Displays

The Hydraulic Fracturing Test Site (HFTS) project, fielded a few years ago within the Wolfcamp Formation in the Permian Basin in the United States, provides an excellent opportunity to further develop our understanding of the geomechanical response to hydraulic stimulation and associated production in shale lithologies. In addition to a full set of geophysical and tracer observations, the project obtained core samples from wells drilled through the stimulated region, characterizing the propagation of fractures, reactivation of pre-existing natural fractures, and placement of proppant. In addition to providing an overview of the available field data from the field test, we describe here a multi-scale modeling effort to investigate the hydrologic, mechanical and geochemical response of the Wolfcamp Formation to stimulation and production. The ultimate outcome of this project is the application and validation of a new framework for microscopic to reservoir scale simulations, built upon a fusion of existing high performance simulation capabilities.

The modeling occurs across two spatial domains – the “reservoir scale”, which encompasses the intra- and inter-well regions, and the “inter-fracture scale”, which is the region between stimulated fractures. Physics-based simulations of the fracture network evolution upon stimulation at the reservoir scale using the simulator GEOS provide input for reservoir-scale production simulations conducted with the TOUGH family of codes. At the inter-fracture scale, the fluid dynamics and reactive transport Chombo-Crunch code is used simulate the micro-scale pore-resolved physical processes occurring at the fracture and rock interfaces upon stimulation and production, tested against laboratory studies of proppant transport and pore-scale reactions. Micro-scale modeling and imaging provides upscaled flow and transport parameters for larger-scale reservoir modeling and production optimization.

How to cite: Birkholzer, J., Morris, J., Bargar, J., Cihan, A., Crandall, D., Deng, H., Fu, P., Hakala, A., Hao, Y., Jew, A., Kneafsey, T., Lopano, C., Molins Rafa, S., Nakagawa, S., Moridis, G., Reagan, M., Settgast, R., Steefel, C., and Voltolini, M.: Multi-Scale Simulation of Hydraulic Fracturing and Production: Testing with Comprehensive Data from the Hydraulic Fracturing Test Site in the Permian Basin, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19988, https://doi.org/10.5194/egusphere-egu2020-19988, 2020.

Characterization of coupled hydro-mechanical (HM) processes in rock fractures is important for several key geosciences applications, such as rock slope stability, enhanced geothermal systems, and hydraulic fracturing. In-situ experimentation of these processes is challenging, and presently very few techniques exist for quantifying the parameters needed to calibrate hydromechanical models for fractured rocks at field scales. One recent field technology is the step-rate injection method for fracture in-situ properties (SIMFIP) developed by Guglielmi et al. (2014). The method measures simultaneously the time evolution of flow rate, pressure and three-dimensional deformation of the test interval at high resolution.

In June 2019 a set of SIMFIP experiments was carried out in Åre, Sweden, in the COSC-1 borehole. This is a 2.5 km deep borehole aimed primarily for scientific investigations and the fractures and intact rock sections in the borehole are well characterized. Based on the earlier characterization work, three sections were selected for SIMFIP testing: one intact rock section, one section containing a conductive fracture and one section containing a non-conductive fracture (Niemi et al., in prep.).

In this study, a coupled HM model is developed to represent the key coupled processes occurring during these SIMFIP tests. A fully-coupled vertex-centered finite volume scheme and a decoupled finite element model are implemented independently to simulate the elastic deformations and changes in pressure induced by the step-rate injection or flow back of given water volumes. Specifically, the two models are implemented in the commercial simulator COMSOL Multiphysics (sequentially coupled FEM), and the free-open source academic code DuMu^X based on the models of Beck (2019). The models are used to match the pressure recorded by the high precision sensors in the test interval. A parametric study is carried out to mimic the fracture extension and step-down stages of the experiments and to investigate the influence of the key hydromechanical parameters (hydraulic aperture, permeability, storativity, and elastic moduli) on the observed data. The resulting coupled hydromechanical model will be further developed to study the three-dimensional deformation of the borehole section under the SIMFIP test.

Beck M (2019) Conceptual approaches for the analysis of coupled hydraulic and geomechanical processes. Ph.D. Thesis, Stuttgart University

Guglielmi Y, Cappa F, Lançon H, Janowczyk JB, Rutqvist J, Tsang CF, and Wang JSY. (2014) ISRM Suggested Method for Step-Rate Injection Method for Fracture In-Situ Properties (SIMFIP): Using a 3-Components Borehole Deformation Sensor. Rock Mech Rock Eng 47:303–311. https://doi.org/10.1007/s00603-013-0517-1

Niemi, Auli, Yves Guglielmi, Patrick Dobson, Paul Cook, Chris Juhlin, Chin-Fu Tsang, Benoit Dessirier, Alexandru Tatomir, Henning Lorenz, Farzad Basirat, Bjarne Almqvist, Emil Lundberg and Jan-Erik Rosberg 'Coupled hydro-mechanical experiments on fractures in deep crystalline rock at COSC-1 – Field test procedures and first results’. Manuscript under preparation, to be submitted to Hydrogeology Journal.

How to cite: Tatomir, A., Basirat, F., Tsang, C.-F., Guglielmi, Y., Dobson, P., Cook, P., Juhlin, C., and Niemi, A.: Coupled Hydro-Mechanical Modeling of Fracture Normal Displacement and Fluid Pressures during a SIMFIP (step-rate injection method for fracture in-situ properties) Test, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7387, https://doi.org/10.5194/egusphere-egu2020-7387, 2020.

Mineral dissolution is a micro-scale process, which may significantly alter the microstructure of rocks, and consequently affect their effective mechanical behavior at the macro scale. Predicting changes in rock stiffness is of paramount importance within the context of risk assessment for most applications related to geological subsurface utilization, where reduction of mechanical parameters is of particular relevance to assess reservoir, caprock and fault integrity [1].

In the present study, the effective elastic properties of typical reservoir rocks are determined based on micro-computer tomography (micro-CT) scans. The resulting three-dimensional rock geometry comprises a more realistic microstructure regarding the shapes of grains, cements and the overall porous network compared to available empirical approaches. Effective rock stiffness is calculated by a static finite element method, which imposes an uniform strain on the digital rock sample and calculates the resulting stresses. The effect of spatial cement distribution within the pore network is taken into account, considering passive pore filling as well as framework supporting cements. Rock stiffness increases due to the precipitation of pore-filling minerals. This quantitative approach substantially improves the accuracy in predicting elastic rock properties compared to general analytical methods, and further enables quantification of uncertainties related to spatial variations in mineral distribution.

[1] Wetzel M., Kempka T., Kühn M. (2018): Quantifying Rock Weakening Due to Decreasing Calcite Mineral Content by Numerical Simulations. Materials, 11, 4, 542. DOI: http://doi.org/10.3390/ma11040542

How to cite: Wetzel, M., Kempka, T., and Kühn, M.: Mechanical effects of rock cement alteration quantified using digital rock physics, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-429, https://doi.org/10.5194/egusphere-egu2020-429, 2020.

Over the last few years, our understanding of the processes involved in the application of Kinetic Interfacial Sensitive (KIS) tracers in two-phase flow as a means to quantify the fluid-fluid interfacial area has been enhanced with the use of controlled column experiments (Tatomir et al. 2015,2018). However, there are still some open questions regarding the effect of immobile water, either as capillary and dead-end trapped water or as a film, and the measured by product concentration at the outflow.

In this study, a new pore-scale reactive transport model is presented, based on the phase-field method, which is able to deal with the KIS tracer interfacial reaction and selective distribution of the by-production into the water phase. The model is validated by comparing the analytical solutions for a diffusion process across the interface and a reaction-diffusion process, and is tested for a drainage process in a capillary tube for different Péclet numbers. The applicability of the model is demonstrated in a realistic 2D porous medium NAPL/water drainage scenario used in the literature. Four case studies are investigated in detail to obtain macroscopic parameters, like saturation, capillary pressure, specific interfacial area, and concentration, for a number of combinations between the inflow rate, the contact angle and diffusivity. We derive a relation between the by-product mass at the outflow and the mobile part of the interfacial area, which is formulated by adding a residual factor. This term relates to the part of the by-product produced by mobile interface that becomes residual in the immobile zones.

How to cite: Gao, H., Tatomir, A., Karadimitriou, N., and Sauter, M.: A phase field method pore-scale model for simulating kinetic interface sensitive tracers reactive transport in porous media two-phase flow systems, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5460, https://doi.org/10.5194/egusphere-egu2020-5460, 2020.

A successful strategy for speeding up coupled reactive transport simulations at price of acceptable accuracy loss is to compute geochemistry, which represents the bottleneck of these simulations, through data-driven surrogates instead of ‘full physics‘ equation-based models [1]. A surrogate is a multivariate regressor trained on a set of pre-calculated geochemical simulations or potentially even at runtime during the coupled simulations. Many available algorithms and implementations are available from the thriving Machine Learning community: tree-based regressors such as Random Forests or xgboost, Artificial Neural Networks, Gaussian Processes and Support Vector Machines just to name a few. Given the ‘black-box‘ nature of the surrogates, however, they generally disregard physical constraints such as mass and charge balance, which are of course of paramount importance for coupled transport simulations. A runtime check of error of balances in the surrogate outcomes is therefore necessary: predictions offending a given tolerance must be rejected and the full physics chemical simulations run instead. Thus the practical speedup of this strategy is a tradeoff between careful training of the surrogate and run-time efficiency.

In this contribution we demonstrate that the use of surrogates can lead to a dramatic decrease of required computing time, with speedup factors in the order of 10 or even 100 in the most favorable cases. Thus, large scale simulations with some 10⁶ grid elements are feasible on common workstations without requiring computation on HPC clusters [2].

Furthermore, we showcase our implementation of Distributed Hash Tables caching geochemical simulation results for further reuse in subsequent time steps. The computational advantage here stems from the fact that query and retrieval from lookup tables is much faster than both full physics geochemical simulations and surrogate predictions. Another advantage of this algorithm is that virtually no loss of accuracy is introduced in the simulations. Enabling the caching of geochemical simulations through DHT speeds up large scale reactive transport simulations up to a factor of four even when computing on several hundred cores.

These algorithmical developments are demonstrated in comparison with published reactive transport benchmarks and on a real-life scenario of CO₂ storage.

[1] Jatnieks, J., De Lucia, M., Dransch, D., Sips, M. (2016): Data-driven surrogate model approach for improving the performance of reactive transport simulations. Energy Procedia 97, pp. 447-453. DOI: 10.1016/j.egypro.2016.10.047

[2] De Lucia, M., Kempka, T., Jatnieks, J., Kühn, M. (2017): Integrating surrogate models into subsurface simulation framework allows computation of complex reactive transport scenarios. Energy Procedia 125, pp. 580-587. DOI: 10.1016/j.egypro.2017.08.200

How to cite: De Lucia, M., Engelmann, R., Kühn, M., Lindemann, A., Lübke, M., and Schnor, B.: Speeding up reactive transport simulations: statistical surrogates and caching of simulation results in lookup tables, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17719, https://doi.org/10.5194/egusphere-egu2020-17719, 2020.

In the present study, a pre-existing stoichiometric equilibrium model based on direct minimization of Gibbs free energy has been further developed and applied to estimate the equilibrium composition of synthesis gases produced by the gasification of carbon-rich feedstock (e.g., coal, municipal waste or biomass) in a fixed-bed reactor [1]. Our modeling approach is validated against thermodynamic models, laboratory gasification and demonstration-scale experiments reported in the literature. The simulated synthesis gas compositions have been found to be in good agreement under a wide range of different operating conditions. Consequently, the presented modeling approach enables an efficient quantification of synthesis gas compositions derived from feedstock gasification, considering varying feedstock and oxidizer compositions as well as pressures and temperatures. Furthermore, the developed model can be easily integrated with numerical flow and transport simulators to simulate reactive transport of a multi-componentgas phase.

[1] Otto and Kempka, Synthesis gas composition prediction for underground coal gasification using a thermochemical equilibrium modeling approach, Energies (in review)

How to cite: Otto, C. and Kempka, T.: Thermochemical equilibrium modeling approach for carbon-rich feedstock gasification validated against laboratory and large-scale experiments, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18348, https://doi.org/10.5194/egusphere-egu2020-18348, 2020.

The energy supply in Germany is subject to a profound change. The present paper addresses the German potential for the innovative idea of storing excess energy from renewable power sources in the form of hydrocarbons, which can be used in a closed cycle to produce electricity in an environmentally friendly manner [1].

Excess electricity from wind and sun can be transformed into hydrogen, and with carbon dioxide subsequently into methane until large hydrogen storage capacities become available. When needed, electricity is regained in a combined cycle plant combusting the methane. To close the carbon cycle, carbon dioxide is captured on site. Two subsurface storage formations for both gases are required for the technology [2]. We studied a regional show case for the city of Potsdam and worked out the overall energy and cost efficiency [3]. Our results demonstrate that this extended way of power-to-gas is not only technically, but also economically feasible compared to other state-of-the-art excess energy storage technologies [4].

Here, we are taking into account the actual German storage capacity for natural gas. The most recent development is characterised by stagnation of the available total working gas volume and an increase in the significance of cavern storage at the expense of porous reservoirs. This resulted in the decommissioning of a couple of storage sites within the last years. In view of the fact that natural gas is still second most important for Germany’s primary energy provision, those sites should better be used to store excess energy from renewables instead of their abandonment. We show that the technology to store excess energy in form of methane via power-to-gas is available and ready for operation and that the potential within the German subsurface is enormous. This provides an intermediate option to reduce greenhouse gas emissions while hydrogen storage is still under research and development.

[1] Kühn M. (2013): System and method for ecologically generating and storing electricity. - Patent WO 2013156611 A1

[2] Streibel M., Nakaten N.C., Kempka T., Kühn M. (2013): Analysis of an Integrated Carbon Cycle for Storage of renewables. - Energy Procedia, 40, pp. 202-211

[3] Kühn M., Nakaten N.C., Streibel M., Kempka T. (2014): CO₂ Geological Storage and Utilization for a Carbon Neutral “Power-to-gas-to-power” Cycle to Even Out Fluctuations of Renewable Energy Provision. - Energy Procedia, 63, pp. 8044-8049

[4] Nakaten N.C., Chabab E., Kempka T., Kühn M. (2019): An Updated Classification of the Enhanced Power-to-Gas-to-Power Competitiveness Based on Integrated Geological Storage. - 14^th Greenhouse Gas Control Technologies Conference Melbourne 21-26 October 2018 (GHGT-14)

How to cite: Kühn, M., Nakaten, N. C., and Kempka, T.: Huge subsurface storage potential for excess energy already available in Germany, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6085, https://doi.org/10.5194/egusphere-egu2020-6085, 2020.

Excess electricity produced from renewables can be converted into CH₄ by consuming CO₂ and H₂ by means of the Power-to-Gas (PtG) technology ^[1]. Previous work indicates that subsurface storage of CO₂ and CH₄ can meet the projected energy storage requirements ^{[1] [2]}. However, gas mixing occurs if both gases are stored in the same reservoir ^[3], and energy is lost if CH₄ is used as cushion gas when both gases are separately stored in different reservoirs ^[2]. Therefore, an innovative approach to overcome the limitation of aforementioned storage schemes is introduced in this study. For that purpose, the focus is on a double reservoir setting in one anticline system as it is commonly found in, e.g., the Northern German Basin. Here, the confining layer and preexisting or artificial hydraulic connections between the two reservoirs enable the operator to reduce energy losses and avoid gas mixing. We have elaborated a numerical multiphase flow model including the wellbore systems and reservoirs to study the fluid flow and beneficiary effects of pressure interaction between both reservoirs. Based on the geological and operational data of our regional showcase in Germany ^{[4] [5]}, the energy storage efficiency is quantified, and the potential benefits of the proposed storage scheme are evaluated. It shows that the production of CH₄ increases by 68% over twenty years of injection and production. Furthermore, the factors that affect storage efficiency are analyzed to provide information for the optimization of PtG-based subsurface energy storage systems. The simulation can be applied to different geological systems and for parameter sensitivity studies to reduce energy losses and improve storage efficiency.

Keywords: Power-to-Gas; Subsurface gas storage; Carbon dioxide; Methane

[1] Kühn M, Nakaten N, Streibel M, Kempka T. CO₂ Geological storage and utilization for a carbon neutral “Power-to-gas-to-power” cycle to even out fluctuations of renewable energy provision. Energy Procedia. 2014; 63:8044-9.

[2] Ma J, Li Q, Kühn M, Nakaten N. Power-to-gas based subsurface energy storage: A review. Renewable and Sustainable Energy Reviews. 2018; 97:478-96.

[3] Ma J, Li Q, Kempka T, Kühn M. Hydromechanical response and impact of gas mixing behavior in subsurface CH₄ storage with CO₂-based cushion gas. Energy & Fuels, 2019; 33 (7), 6527-6541

[4] Streibel M, Nakaten N, Kempka T, Kühn M. Analysis of an integrated carbon cycle for storage of renewables. Energy Procedia 40 (2013): 202-211.

[5] Kühn M, Streibel M, Nakaten N, Kempka T. Integrated underground gas storage of CO₂ and CH₄ to decarbonise the “power-to-gas-to-gas-to-power” technology. Energy Procedia 59 (2014): 9-15.

How to cite: Ma, J., Kempka, T., Chabab, E., Li, Q., and Kühn, M.: Hydraulic interactions of subsurface reservoirs used for excess energy storage, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5656, https://doi.org/10.5194/egusphere-egu2020-5656, 2020.

Energy transition from conventional to renewable energy sources requires large energy storage capacities to balance energy demand and production, due to the fluctuating weather-dependent nature of renewable energy sources like wind or solar power. Subsurface energy storage in porous media may provide the required large storage capacities. Available storage technologies include gas storage of hydrogen, synthetic methane or compressed air. Determination of the spatial dimensions of potential geological storage structures is required, in order to estimate the achievable local storage potential. This study, therefore, investigates the energy storage potential for the three storage technologies using a part of the North German Basin as study region.

For this study, a geological model of the geological subsurface, including the main storage and cap rock horizons present, was constructed and consistently parameterized using available data from the field site. Using spill point analysis potential trap closures were identified, also considering existing fault systems and salt structures for volumetric assessment. Volumetric assessment was performed for each storage site for methane, hydrogen and compressed air, as storage gases and their gas in place volumes were calculated. The effects of uncertainty of the geological parameters were quantified accounting for porosity, permeability and the maximum gas saturation using regional petrophysical models. The total regional energy storage capacity potential was estimated for methane and hydrogen, based on their lower heating values, while an exergy analysis of methane, hydrogen and compressed air was used to compare all available storage technologies. In addition to the storage capacity, also deliverability performance under pseudo-steady state flow condition was estimated for all sites and storage gases.

The results show significant gas in place volumes of about 2350 bcm for methane, 2080 bcm for hydrogen and 2100 bcm for compressed air as a regional gas storage capacity. This capacity is distributed within three storage formations and a total of 74 potential trap structures. Storage sites are distributed rather evenly over depth, with shallow sites at about 400 - 500 m and deep sites reaching depths of about 4000 m. The exergy analysis shows that hydrogen and methane storage technologies have high exergy values of about 15.9 kWh and 8.5 kWh per m^³, due to the high chemical part of the exergy, while for compressed air energy storage only the physical part is used during storage and the corresponding value is thus reduced to 6.1 kWh. The total energy storage capacity thus identified of about 32000 TWh of methane and 8400 TWh of hydrogen, with a low estimate of 23000 TWh and 6100 TWh accounting for uncertainty of geological parameters. Thus, the potential is much larger than predicted required capacities, showing that the subsurface storage technologies have a significant potential to mitigate offsets between energy demand and renewable production in a sustainable and renewable future energy system.

How to cite: Gasanzade, F., Bauer, S., and Pfeiffer, W. T.: A comparison of the geological potential for methane, hydrogen and compressed air energy storage , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5726, https://doi.org/10.5194/egusphere-egu2020-5726, 2020.

Storage options for the energy storage in the subsurface includes the injection and storage of the “energy gas” (e.g., methane, hydrogen, compressed air) or thermal water into the underground formations. The heterogeneous structure of the storage formations could play a crucial role on the potential storage capacity, as well as the formulation of post treatment strategy. Hence, innovative techniques are required for characterizing the high-resolution formation heterogeneity and monitoring the gas or heat plume distribution in the subsurface after their injections.  Previous studies have shown that flow properties can vary as the gas or thermal water being injected into the aquifer. In this study, we propose a time-lapse hydraulic tomography (HT) method for characterizing the baseline hydraulic information and depicting the hydraulic property changes through a series of cross-well pumping tests. These tests were implemented in two pilot sites for methane and hot water injection tests at Wittstock, Germany. In order to generate a three-dimensional tomographical configuration, each pumping test was conducted at certain depth in a testing well, accompanying with multiple observation points at other wells. Depth-variant pumping and observation segments were formed by the double-packer system. As a result, we achieved 198 and 135 baseline drawdown curves for the methane and heat sites, respectively. For these measured data, we initially evaluated the effective hydraulic conductivity and specific storage of the aquifer according to certain analytical fitting methods. Furthermore, the vertical anisotropy of the hydraulic conductivity was also estimated. Sequentially, the fitted hydraulic parameters and analytical drawdown curves were utilized for correcting the well skin effects on hydraulic traveltimes and attenuations, as they have an unneglectable impact on them.  The corrected hydraulic traveltimes and attenuations were used for the inversion of the baseline hydraulic diffusivity and specific storage, respectively. Hydraulic conductivity distribution was then estimated through these two parameters. After we achieved the baseline information, HT was executed again by repeating the tomographical pumping tests after methane and hot water injections. The same data processing and inversion techniques were applied to the drawdown curves derived from the post-injection period. Inverted hydraulic diffusivity, specific storage, and hydraulic conductivity were compared to the baseline inversion results. Changes on these hydraulic properties could provide the information of the spatial distribution of methane or heat plume.

How to cite: Hu, L., Somogyvári, M., and Bauer, S.: Utilizing time-lapse hydraulic tomography to characterize the subsurface changes during methane and heat injection experiments, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7766, https://doi.org/10.5194/egusphere-egu2020-7766, 2020.

Due to its sustainability, continuity and low carbon emissions, the utilization of geothermal energy is gaining more attention all around the world. Shallow geothermal energy is usually extracted through borehole heat exchangers (BHE) with a maximum length up to 150 m. Such systems typically require large space areas, thus limiting its application in built-up urban areas. This study presents a case where deep borehole heat exchanger (DBHE) with a depth down to 2500 m was constructed to extract geothermal energy for building heating purposes. A double-continuum finite element based numerical model was set up to simulate the heat transport process within and around the DBHE. The model has been validated by the experimental data in a demonstration project located in Fengxi, Xi’an China. The heat extracting performance of DBHE under different types of boundary conditions (including the Dirichlet condition and Neumann condition) are evaluated. The amount of thermal recharges from top, sides and bottom of the domain were differentiated and quantified. It is found that different types of boundary conditions will lead to deviations in the simulated heat fluxes and corresponding thermal recharge. The numerical simulations also suggest that the sustainable heat extract capacity of DBHE is mainly determined by the stored heat from the surrounding subsurface, and thermal recharge takes only a limited contribution. According to the calibrated modelling results, the proper heat extraction rate of DBHE in the long-period operation modes is analyzed.

How to cite: Cai, W., Chen, C., Wang, F., Liu, J., Kolditz, O., and Shao, H.: Performance Evaluation and Operation Mechanism of Deep Borehole Heat Exchanger with Different Types of Boundary Conditions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5598, https://doi.org/10.5194/egusphere-egu2020-5598, 2020.

Natural gas hydrates, which are ice like crystalline solids, contain tremendous amount of potential hydrocarbon gas. Gas recovery through hydrate dissociation can be achieved through depressurization, inhibitor injection and thermal stimulation. The hydrate dissociation by depressurization involves significant pressure and temperature gradients as the dissociation process is highly endothermic. The destabilization of solid hydrate into fluid constituents causes loss of cementation which can alter the stress field which in turn changes the porosity and permeability of the hydrate bearing medium causing subsidence. In the present study, a thermo-hydro-mechanical-chemical (THMC) coupled numerical simulator is developed accounting for the hydrate phase change kinetics, non-isothermal multiphase flow and geomechanics. The point centered or node centered finite volume method is used for space discretization of flow and energy equations while the finite element method is used for stress equilibrium equation. This procedure requires the flow and mechanics variables to be co-located. The finite volumes are constructed around the flow variables defined at nodes while the finite element is defined by the corner nodes. The volumetric strain rate term in the flow equations, which couples the flow and geomechanics equations, is evaluated by interpolating the volumetric strains calculated over the finite elements to the finite volumes. Our simulations show that this procedure results in a stable convergence of the solution without the need for any stabilizing terms due to co-located variable arrangement. Our simulations also show that the iterative coupled approach, where the flow and geomechanics equations are solved separately and sequentially, gives stable convergence without any additional split terms due to sequential but iterative solving of the coupled equations.

How to cite: Samala, R. and Chaudhuri, A.: Coupled multiphase flow and geomechanics simulation of hydrate dissociation using FVM-FEM co-located variables arrangement, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6745, https://doi.org/10.5194/egusphere-egu2020-6745, 2020.

The recent development of the academic reservoir simulator MUFITS aims its transformation to a universal software package that allows for (a) numerical modelling of non-isothermal multicomponent flows in porous media under wide range of pressures and temperatures, including under critical thermodynamic conditions, (b) history matching of non-isothermal reservoir models, and (c) optimization of thermohydrodynamic processes in porous media.

The extended simulator capabilities for modelling of multicomponent flows includes a new fluid properties module for compositional and thermal reservoir simulations using different cubic equations of state (e.g. Peng-Robinson EoS). An extended library of hydrocarbons, carbon dioxide, nitrogen, water, and other components is built into the simulator, and additional components can be characterized and loaded into the library. An arbitrary number of components can be used in particular simulation. In order to simplify the module usage, the corresponding input data are made compatible with the petroleum industry standards. Unlike many other codes, MUFITS allows for compositional modelling of non-isothermal flows of fluids which properties are predicted with a cubic EoS.

For improved history matching and optimization the simulator is supplied with an external Simulation Control Unit (SCU), which automatically changes certain parameters of the digital reservoir model and reads back the results of the simulations. An external control loop is implemented in SCU. At each iteration of the loop non-isothermal flow in a porous medium is simulated, and the simulation results are used for calculation of the objective function being minimized. In order to accelerate the history matching and optimization, the SCU can simultaneously (in parallel) run several reservoir simulations. The simulator is supplied with the build-in capabilities for the calculation of gravity changes and surface uplift/subsidence which measurements can also be automatically used in history matching.

We complement the new developments with several application examples related to gas condensate fields exploration, carbon dioxide injection in depleted oil reservoirs and gas storages, and natural flows in deep geothermal systems.

We acknowledge the funding from Russian Science Foundation under grant # 19-71-10051.

How to cite: Afanasyev, A., Vedeneeva, E., and Gorokhova, N.: MUFITS: A Universal Reservoir Simulator for Numerical Modelling, History Matching and Optimization of Multicomponent Flows in Porous Media, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11914, https://doi.org/10.5194/egusphere-egu2020-11914, 2020.

Upward brine migration through permeable fault damage zones could endanger near-surface drinking water resources. Deep porous rock formations offer a large potential for gas storage, like e.g. methane or CO₂. But gas injection induces formation pressure build up, that can potentially lead to vertical or horizontal brine displacement. Here fault zones play an important role as they can act either as lateral no-flow boundaries or as permeable pathways, that allow for fluid flow and pressure dissipation. Numerical reservoir simulations, which have become an important tool for investigating these effects quantitatively, have to be performed on a regional scale, in order to include the large-scale geological faults zones. Fault zones have to be implemented into the model in a geometrically and hydraulically flexible way, to account for the variety of natural conditions encountered, as e.g. open or closed fault zone.

In order to model that complexity, the corner point grid approach has been applied by geologists for decades. The corner point grid utilizes a set of hexahedral blocks to represent geological formations. At the fault plane, where geological layers are vertically shifted, hanging nodes appear and the corner point grid cannot be used directly, if permeable fault zones have to be represented in the model. In this study we present an extension of a mesh converter, which removes hanging nodes at the fault plane by point combination, thus providing a consistent finite element mesh. Our numerical model can account for heterogeneous hydraulic properties of the fault damage zone and the enclosed fault core. The fault core is represented by one layer of 3D finite elements on each side of the fault plane. The fault damage zone consists of a continuous layer of quadrangular 2D finite elements, which are attached at the outer face of the 3D fault core elements. This model allows for fluid flow along the fault plane while fluid flow through the fault core could be adjusted by element permeability. This concept was implemented into a workflow using the FEM-simulator OpenGeoSys in combination with a mesh converter.

The concept and workflow are shown to run stable using dedicated test cases for method validation, accounting for the coupled transport of water, heat and salt mass for different fault zone setups in a synthetic multi-layered subsurface. Here we focused on brine displacement and uprising due to formation pressure increase after gas injection, which is numerically realized by Dirichlet pressure boundary conditions. Further, we will investigate the relation between computational efficiency and flow solution differences by comparing this concept with the approach of fully discretized faults. Additionally, we will apply our workflow on a real geological case in the Northern German Basin, where a fault system is close to a potential gas storage side.  

How to cite: Vehling, F., Gasanzade, F., Delfs, J.-O., and Bauer, S.: Simulation of brine migration along geological fault zones using a consistent mesh approach, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7023, https://doi.org/10.5194/egusphere-egu2020-7023, 2020.

Many different scientific open-source and commercial black-box software packages are available for the simulation of fluid flow and transport processes in the geological subsurface. Unfortunately, most of these simulators are limited by tightly integrated chemical modules with insufficient capabilities or the general lack of flexible interfaces applicable for an efficient coupling of third-party chemical libraries. Furthermore, most available open-source numerical frameworks are too complex to be used for educating geosciences students in numerical modelling techniques beyond the general application of ready-for-use simulators to specific modelling challenges. Taking into consideration that the development of a critical perspective of an emerging modeller requires fundamental analysis and understanding of common numerical modelling approaches and pitfalls, scientific source codes written in lower-level programming languages (e.g., FORTRAN, C++ or C) are per se less comprehensible compared to higher-level language implementations (e.g., Python). Hereby, the general lack of proper source code documentation, observed in many scientific open-source numerical codes additionally reduces code readability, and thus hinders code further development by third parties.
To overcome many of these limitations, the TRANsport Simulation Environment (TRANSE) has been developed based on the finite difference method. It allows for a highly flexible integration and coupling of arbitrary processes with thermodynamic and chemical libraries to consider chemical reactions and fluid equations of state. To date, TRANSE solves the pressure-based and density-driven formulation of the Darcy flow equation, coupled with the equations for transport of heat and chemical species on structured grids by simple explicit, weighted semi-implicit or fully-implicit numerical schemes, and is composed of less than 1,000 lines of Python code. A flux-corrected advection scheme can be employed in addition to pure upwinding to minimise numerical dispersion in transport problems dominated by high Péclet numbers.
Just-in-time compilation by means of the Python Numba library results in computational times in the order of equivalent lower-level language implementations (e.g., FORTRAN, C or C++), while CPU-based parallelisation allows for the realisation of high spatial model discretisations. Chemical libraries coupled to TRANSE can be easily parallelised to increase the overall computational efficiency, whereby the latter is especially relevant as chemistry usually represents the main computational bottleneck in reactive transport simulations. Python’s numpy library is used to enable fast and efficient model parametrisation as well as simulation runtime control, whereby the Matplotlib library is employed for automated visualisation. More sophisticated visualisation and post-processing are achieved by using the EVTK library for exporting VTK-compatible data to the interactive software packages VisIt, Mayavi or Paraview. 
The present contribution demonstrates the basic validity of the code implementation by comparison against standard numerical model benchmarks for heat (1D heat diffusion) and fluid flow (Theis problem), advective transport (rotating cone test), density-driven fluid flow (Henry’s and Elder’s problems) as well as available density- and viscosity-driven hydrothermal convection in porous media. A fully coupled application example considering reactive transport of gaseous chemical species at high temperatures is presented.

How to cite: Kempka, T.: Simple and efficient TRANsport Simulation Environment for density-driven fluid flow and coupled transport of heat and chemical species, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18145, https://doi.org/10.5194/egusphere-egu2020-18145, 2020.