-compositional equation-of-state model. Its recent reformulation on semi-structured, spatially non-conforming grids allows very general local refinement and dynamic mesh adaptivity.
Iteratively coupled geomechanics is simulated, which can predict fracture opening on fixed networks based upon induced stresses and poromechanical effects. In the most complex case, it is coupled with the phase field method to model nucleation and branching of non-planar fractures in highly heterogeneous media. Several examples are demonstrated to model fracture networks. The general semi-structured discretization can simulate flow and geomechanics on networks of fractures in large reservoirs with local resolution where desired. Dynamic adaptive mesh refinement can be used for both tracking transient flow features such as sharp the propagation of new fractures via hydraulic stimulation. This framework allows the seamless ability to switch from production to propagation scenarios, by varying the degrees of physics.
This work demonstrates a capability to perform high-fidelity simulations on complex fracture networks in large reservoirs at a reasonable computational cost. The gridding algorithms are straightforward extensions to traditional finite difference reservoir simulators. It can also be coupled with state-of-the-art complex phase field fracture propagation. This extends the capabilities of many legacy reservoir simulators to handle more physics.
Geochemical scale formation and deposition in reservoir is a common problem in upstream oil and gas industry, which results in equipment corrosion, wellbore plugging, and production decline. In unconventional reservoirs, the negative effect of scale formation becomes more pronounced as it can severely damage the conductivity of hydraulic fractures. Hence, it is necessary to predict the effect of scale deposition on fracture conductivity and production performance.
In this work, an integrated reactive-transport simulator is utilized to model geochemical reactions along with transport equations in conventional and unconventional reservoirs considering the damage to the fracture and formation matrix. Hence, a compositional reservoir simulator (UTCOMP), which is integrated with IPhreeqc, is utilized to predict geochemical scale formation in formation matrix and hydraulic fractures. IPhreeqc offers extensive capabilities for modeling geochemical reactions including local thermodynamic equilibrium and kinetics. Based on the amount of scale formation, porosity, permeability, and fracture aperture are modified to determine the production loss. The results suggested that interaction of the formation water/brine and injection water/hydraulic fracturing fluid is the primary cause for scale formation. The physicochemical properties such as pressure, temperature, and
During hydraulic fracturing, precipitation of barite and dissolution of calcite are identified to be the main reactions, which occur as a result of interaction between the formation brine, formation mineral composition, and injection water/hydraulic fracturing fluid. Calcite dissolution can increase the matrix porosity and permeability while barite precipitation has an opposite effect. Therefore, the overall effect and final results depend on several parameters such as HFF composition, HFF injection rate, and formation mineral/brine. Based on the fracturing fluid composition and its invasion depth in this study, the effect of barite precipitation was dominant with negative impact on cumulative gas production. The outcome of this study is a comprehensive tool for prediction of scale deposition in the reservoir which can help operators to select optimum fracturing fluid and operating conditions.
Despite the great interest and importance of modeling hydrocarbon production from tight oil reservoirs, the thermodynamic stability of multicomponent mixtures with capillary pressure has not been studied sufficiently. This paper introduces a practical algorithm for phase stability analysis of multi-component mixtures with capillary pressure. The capillary pressure is determined from a realistic saturation-dependent function which is representative of pore size distributions as well as other petrophysical properties such as wettability and water saturation. The new stability procedure is coupled with flash calculations. Therefore, the phase saturations and compositions of the mixture are also provided in addition to the stability condition once the solution is converged. The significance and robustness of the new method is shown in several examples with realistic tight oil and gas-condensate mixtures.
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.
Gu, Qifan (The University of Texas at Austin) | Fallah, AmirHossein (The University of Texas at Austin) | Ambrus, Adrian (The University of Texas at Austin, now with Norwegian Research Centre) | Chen, Dongmei (The University of Texas at Austin) | Ashok, Pradeepkumar (The University of Texas at Austin) | van Oort, Eric (The University of Texas at Austin)
For robust and efficient automated Managed Pressure Drilling (MPD) operation, the choke controller requires a hydraulics model that is highly accurate and fast. The integration of a thermal model would be a great improvement for the hydraulics model's accuracy but has not been given sufficient discussion before.
In this paper, aquasi-steady thermal model is added to an automated MPD control approach that uses a reduced Drift-Flux Model (RDFM) for multiphase flow simulation. This provides the dynamic temperature profile in the well without increasing the computational expense. The energy equation is solved using the finite-difference method (FDM) in an explicit scheme, with all the temperature-dependent parameters updated in accordance with the calculated temperature profile in each loop. The RDFM is also reformulated to account for the heat transfer between the gas and the surroundings. This modified model is incorporated with an automated observer routine to estimate control parameters, e.g. volume of gas expansion (dependent on temperature), which are used by the controller for choke opening manipulation.
The simulation result of the proposed modeling approach for the scenario with a dynamic temperature profile are compared with that obtained with a validated full-order Drift-Flux Model (DFM) with an energy equation for validation. The dynamic temperature profile shows significant deviation from the steady-state temperature profile predicted in the absence of the thermal model. The proposed model is also compared with the RDFM without adding energy equation to show the improvements with the addition of thermal model. Moreover, accurate temperature modeling during multiphase flow situations is essential to achieving high-fidelity influx control and handling. The updated controller incorporating the new thermal model was tested, and the performance of the choke controller turned out to be faster and more precise than the previous controller which was based on a RDFM without energy equation. The computational cost of this modified model was also tested in a full-scale wellbore geometry with two-phase flow. The calculation time is of the order of ~70ms for 1s sensor data sampling on a normal PC, which is more than sufficient for automated real time control.