740 research outputs found
A multi-scale approach for numerical modelling of the CO2 sequestration process
No full textSubsurface carbon dioxide (CO2) sequestration is a promising technology to reduce the CO2 emission into the atmosphere. After injection into subsurface formation, the carbon dioxide plume can migrate several kilometres until it is fully trapped. Four major mechanisms play an important role in trapping which include structural trapping, residual trapping, dissolution trapping or mineralization. The accurate numerical simulation of the sequestration process is challenging owing to the complexity of buoyancy driven enhanced dissolution and convective propagation of the CO2 plume. To resolve these processes, one often needs an extremely fine computational grid which makes the CPU time prohibitive for modelling at reservoir scale. Several simplified models were proposed which include analytical models (Hesse, 2008; Gasda et al., 2012), vertical equilibrium models (Gasda et al., 2012; (Pruess & Nordbotten, 2011) and an algebraic multi-scale model (Hesse, 2008). Here we proposed and applied the multi-scale models with dissolution for modelling of CO2 sequestration on the large-scale. Several numerical experiments are considered using adjusted small-scale simulation of the plume dynamic in a sloped aquifer. The enhanced rate of dissolution captured in the small-scale models with geometrical properties was then applied to the simulation in the realistic aquifer. A sink term applied at the CO2-brine-interface is implemented in the ADGPRS program. This term numerically acts as the dissolution mass transfer that would otherwise occur in a compositional simulation at fine resolution. It is important to contemplate the slow reduction in dissolution rate after the fingers begin to interact with the bottom of the reservoir. After interaction becomes significant, a reduction in the local dissolution rate is considered. We compared our multi-scale approach with a high-fidelity compositional simulation at high resolution, similar to the results presented in (Elenius, Voskov & Tchelepi, 2015). The applicability of the proposed approach was validated on the numerical model of a realistic aquifer.Applied Earth SciencesPetroleum Engineering and Geo-science
Modeling and Upscaling of Shale Gas Using a Discrete Fracture Modeling Approach
No full textGas flow in fractured nano-porous shale formations is complicated by a hierarchy of structural features, ranging from nanopores to microseismic and hydraulic fractures, and by several transport mechanisms that differ from standard viscous flow used in reservoir modelling. In small pores, self-diffusion becomes more important than advection, also slippage effect and Knudsen diffusion becomes relevant at this scale. The characteristics and properties of the fracture networks plays a major role in the performance of shale gas reservoirs, therefore the use of accurate simulation technique that honor the complexity of these reservoirs and capture the associated dynamics of nanopores is strongly required. However, these accurate simulations often necessitate a large amount of computations for field scale models and therefore require upscaling. Yet the upscalling techniques generally in use are based on idealizations that do not reflect the discrete features of the reservoir. In this work, we first incorporate the formulations of a statistical bundle of dual tube model to describe the dynamics of shale gas into a discrete fracture model. The formulation of the DFM model we use applies an unstructured control volume finite difference approach with a two point flux approximation. We then propose to upscale these detailed descriptions using two different techniques, with the major difference in their coarse grid geometry. The first approach, referred to as EDFM upscaling, relies on a structured Cartesian coarse grid. While the second method, which we call the multiple subregion (MSR) upscaling, introduces a flow based coarse grid to replicate the diffusive character of the pressure in the matrix. The required parameters for the coarse scale model in both methods and the geometry of the subregions in the second method are determined efficiently from global single-phase flow solution using the underlying discrete fracture model. The methods are applied to simulate single-phase gas flow in 2D fractured reservoir models, and are shown to provide results in close agreement with the underlying DFM and with considerable reduction in the computational time. We notice that in order to account for the prevailing transient effects in low permeability shale, the upscaled transmissibility need to be related to pressure for better results. Finally, we consider the EDFM upscaling we propose as an easier approach in its implementation, while the MSR technique as a more accurate method.Civil Engineering and GeosciencesGeoscience & Engineerin
Hierarchical coarsening of simulation model for in-situ upgrading process
No full textOil shales are sedimentary rocks containing organic matter in the form of Kerogen which accounts for more than 5 trillion barrels of oil in place according to Birol, 2010; therefore, oil shales represents a plausible solution for the constantly increasing demand for hydrocarbons. Oil shale production is currently done using two different techniques, surface retorting and in-situ retorting. The last one being the focus of this study. During this process, the sedimentary rock containing the kerogen is brought into a high-temperature environment with oxygen deficit. At this stage, the organic matter is subject to a thermo-chemical decomposition that finally releases the hydrocarbon in liquid and gas forms. This process is also known as pyrolysis. During this process, solid and fluid components experience compositional and physical changes, which requires complex chemical models represented by multiple species and several governing relations. In this work, we first developed a numerical solver for closed systems with simple kinetics models. This initial work allowed us to analyze the dynamic behavior of each component during the chemical decomposition of the kerogen and its impact in the porosity of the system. Then, we described an accurate base model for chemical decomposition of kerogen. This model was then implemented in our in house simulator ADGPRS. The model is based on the most recent understanding of pyrolysis process, and it incorporates coupling of chemical kinetics to heat and mass transport. Due to the high number of species, variations of porosity as consequence of the transformation of solid species into fluid products and complex multi-scale structure of porous media, the simulation performance of the high-fidelity model is limited. Therefore, in the second step of this work, we introduce a hierarchy of coarser models to improve the run-time of forward solution without significant reduction in accuracy. We applied coarsening in time, space, and chemical representation, and quantify errors introduced at each coarsening level. In conclusion, we provided recommendations for large-scale modeling of in-situ upgrading process.Civil Engineering and GeosciencesGeoscience & EngineeringPetroleum Engineerin
Dispersion and Heat Conduction in a Simplified Geothermal Doublet
No full textThe goal of this study is to test out the accuracy of the upscaling approach (Jinyu Tang, 2021) for a geothermal doublet. This approach tries to simulate the physical thermal dispersion. When modeling in a geothermal reservoir it would be easy if a lot of layers can be upscaled. However, when doing upscaling one can not just take an average of the layer properties. This results in a very inaccurate representation of reality. That is where the upscaling comes in. First, some other points need to be considered. The reservoir is simulated in DARTS (Wang, Voskov, Khait, & Bruhn, 2020). This simulator uses numerical methods to model the reservoir. Before starting on modeling geothermal reservoirs first a 1D case is evaluated to check for numerical dispersion that comes into play. With that evaluation done the 2D cases were simulated. The full reservoir has 91 layers, these can be upscaled into 9 layers eventually. To start building up to that scenario first 2 other scenarios are evaluated. First, an upscaled section of the first block of upscaled layers is evaluated. This was originally 10 layers and now upscaled to one layer. This one layer was first simulated in a one grid simulation and then a single grid simulation. These results are compared to a simulation of the original layer properties and a simulation of an arithmetic average of the reservoir properties. This is also done on a second scenario with 2 upscaled groups and eventually the full 9 layer reservoir (originally 91 layers). With these scenarios evaluated the upscaling shows to give a better simulation of the reservoir compared to using an average for the layer properties. This is all compared with a simulation of the original layer properties
Multiscale reconstruction in physics for compositional simulation
No full textA compositional formulation is a reliable option for understanding the complex subsurface processes and the associated physical changes. However, this type of model has a great computational cost, since the number of equations that needs to be solved in each grid block increases proportionally with the number of components employed. To address this issue, we herewith propose a multiscale reconstruction in physics for compositional simulation. The ideology consists of two stages, wherein two different sets of restriction and prolongation operators are defined based on the dynamics of compositional transport. In the first stage, an operator restricting the arbitrary number of components to only two equations for flow and transport is implemented with the objective of accurately reconstructing the multiphase boundaries in space. The prediction of multiphase front propagation is the most critical aspect of the approach, as they involve a lot of uncertainties. Once the position of two-phase boundaries is identified, the full conservative solution in the single-phase region can be accurately reconstructed based on the prolongation interpolation operator. Subsequently, in the second stage, the solution for the multicomponent problem (full system) in the two-phase region is reconstructed by solving just two transport equations with the aid of restriction operator defined based on an invariant thermodynamic path. The proposed reconstruction strategy results in coarsening of the compositional problem in terms of the physical representation (number of equations), thereby appreciably reducing the simulation time by several folds without significant loss in the accuracy. We demonstrate the applicability of the proposed multiscale strategy for several challenging gas injection problems.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Reservoir Engineerin
Empowering end-users in the energy transition: An exploration of products and services to support changes in household energy management
No full textCurrent discourse on smart grid deployment expects residential end users to play a more active role as co-providers in the electric power system. Their electricity consumption and production is considered a resource for balancing supply and demand in an electric power system with distributed generation. This means that, in addition to using energy efficiently, they, for example, have to adjust their consumption patterns to the production patterns of locally available and intermittent energy generation. This thesis explores how the technological and social contexts of smart grids can shape the role of residential end-users as co-providers in the electric power system. The main objective was to formulate implications for the development of products and services that support end-users in taking up a co-provider role. The research involved a literature review about currently applied smart grid technologies and field studies of two pilot projects in which households were equipped with smart energy technology: Energy Battle and PowerMatching City. Both cases concern the implementation of a product-service combination that was new for the household and that was aimed at enabling one or more aspects of co-providing end-user behavior. End-users’ experiences in using the implemented system were central to the research in each case. The research resulted in design implications within four themes: (1) Design of the user interface, (2) Design in relation to the social context at household and community level, (3) Integral design approach to address behavioral and technical aspects of smart energy system performance, and (4) Design of products and services as part of an experiential learning process for both developers and end-users.Design Engineering / Design for SustainabilityIndustrial Design Engineerin
Operator-based linearization approach for modeling of multiphase multi-component flow in porous media
No full textA new approach for the linearization of governing equations that describe flow and transport in porous media is proposed in this work. It is based on an approximate representation of the exact physics of the problem, which is similar to an approximate representation of space and time discretization performed in conventional simulation. The governing equations are introduced as a combination of operators, dependent on spatially altered properties and operators, fully controlled by nonlinear properties of fluid and rock. Next, a parametrization in the physics space of the problem is introduced. The property-based operators are approximated using direct interpolation in the space of nonlinear unknowns. The discrete version of the governing equations is constructed as a combination of operators that approximate both nonlinear physics and discretization in time and space. This approach is applied to the reservoir simulation of miscible and immiscible displacement processes. The performance of the method demonstrates a convergence of simulation results by resolution in physical space with the improved performance.Reservoir Engineerin
Optimization of CO<sub>2</sub> injection using multi-scale reconstruction of composition transport
No full textThe current situation with green gas emission requires the development of low-carbon energy solutions. However, a significant part of the modern energy industry still relies on fossil fuels. To combine these two contradictory targets, we investigate a strategy based on a combination of CO2 sequestration with enhanced oil recovery (EOR) in the hydrocarbon reservoirs. In such technology, the development of miscibility is the most attractive strategy from both technological and economic aspects. Modeling of this process involves solving complex nonlinear problem describing compositional flow and transport in highly heterogeneous porous media. An accurate capture of the miscibility development usually requires an extensive number of components to be present in the compositional problem which makes simulation run-time prohibitive for optimization. Here, we apply a multi-scale reconstructing of compositional transport to the optimization of CO2 injection. In this approach, a prolongation operator, based on the parametrization of injection and production tie-lines, is constructed following the fractional flow theory. This operator is tabulated as a function of pressure and pseudo-composition which then is used in the operator-based linearization (OBL) framework for simulation. As a result, a pseudo two-component solution of the multidimensional problem will match the position of trailing and leading shocks of the original problem which helps to accurately predict phase distribution. The reconstructed multicomponent solution can be used then as an effective proxy-model mimicking the behavior of the original multicomponent system. Next, we use this proxy-model in the optimization procedure which helps to improve the performance of the process several fold. An additional benefit of the proposed methodology is based on the fact that important technological features of CO2 injection process can be captured with lower degrees of freedom which makes the optimization solution more feasible.RST/Biomedical ImagingReservoir Engineerin
Operator-based linearization for efficient modeling of geothermal processes
No full textNumerical simulation is one of the most important tools required for financial and operational management of geothermal reservoirs. The modern geothermal industry is challenged to run large ensembles of numerical models for uncertainty analysis, causing simulation performance to become a critical issue. Geothermal reservoir modeling requires the solution of governing equations describing the conservation of mass and energy. The robust, accurate and computationally efficient implementation of this solution suggests an implicit time-approximation scheme, which introduces nonlinearity into the system of equations to be solved. The most commonly used approach to solving the system of nonlinear equations is based on Newton's method and involves linearization with respect to nonlinear unknowns. This stage is the most complicated for implementation and usually becomes the source of various errors. A new linearization approach – operator-based linearization – was recently proposed for non-isothermal flow and transport. The governing equations, discretized in space and time, were transformed to the operator form where each term of the equation was specified as the product of two operators. The first operator comprises physical properties of rock and fluids, such as density or viscosity, which depend only on the current state of a grid block, fully defined by the values of nonlinear unknowns. The second operator includes all terms that were not included in the first operators, and depends on both the state and spatial position of a control volume. Next, the first type of operators was parametrized over the physical space of a simulation problem. The representation of highly nonlinear physics was achieved by using multi-linear interpolation, which replaces the continuous representation of parametrized operators. The linearization of the second type of operators was applied in the conventional manner. In this work, we investigated the applicability of this approach to the geothermal processes, specifically for low-enthalpy and high-enthalpy geothermal doublet models with hydrocarbon co-production. The performance and robustness of the new method were tested against the conventional approach on a geothermal reservoir of practical interest. This approach shows significant improvement of geothermal simulation performance, while errors, introduced by coarsening in physics, remain under control. The simplicity of implementation on emerging computational architectures and nonlinearity reduction provide advanced opportunities for uncertainty quantification and risk analysis of geothermal projects.Reservoir Engineerin
Integrated Framework for Modelling of Thermal-Compositional Multiphase Flow in Porous Media
No full textVarious novel computing architectures, like massively parallel and multi-core, as well as computing accelerators, like GPUs or TPUs, keep regularly expanding. In order to exploit the benefits of these architectures to the full extent and speed up reservoir simulation, the source code has to be inevitably rewritten, sometimes almost completely. We demonstrate how to extract complex physics-related computations from the main simulation loop, leaving only an algebraic multilinear interpolation kernel instead. In combination with linear solvers, which usually have made available soon once the new architecture is introduced, the approach accommodates execution of the entire nonlinear loop on the latest hardware and computational architectures. We describe the integrated simulation framework built on top of this technique and show the applicability of the approach to various challenging physical and chemical problems. All simulation engines along with linear solvers, well controls, interpolation engines, and state operator evaluators are implemented in C++11 and exposed into Python coupling the flexibility of the script language with the performance of C++.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Reservoir Engineerin
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