Layer | Fill | Outline |
---|
Map layers
Theme | Visible | Selectable | Appearance | Zoom Range (now: 0) |
---|
Fill | Stroke |
---|---|
Collaborating Authors
SPE Reservoir Simulation Conference
Coupled Geomechanics and Fluid Flow Modeling for Petroleum Reservoirs Accounting for Multi-Scale Fractures
Wu, Dawei (SINOPEC Petroleum Exploration and Production Research Institute) | Di, Yuan (Peking University) | Kang, Zhijiang (SINOPEC Petroleum Exploration and Production Research Institute) | Wu, Yu-Shu (Colorado School of Mines)
Abstract Accurate modeling of fractured reservoirs is very challenging due to the various scales of fractures. The fracture networks may be too complex to be represented using the equivalent continuum model (ECM) or dual porosity-dual permeability (DPDK) model, yet too computational costly to be modeled using the discrete fracture (DFM) or embedded discrete fracture (EDFM) models. This paper proposes a hybrid model that integrates ECM, DPDK, and an integrally embedded discrete fracture model (IEDFM) to account for multi-scale fractures. The hybrid model is applied to investigate the coupled geomechanics-fluid flow process in fractured reservoirs. In the hybrid model, small-scale fractures are upscaled into effective matrix permeability tensor using ECM, medium-scale fractures are considered as an individual continuum using DPDK, and large-scale fractures are explicitly represented using IEDFM. The multiphase flow in effective matrix and fracture continua is modeled using the multi-point flux approximation (MPFA), and fluid exchanges between the anisotropic continua and the large-scale fracture control volumes are precisely calculated using the IEDFM. Empirical models are used to calculate the displacement of natural fractures, and analytical models are used to calculate the aperture changes of hydraulic fractures. The overall deformation of a fractured rock is described using an equivalent method. The coupled geomechanics-fluid flow system is discretized by the finite element-finite volume method (FV-FEM) and solved using the fixed-stress split iterative coupling approach. Several examples are presented to demonstrate the applicability of the proposed method. The hybrid model is first employed to simulate water flooding process in a naturally fractured reservoir with multi-scale fractures. Effects of different scales of fractures, geomechanics coupling and capillary pressure are investigated. A case of producing from horizontal well in a hydraulic fractured tight oil reservoir is then studied, where the hydraulic fractures are modeled explicitly using IEDFM and the stimulation areas around hydraulic fractures are modeled using DPDK. Effects of stimulation area size on the pressure depletion and on the stress evolution process in the reservoir are investigated.
- Well Completion > Hydraulic Fracturing (1.00)
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Naturally-fractured reservoirs (1.00)
- Reservoir Description and Dynamics > Reservoir Simulation (1.00)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (1.00)
Abstract Computational Stratigraphy (CompStrat) is a state-of-the-art earth-modeling method that captures the key heterogeneities in subsurface reservoirs through modeling of the detailed flow and sediment transportation processes in various depositional environments. The method is fully based on physics and generates high-resolution 3D earth models that are much more geologically realistic than those generated by traditional earth-modeling methods. It can accurately predict and preserve those spatially continuous but vertically thin and volumetrically insignificant layers, such as shale layers, thus enabling a much more accurate representation of natural reservoir connectivity. In the past few years, CompStrat has been studied mainly within the earth science community and has yet been broadly applied in reservoir simulation research and practices. Our objective is to bridge this gap and allow this frontier technology to offer geologically realistic earth models for reservoir simulation to better understand how various geological features contribute and control subsurface flow patterns and performance, and subsequently leading to a better integration among earth modeling, flow simulation, and more reliable reservoir performance predictions. CompStrat models often have large number of cells (hundreds of millions or more). A large proportion of them are related to thin shale layers. These thin cells can often cause convergence difficulties in reservoir simulations. We developed a grid coarsening method to drastically reduce the cell number and the simulation time with minimum altering of overall model connectivity characteristics. The method reduces the cell number by 85% to 93% and the simulation time by 94% to 99.4% with limited loss of accuracy for representative examples. Without this method, the simulation may take impractically long time to run for large models with complex multiphase flow dynamics. The successful removal of the computational bottleneck enables the application of this frontier earth-modeling method in high-fidelity reservoir simulation. It also facilitates detailed understanding of the connection between geology and flow to offer valuable insight for reservoir modeling, production forecast uncertainty analysis, and history matching. We developed a method to label, evaluate, and rank geological features based on their influence on flow performance, with shale layers being the specific focus. The labeling is performed semi-automatically and the evaluation and ranking is done efficiently with a reduced-physics solver. The result is statistically consistent across multiple realizations.
- Geology > Sedimentary Geology (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (1.00)
- Geology > Geological Subdiscipline (1.00)
- Reservoir Description and Dynamics > Reservoir Simulation > Scaling methods (1.00)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Geologic modeling (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (1.00)
Abstract Accurate simulation of the thermoporoelasticity problems is beneficial for the exploitation activities of aquifers, geothermal, and hydrocarbon reservoirs. Simulating such problems using a finite-element Continuous Galerkin scheme (CG) lacks local energy/mass conservation. Despite being a conservative scheme, Discontinuous Galerkin (DG) is computationally expensive with much higher degrees of freedom (DoFs). This paper presents the Enriched Galerkin scheme (EG) implementation for thermoporoelasticity problems to ensure local energy/mass conservation with fewer DoFs.
- Reservoir Description and Dynamics > Reservoir Simulation (1.00)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (0.72)
- Reservoir Description and Dynamics > Reservoir Characterization > Reservoir geomechanics (0.69)
- Reservoir Description and Dynamics > Non-Traditional Resources > Geothermal resources (0.47)
A Practical Approach to Select Representative Deterministic Models Using Multi-Objective Optimization from an Integrated Uncertainty Quantification Workflow
Gao, Guohua (Shell Global Solutions, US Inc.) | Lu, Hao (Shell Global Solutions International B.V.) | Wang, Kefei (Shell Exploration & Production Company) | Jost, Sean (Shell Global Solutions, US Inc.) | Shaikh, Shakir (Shell Global Solutions, US Inc.) | Vink, Jeroen (Shell Global Solutions International B.V.) | Blom, Carl (Shell Global Solutions International B.V.) | Wells, Terence (Shell Global Solutions International B.V.) | Saaf, Fredrik (Shell Exploration & Production Company)
Abstract Selecting a set of deterministic (e.g., P10, P50 and P90) models is an important and difficult step in any uncertainty quantification workflow. In this paper, we propose to use multi-objective optimization to find a reasonable balance between often conflicting features that must be captured by these models. We embed this approach into a streamlined uncertainty quantification workflow that seamlessly integrates multi-realization history-matching (MHM), production forecasting with uncertainty ranges and representative, deterministic model selection. Some uncertain parameters strongly impact simulated responses representing historic (production) data and are selected as active parameters for history-matching, whereas others are important only for forecasting. An ensemble of conditional realizations of active history match parameters is generated in the MHM stage using a distributed optimizer, integrated with either randomized-maximum-likelihood (RML) or Gaussian-mixture-model (GMM). This ensemble is extended with unconditional realizations of forecast parameters generated by sampling from their prior distribution. Based on production forecasting results from simulations of this ensemble representing the posterior uncertainty distribution, representative (P10/P50/P90) models are selected using multi-objective optimization. In addition to matching target values of the primary and a few secondary key performance indicators (e.g., cumulative oil/gas/water production, recovery factor, etc.), selected representative models often must satisfy other requirements or constraints, e.g., the value of some key parameters must be within a user specified tight range. It can be quite difficult to find a set of representative models that satisfy all requirements. Even more challenging, some requirements may be conflicting with others such that no single model can satisfy all requirements. To overcome these technical difficulties, this paper proposes formulating different requirements and constraints as objectives and applying a multi-objective optimization strategy to find a set of Pareto optimal solutions based on the concept of dominance. One or more representative models can then be selected from the set of optimal solutions according to case dependent preferences or requirements. The proposed method is tested and validated on a realistic example. Our results confirm that the proposed method is robust and efficient and finds acceptable solutions with no violation or minimal violations of constraints (when conflicting constraints are present). These results suggest that our advanced multi-objective optimization technique can select high-quality representative models by striking a balance between conflicting constraints. Thus, a better decision can be made while running much fewer simulations than would be required with traditional methods.
- North America > United States > Texas (1.00)
- Europe (1.00)
- Asia (0.93)
- Research Report > New Finding (1.00)
- Research Report > Experimental Study (0.86)
- Information Technology > Artificial Intelligence > Representation & Reasoning > Optimization (1.00)
- Information Technology > Artificial Intelligence > Representation & Reasoning > Uncertainty > Bayesian Inference (0.48)
- Information Technology > Artificial Intelligence > Machine Learning > Learning Graphical Models > Directed Networks > Bayesian Learning (0.34)
A Sequentially Coupled THM Model for Fractured Enhanced Geothermal Systems using XFEM and Hybrid EDFM and MINC Models
Yu, Xiangyu (Colorado School of Mines) | Yan, Xia (China University of Petroleum, East China) | Wang, Cong (Saudi Aramco) | Wang, Shihao (Chevron N America Upstream) | Wu, Yu-Shu (Colorado School of Mines)
Abstract The long-term fluid circulation of Enhanced Geothermal Systems (EGS) involves complex coupled Thermal-Hydrological-Mechanical (THM) processes dominated by hydraulic and induced natural fractures. The hydraulic fracture of arbitrary shape in response to pressure changes and thermal strains can be handled by the three-dimensional (3D) eXtended Finite Element Method (XFEM). The induced/natural fractures are incorporated into the model and treated as one continuum of the Multiple INteracting Continua (MINC) for the investigation of their impacts. A TOUGH-code-based program, TOUGH2-EGS, is utilized to simulate the Thermal-Hydrological processes. The 3D Embedded Discrete Fracture Method (EDFM), compatible with the 3D XFEM, is adopted to model the hydraulic fracture. TOUGH2-EGS is then coupled with an XFEM simulator by the sequentially coupled fixed-stress split approach. The convergence performance of this coupling scheme is firstly analyzed by introducing the fracture stiffness coefficient into a single-fracture model. Sensitivity analyses are performed for this model in terms of injection temperature and thermal expansivity. The hybrid EDFM and MINC model is established and analyzed for an EGS with both hydraulic and induced/natural fractures. The convergence performance of the single-fracture model shows that an appropriate stiffness coefficient is essential for this model and different choices of the coefficient value result in distinct performances. The sensitivity analyses for injection temperatures and thermal expansivity are conducted by comparing effective stresses, pressure, temperature, and porosity/permeability distributions, as well as dynamic production temperature, outflow rate, and injection fracture permeability. The results illustrate that the fracture aperture is opened by the cold fluid injection and the reservoir is dominated by the thermal stress/strain. The temperature and pressure distribution are both affected by the thermal-hydrological-mechanical processes through the dynamic porosity, permeability, stress/strain, and fluid viscosity. The thermal breakthrough curves reflect that the conduction contributes the most to heating the fluid while the outflow rates demonstrate the mass loss due to the porosity/permeability altered by thermo-poro-elasticity. In the hybrid model, the enhancement of the natural fracture permeability notably delays the thermal breakthrough by allowing injected fluid to contact more hot reservoirs. Natural fracture spacing, MINC partition numbers are also varied to investigate their influence on the production behavior: the increased spacing delays the thermal breakthrough and needs more MINC partitions for modeling accuracy. Traditional coupled THM models are only applicable under the assumption of infinitesimal strains which does not hold in hydraulically fractured EGS reservoirs. The introduction of fracture stiffness stabilizes the numerical solution. The combined 3D XFEM and EDFM is capable of handling arbitrary fracture shapes in a 3D EGS model. Moreover, the hybrid hydraulic and induced/natural fracture model enables us to establish the stimulated reservoir volume of the EGS and investigate the operational and geological parameters.
- Energy > Renewable > Geothermal > Geothermal Resource (1.00)
- Energy > Oil & Gas > Upstream (1.00)
- Energy > Renewable > Geothermal > Geothermal Resource for Power Generation > Enhanced Geothermal System (0.61)
Abstract Flow coupled with geomechanics problems has gathered increased research interest due to its resemblance to engineering applications, such as unconventional reservoir development, by incorporating multiple physics. Computations for the system of such a multiphysics model is often costly. In this paper, we introduce a posteriori error estimators to guide dynamic mesh adaptivity and to determine a novel stopping criterion for the fixed-stress split algorithm to improve computational efficiency. Previous studies for flow coupled with geomechanics have shown that local mass conservation for the flow equation is critical to the solution accuracy of multiphase flow and reactive transport models, making mixed finite element method an attractive option. Such a discretization maintains local mass conservation by enforcing the constitutive equation in strong form and can be readily incorporated into existing finite volume schemes, that are standard in the reservoir simulation community. Here, we introduced a posteriori error estimators derived for the coupled system with the flow and mechanics solved by mixed method and continuous Galerkin respectively. The estimators are utilized to guide the dynamic mesh adaptivity. We demonstrate the effectiveness of the estimators on computational improvement by a fractured reservoir example. The adaptive method only requires 20% of the degrees of freedom as compared to fine scale simulation to obtain an accurate solution. To avoid solving enormous linear systems from the monolithic approach, a fixed-stress split algorithm is often adopted where the flow equation is resolved first assuming a constant total mean stress, followed by the mechanics equation. The implementation of such a decoupled scheme often involves fine tuning the convergence criterion that is case sensitive. Previous work regarding error estimators with the flow equation solved by Enriched Galerkin proposed a novel stopping criterion that balances the algorithmic error with the discretization error. The new stopping criterion does not require fine tuning and avoids over iteration. In this paper, we extend such a criterion to the flow solved by mixed method and further confirm its validity.
- Reservoir Description and Dynamics > Reservoir Simulation (1.00)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization (1.00)
- Production and Well Operations > Well & Reservoir Surveillance and Monitoring > Downhole and wellsite flow metering (0.89)
Summary The representation of faults and fractures using cut-cell meshes often results in irregular non-orthogonal grids. Simple finite volume approaches fail to handle complex meshes because they are highly prone to grid orientation effects and only converges for K-orthogonal grids. Wide stencil approaches and higher order methods are computationally expensive and impractical to adopt in commercial reservoir simulators. In this work, we implement an Enriched Galerkin (EG) discretization for the flow and transport problems on non-orthogonal grids. The EG approximation space combines continuous and discontinuous Galerkin methods. The resulting solution lies in a richer space than the the two-point flux approximation (TPFA) method and allows a better flux approximation. It also resolves the inconsistencies that are usually associated with TPFA scheme. The method is tested for various non-orthogonal mesh configurations arising from different fault alignments. The performance of the scheme is also tested for reservoirs with strong anisotropy as well as reservoirs with heterogeneous material properties.
Coupled CO2 Injection Well Flow Model to Assess Thermal Stresses under Geomechanical Uncertainty
Andrianov, Nikolai (Geological Survey of Denmark and Greenland, GEUS) | Amour, Frédéric (Technical University of Denmark) | Hajiabadi, Mohammad Reza (Technical University of Denmark) | Nick, Hamidreza M. (Technical University of Denmark) | Haspang, Martin Patrong (Gas Storage Denmark)
Abstract We develop a two-phase transient non-isothermal wellbore flow model, augmented with a radial heat conduction in the annulus, casing, and the reservoir. Using the available data for a saline aquifer in Denmark, we build a one-dimensional geomechanical well model and assess the stresses at the wellbore wall using the analytical Kirsch formula. Using the temperature at the wellbore wall, we calculate the corresponding thermal stresses. Furthermore, we assess the impact of the uncertainty in thermal expansion coefficients on the magnitudes of thermal stresses. For the cases considered, the magnitude of the changes in the critical pressure and in the fracture pressure with and without thermal stresses does not exceed 3%.
- Europe > Denmark (0.68)
- North America > United States > California (0.28)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock (0.71)
- Oceania > Australia > Western Australia > Perth Basin > Carynginia Shale Formation (0.99)
- Europe > Norway > North Sea > Central North Sea > Central Graben > PL 019 > Gassum Formation (0.99)
- Europe > Denmark > North Sea > Danish Sector > Central Graben > Block 5504/12 > Tyra Field (0.98)
- Europe > Denmark > North Sea > Danish Sector > Central Graben > Block 5504/11 > Tyra Field (0.98)
Abstract The training speed is slow for the convolutional neural network (CNN)-based physics-informed neural network (PINN) in surrogate models and it is difficult to be applied to large-scale engineering problems. The Fourier Neural Operator (FNO) network can speed up 100 times faster than the PINN according to current literature. But the current FNO only handles the 3D (x, y, t) spatial-temporal domain. In this work, we developed a new framework to simulate the 4D (x, y, z, t) subsurface flow problems using the FNO network and the domain decomposition method. After numerical simulation runs, the obtained results of subsurface flow field distributions in 4D spatial-temporal domain (x, y, z, t) are decomposed into multiple 3D spatial-temporal domains (x, y, t) in the z dimension. Then, multiple FNO networks are used to train 3D spatial-temporal domain (x, y, t) in parallel to predict the distributions of the flow field in subsequent time steps. Finally, the predicted results of the 4D spatial-temporal solution in subsequent time steps are obtained by re-coupling the trained 3D (x, y, t) results in the z dimension. In this way, our new framework successfully extends FNO-network from 3D (x, y, t) to 4D (x, y, z, t) to predict field distributions in subsurface flow. The new framework was successfully applied to some very complex cases of CO2 injection for enhanced oil recovery (EOR) in compositional simulations. The predicted accuracy is enough for the method to be applied to simulate the complex CO2 EOR in fractured systems. The computational speed in 4D (x, y, z, t) can be as fast as it does in 3D (x, y, t) through parallel training. The tested results show that our new framework can efficiently simulate the EOR processes by injecting CO2 into complex fracture reservoirs. For the first time, we developed a new methodology that successfully extends the current FNO network from 3D (x, y, t) to 4D (x, y, z, t). Our framework paves way for the fast FNO network to solve the large-scale spatial-temporal domain of reservoir engineering systems.
- Research Report > New Finding (0.48)
- Research Report > Experimental Study (0.34)
Abstract Long-term production of gas from the Groningen field has led to subsidence and seismicity in the region. Most of the prior Groningen modeling studies assumed elastic deformation of the reservoir due to the challenges in modeling poroplasticity in a reservoir with hundreds of faults and decades of production history. Here we quantify the role of inelastic deformation in production-induced subsidence and seismicity in the field via 3D high-resolution multiphysics modeling which couples multiphase flow and elastoplastic deformation in a complex geologic system made of claystone overburden, carboniferous underburden, and the gas-bearing sandstone reservoir compartmentalized with 100+ faults. We drive the model with four decades of historical production, spanning the period of induced seismicity, and two decades of future production under gas injection-enhanced recovery. We calibrate the model using the available pressure and subsidence data and analyze compartmentalized depletion and deformation due to spatially varying production and fault distribution. We analyze stress and strain in the caprock-reservoir depth interval to elucidate the role of inelasticity. We use the evolution in shear and normal tractions on seismogenic faults that hosted 1991-2012 seismicity to quantify the evolution in Coulomb stress and geomechanical stability of the faults.
- Europe > Netherlands > Groningen (0.87)
- Europe > Netherlands > Groningen Province (0.73)
- North America > United States > California > Los Angeles County (0.28)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Sandstone (0.69)
- Geology > Structural Geology > Tectonics > Plate Tectonics > Earthquake (0.49)
- North America > United States > Texas > Permian Basin > Yeso Formation (0.99)
- North America > United States > Texas > Permian Basin > Yates Formation (0.99)
- North America > United States > Texas > Permian Basin > Wolfcamp Formation (0.99)
- (25 more...)