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In this work, we measure the performance of the fixed stress split algorithm for the immiscible water-oil flow coupled with linear poromechanics. The two-phase flow equations are solved on general hexahedral elements using the multipoint flux mixed finite element method whereas the poromechanics equations are discretized using the conforming Galerkin method. We introduce a rigorous calculation of the update in poroelastic properties during the iterative solution of the coupled system equations. The effects of the coupling parameter on the performance of the fixed stress algorithm is demonstrated in two field studies: the Frio oil reservoir and the Cranfield injection site.

Carbon capture and storage is one of the key technologies that can help industries limit their environmental footprint and societies achieve the climate change mitigation goals. The process entails capturing CO 2 and injecting it into deep geological formations for permanent storage. However, the design and modeling of carbon sequestration projects entail significant challenges in assessing the risks and long-term consequences. The fate of CO 2 in the subsurface is dictated by many processes including solute transport, multiphase compositional effects, and trapping mechanisms. The ability to properly capture these phenomena is limited by the abstraction of numerical models, the uncertainty in petrophysical characterization, and the modeling of the thermodynamic effects. In this work, we study the impact of each of these factors on the fate of CO 2 injection in a meter-scale experimental setup. We model the evolution of the CO 2 plume inside the tank using the compositional reservoir simulator IPARS (Integrated Parallel Accurate Reservoir Simulator). We then present an ensemble-based approach to quantify the uncertainties and study the predictability of the numerical models. The results emphasize the ability of the reservoir simulator to predict the evolution of CO 2 in the FluidFlower experimental setup. They also highlight the importance of considering the uncertainty in experimental testing of petrophysical properties in the risk assessment of geological carbon storage projects.

Consistent discretization methods are a natural fit for the novel cut-cell gridding technique for reservoir simulation, which preserves the orthogonality characteristic in the lateral direction. Both uniform (global) and novel hybrid (local) variants of consistent discretization methods are implemented and tested in the vicinity of fault representations on cut-cell grids. Novel consistent discretization methods, which do not require major intrusive changes to the solver structure of industrial-grade reservoir simulators, are investigated in this work. Cell-centered methods such as multi-point flux approximation (MPFA), average multi-point flux approximation (AvgMPFA), and nonlinear two-point flux approximation (NTPFA) methods fit naturally into the framework of existing industrial-grade simulators. Thus, cut-cell compatible variants of AvgMPFA and NTPFA and their novel hybridizations with TPFA are implemented and tested. An implementation of the relatively more computationally expensive MPFA is also made to serve as accuracy reference to AvgMPFA and NTPFA. AvgMPFA and NTPFA multiphase simulation results are compared in terms of accuracy and computational performance against the ones computed with reference MPFA and TPFA methods on a set of synthetic cut-cell grid models of varying complexity including conceptual models and a field-scale model. It is observed that AvgMPFA consistently yields more accurate and computationally efficient simulations than NTPFA on cut-cell grids. Moreover, AvgMPFA-TPFA hybrids run faster than NTPFA-TPFA hybrids when compared on the same problem for the same hybridization strategy. On the other hand, the computational performance of AvgMPFA degrades more rapidly compared to NTPFA with increasing “rings” of orthogonal blocks around cut-cells. Auspiciously, only one or two “rings” of orthogonal blocks around cut cells are sufficient for AvgMPFA to deliver high accuracy.

Successful deployment of geological carbon storage (GCS) requires an extensive use of reservoir simulators for screening, ranking and optimization of storage sites. However, the time scales of GCS are such that no sufficient long-term data is available yet to validate the simulators against. As a consequence, there is currently no solid basis for assessing the quality with which the dynamics of large-scale GCS operations can be forecasted. To meet this knowledge gap, we have conducted a major GCS validation benchmark study. To achieve reasonable time scales, a laboratory-size geological storage formation was constructed (the “FluidFlower”), forming the basis for both the experimental and computational work. A validation experiment consisting of repeated GCS operations was conducted in the FluidFlower, providing what we define as the true physical dynamics for this system. Nine different research groups from around the world provided forecasts, both individually and collaboratively, based on a detailed physical and petrophysical characterization of the FluidFlower sands. The major contribution of this paper is a report and discussion of the results of the validation benchmark study, complemented by a description of the benchmarking process and the participating computational models. The forecasts from the participating groups are compared to each other and to the experimental data by means of various indicative qualitative and quantitative measures. By this, we provide a detailed assessment of the capabilities of reservoir simulators and their users to capture both the injection and post-injection dynamics of the GCS operations.

Successful deployment of geological carbon storage (GCS) requires an extensive use of reservoir simulators for screening, ranking and optimization of storage sites. However, the time scales of GCS are such that no sufficient long-term data is available yet to validate the simulators against. As a consequence, there is currently no solid basis for assessing the quality with which the dynamics of large-scale GCS operations can be forecasted. To meet this knowledge gap, we have conducted a major GCS validation benchmark study. To achieve reasonable time scales, a laboratory-size geological storage formation was constructed (the “FluidFlower”), forming the basis for both the experimental and computational work. A validation experiment consisting of repeated GCS operations was conducted in the FluidFlower, providing what we define as the true physical dynamics for this system. Nine different research groups from around the world provided forecasts, both individually and collaboratively, based on a detailed physical and petrophysical characterization of the FluidFlower sands. The major contribution of this paper is a report and discussion of the results of the validation benchmark study, complemented by a description of the benchmarking process and the participating computational models. The forecasts from the participating groups are compared to each other and to the experimental data by means of various indicative qualitative and quantitative measures. By this, we provide a detailed assessment of the capabilities of reservoir simulators and their users to capture both the injection and post-injection dynamics of the GCS operations.

Subsurface problems are inherently challenging because they involve multiple physical processes interacting with each other. Numerical models tend to break down the system into smaller problems that are easier to solve and that could be coupled within one framework. Fractured reservoirs are especially difficult to model due to the variety of physical processes that act at different scales. These processes include (1) fracture propagation, (2) flow through fractures and through the matrix, (3) hydrocarbon phase behavior, and (4) poroelastic deformations. Modeling the interaction between these processes plays an integral role in designing many energy and environmental applications. The primary objective of this work is to construct a holistic framework that can model flow and geomechanics in fractured reservoirs using computationally efficient algorithms. The framework can handle complex multiphysics problems including: multiphase flow, mechanical deformations, the capability to stimulate new fractures or activate existing ones, and the ability to seamlessly switch between propagation and production scenarios within the same simulation study. The approach includes coupling the in-house reservoir simulator (IPARS) with a phase-field fracture propagation model. In addition to hydraulic fracturing problems, the framework can model flow and geomechanics on fixed fracture networks with dynamic aperture variations. It can also simulate multiphase flow through natural fractures using general semi-structured grids. Two numerical schemes are introduced to improve the efficiency of computations. A multirate approach is proposed to enhance the performance of the $L$-scheme for decoupling the phase-field and displacement equations. A domain decomposition scheme is also presented to perform space-time refinement for flow through fractured reservoirs. Local time stepping and spatial mesh refinement can be used in the vicinity of the fractures while taking large grids cells with coarse time steps everywhere else in the reservoir. This motivates space and time adaptive mesh refinement in reservoir simulations.

Successful deployment of geological carbon storage (GCS) requires an extensive use of reservoir simulators for screening, ranking and optimization of storage sites. However, the time scales of GCS are such that no sufficient long-term data is available yet to validate the simulators against. As a consequence, there is currently no solid basis for assessing the quality with which the dynamics of large-scale GCS operations can be forecasted. To meet this knowledge gap, we have conducted a major GCS validation benchmark study. To achieve reasonable time scales, a laboratory-size geological storage formation was constructed (the \"FluidFlower\"), forming the basis for both the experimental and computational work. A validation experiment consisting of repeated GCS operations was conducted in the FluidFlower, providing what we define as the true physical dynamics for this system. Nine different research groups from around the world provided forecasts, both individually and collaboratively, based on a detailed physical and petrophysical characterization of the FluidFlower sands. The major contribution of this paper is a report and discussion of the results of the validation benchmark study, complemented by a description of the benchmarking process and the participating computational models. The forecasts from the participating groups are compared to each other and to the experimental data by means of various indicative qualitative and quantitative measures. By this, we provide a detailed assessment of the capabilities of reservoir simulators and their users to capture both the injection and post-injection dynamics of the GCS operations.