Simulating the fluid flow along fault zones at different scales is essential for predicting the CO2 leakage and containment during injection and storage. However, this can be challenging, especially in the early stages of a storage project when knowledge of the reservoir and caprock is limited and the cost of obtaining the relevant data is high. This study develops a tool for fast screening of fault leakage at the site screening stage. The tool uses a vertically integrated reservoir model coupled with a newly developed upscaled fault leakage function based on source/sink relations. The fault is conceptualized as an increased vertical permeability through the caprock due to the presence of a fracture network in the damage zone and a reduced horizontal permeability in the reservoir due to fault throw and presence of a low-permeability fault core. The proposed tool is validated against numerical simulations demonstrating strong agreement in predicting leakage rates under varying reservoir conditions. The model's capabilities are further tested through simulation cases, including a field-scale application in the Malay Basin. These cases revealed key insights into the roles of fault permeability and fault capillary entry pressure in controlling leakage and highlighted the importance of accurately characterizing these properties to mitigate risks. The computationally efficient model presented in this study is a valuable tool for quantifying uncertainties in key fault parameters, and other constitutive relations that affect the behavior of the storage reservoir and potential fault leakage.

Achieving climate neutrality requires rapid scale-up of CO2 storage to gigatonne scale. Storage clusters—multiple injection sites sharing regional aquifers—offer economic benefits but introduce new challenges in subsurface pressure management. Elevated reservoir pressures can lead to fault slip and leakage, generating environmental and operational risks that span beyond individual license areas. Current site-focused workflows are insufficient for characterizing such cross-boundary effects.

This work introduces the research activities and key ideas of the international research project MuPSI which develops an integrated, multiscale screening and simulation approach to assess geomechanical risks in storage clusters. We present results of a new screening workflow that enables rapid evaluation of pressure interference and fault activation risk across regional aquifers. This is coupled with high-resolution modeling of fault response and new software to bridge region-, project-, and fault-scales. A new highly efficient approach for pressure-stress coupling offers greater software flexibility in geomechanical assessment of individual projects.

The approach is demonstrated using North Sea case studies, including the Horda Platform (Norway) and East Mey (UK). Outputs will support operators and regulators in improving investment decisions, permitting, and cross-license coordination. MuPSI also delivers stakeholder training and knowledge-transfer tools to accelerate adoption of robust, risk-informed storage cluster design.

Carbon capture and storage (CCS) is vital to reducing greenhouse gas emissions and mitigating climate change. Most CCS projects rely on the permanent geological storage of CO2 within deep sedimentary rock formations, but accurately constraining the capacity of these reservoirs usually involves detailed and computationally demanding reservoir modelling and simulation of the pressure evolution and CO2 plume migration. In the absence of this, efficiency factors are often used within volumetric capacity estimates, but this often results in overestimations of storage capacity. As an alternative, we propose a workflow harnessing various, existing, reduced complexity models that account for the surface topography and dynamic fluid behaviour in a computationally efficient manner. We first undertook a static analysis using algorithms available within MRST-co2lab. The reservoir topography is used to determine the locations of structural traps, the trapping routes that link them and downdip filling areas that feed a given trap. This analysis provides indications of the optimal well placement and helps us refine the total capacity of the area into the capacity available just from structural trapping. We followed this with a dynamic analysis, also within MRST-co2lab, using computationally efficient Vertical Equilibrium models. This efficiency allowed us to performing hundreds of simulations and use these results to map storage efficiency and determine the optimal well placement where efficiency is greatest. We tested this workflow within an area of the Malay Basin with illustrative reservoir parameters and estimated storage efficiency, capacity and the optimal well placement within the area without performing any full-physics simulations. The results from VE modelling indicate that the amount that can be contained within this area is 15 times less than the predictions using static storage efficiency factors. The advantage of such a light approach is that sensitivity and uncertainty analysis can be carried out at speed, before targeting certain parameters/areas for more detailed study.

Simulating the fluid flow along fault zones at different scales is essential for predicting the CO2 leakage and containment during injection and storage. However, this can be challenging, especially in the early stages of a storage project when knowledge of the reservoir and caprock is limited and the cost of obtaining the relevant data is high. This study proposes a tool for fast screening of fault leakage at the site screening stage. The tool uses a vertically integrated reservoir model coupled with an upscaled fault leakage function based on source/sink relations. The fault is conceptualized as an increased vertical permeability through the caprock due to the presence of a fracture network in the damage zone and a reduced horizontal permeability in the reservoir due to fault throw and presence of a low-permeability fault core. Simulation results of various CO2 injection scenarios in a reservoir with potential for fault leakage demonstrate that the tool can produce physically consistent leakage predictions. The computationally efficient model presented in this study is a valuable tool for quantifying uncertainties in key fault parameters, and other constitutive relations that affect the behavior of the storage reservoir and potential fault leakage. By incorporating this tool into the site screening stage, stakeholders can quickly screen the risk of CO2 leakage along faults across a range of possible storage sites and subsequently design targeted data acquisition campaigns to better characterize and model the faults. Overall, the proposed tool is a cost-effective and efficient method for screening fault leakage risk during CO2 injection and storage, helping to ensure safe and effective carbon storage.

Geological carbon dioxide (CO2) storage is vital for climate change mitigation, but CO2 leakage, particularly through faults, poses significant risks. Accurately simulating the impact of fault properties across scales is crucial for predicting field-scale CO2 injection and storage outcomes. However, this task is challenging due to limited knowledge, data scarcity, and computational constraints. This study introduces a fast tool for CO2 leakage risk assessment that addresses these challenges. The tool combines a vertically integrated reservoir model with an upscaled fault leakage function based on source/sink relations. It conceptualizes faults as zones of increased vertical permeability in the caprock and reduced horizontal permeability in the reservoir. A steady-state flow approximation estimates CO2 leakage along faults. Geomechanical effects on fluid flow are modeled by coupling fault porosity and permeability, amongst several other parameters with effective stress using constitutive relations. A decoupled method based on Geertsma's uniaxial expansion coefficient, assuming zero lateral strain and constant total vertical stress is used here. Example simulations are shown to illustrate the impact of geomechanically constrained fault parameters such as capillary entry pressure and permeability on fault leakage. The fast model presented in this study is a valuable tool for identifying uncertainties in key fault parameters and other constitutive relations that affect the behavior of the storage reservoir and potential fault leakage outcomes.

Carbon capture and storage is vital for reducing greenhouse gas emissions and mitigating climate change. Most projects involve the permanent geological storage of CO2 within deep sedimentary rock formations, but accurately constraining storage capacity usually involves detailed and computationally demanding reservoir modeling and simulation. Efficiency factors can also be used but these often lead to capacity overestimations. To address this, a workflow is proposed harnessing various existing, reduced complexity models that account for the surface topography and dynamic fluid behavior in a computationally efficient manner. This workflow was tested in an area of the Malay Basin mapped from three-dimensional seismic data but with illustrative reservoir parameters. A static analysis was first undertaken using algorithms within MRST-co2lab. Structural traps, spill paths and spill regions were identified using the reservoir topography. This provided initial indications into optimal well placement and led to refinement of the total capacity of the area into the capacity available within structural traps. This was followed with a dynamic analysis, also within MRST-co2lab, using computationally efficient Vertical Equilibrium models. Hundreds of simulations were undertaken and the optimal well placement was determined based on the maximum storage efficiency achieved. The results indicated that the amount that can be contained within this area is 15 times less than equivalent predictions using static storage efficiency factors. The advantage of such a light approach is that sensitivity and uncertainty analysis can be carried out at speed, before targeting certain parameters/areas for more detailed study.

Accounting for poro-mechanical effects in full-field reservoir simulation studies and uncertainty quantification workflows using complex reservoir models is challenging, mainly because of the high computational cost. We hence introduce an alternative approach that couples hydrodynamics through existing flow diagnostics simulations with poro-mechanics to screen the impact of coupled poro-mechanical processes on reservoir performance without significantly increasing computational overheads. In flow diagnostics, time-of-flight distributions and influence regions can be used to characterise the flow field in the reservoir, which depends on the distribution of petrophysical properties that are altered due to production-induced changes in pore pressure and effective stress. These extended flow diagnostics calculations hence enable us to quickly screen how the dynamics in the reservoirs (e.g. reservoir connectivity, displacement efficiency, and well allocation factors) are affected by the complex interactions between poro-mechanics and hydrodynamics. Our poro-mechanically informed flow diagnostics account for steady-state and single-phase flow conditions based on the poro-elastic theory and assume that the reservoir does not contain fractures. Fluid flow and rock deformation calculations are coupled sequentially. The equations are discretised using a finite-volume method with two-point flux-approximation and the virtual element method, respectively. The solution of the coupled system considers stress-dependent permeabilities. Due to the steady-state nature of the calculations and the effective proposed coupling strategy, these calculations remain computationally efficient while providing first-order approximations of the interplay between poro-mechanics and hydrodynamics, as we demonstrate through a series of case studies. The extended flow diagnostic approach hence provides an efficient complement to traditional reservoir simulation and uncertainty quantification workflows and enable us to assess a broader range of reservoir uncertainties.

Accounting for poro-mechanical effects in full-field reservoir simulation studies and uncertainty quantification workflows is still limited, mainly because of their high computational cost. We introduce a new approach that couples hydrodynamics and poro-mechanics with dual-porosity flow diagnostics to analyze how poro-mechanics could affect reservoir dynamics in naturally fractured reservoirs without significantly increasing computational overhead.

Our new poro-mechanically informed dual-porosity flow diagnostics account for steady-state and single-phase flow conditions in the fractured medium while the fracture-matrix fluid exchange is approximated using a physics-based transfer rate coefficient, which models two-phase flow using an analytical solution for spontaneous imbibition or gravity drainage. The deformation of the system is described by the dual-porosity poro-elastic theory, which is based on mixture theory and micromechanics to compute the effective stresses and strains of the rock matrix and fractures. The solutions to the fluid flow and rock deformation equations are coupled sequentially. The governing equations for fluid flow are discretized using a finite-volume method with two-point flux-approximation while the governing equations for poro-mechanics are discretized using the virtual element method. The solution of the coupled system considers stress-dependent permeabilities for fractures and matrix. Our framework is implemented in the open-source MATLAB Reservoir Simulation Toolbox (MRST).

We present a case study using a fractured carbonate reservoir analog to illustrate the integration of poro-mechanics within the dual-porosity flow diagnostics framework. The extended flow diagnostics calculations enable us to quickly screen how the dynamics in fractured reservoirs (e.g., reservoir connectivity, sweep efficiency, and fracture-matrix transfer rates) are affected by the complex interactions between poro-mechanics and fluid flow where changes in pore pressure and effective stress modify petrophysical properties and hence affect reservoir dynamics.

Because of the steady-state nature of the calculations and the effective coupling strategy, these calculations do not incur significant computational overheads. They provide an efficient complement to traditional reservoir simulation and uncertainty quantification workflows because they enable us to assess a broader range of reservoir uncertainties (e.g., geological, petrophysical, and hydromechanical uncertainties). The capability of studying a much broader range of uncertainties allows the comparison and ranking from a large ensemble of reservoir models and select individual candidates for more detailed full-physics reservoir simulation studies without compromising on assessing the range of uncertainties inherent to fractured reservoirs.

Fractures are often implicitly represented in models used to simulate flow in fractured porous media. This simplification results in smaller models that are computationally tractable. As computational power continues to increase, there has been growing interest in simulation methods that explicitly represent fractures. The embedded discrete fracture model (EDFM) is one such method. In EDFM, fracture and matrix grids are constructed independently. The grids are then coupled to each other via source/sink relations. This modeling approach makes EDFM versatile and easy to use. EDFM has been shown to be able to handle complex fracture networks. The grid construction process is also straightforward and requires minimal fine-tuning. Within academia and industry, EDFM has been used to study geothermal energy production, unconventional gas production, multiphase flow in fractured reservoirs, and enhanced oil recovery processes. In this chapter, the mathematical formulation of EDFM is introduced. We then demonstrate the usage of EDFM via three examples. The first example involves a simple fracture network containing only three fractures. The second involves upscaling a stochastically generated fracture network. Finally, a well test will be simulated in a publicly available data set sourced from the Jandaira carbonate formation in Brazil.

Simulation of multiphase flow in fractured reservoirs still poses a challenge due to the different timescales of fluid flow in fractures and matrix. Common approaches to modeling fractures in reservoir simulators include the discrete fracture and matrix (DFM) method, where the fractures are explicitly represented as lower-dimensional elements in the computational mesh, and multicontinuum approaches (e.g., dual-porosity and dual-permeability models) where the behavior of the fractures and matrix are integrated and treated as distinct continua. The latter requires models (bespoke “transfer functions”) that upscale the multiphase transfer between fracture and matrix. There are several formulations for transfer functions available in the literature, and they are often application dependent. Here, we propose a unified framework for simulation of flow in fractured media. The framework makes no distinction between dual-continuum and DFM methods, treating fractures and one or more matrix domains as flowing domains and virtual domains. Transfer functions are reinterpreted as fluxes between cells of different domains. This enables us to create an abstraction that encompasses both methods and makes it easy to build hybridized models including different regions with different matrix/fracture interaction concepts. We present a series of cases to illustrate the main differences between both modeling approaches and the benefit of a flexible implementation that enables the development of a fit-for-purpose simulator for fractured reservoirs.

Accounting for poro-mechanical effects in full-field reservoir simulation studies and uncertainty quantification workflows is still limited, mainly because of their high computational cost. We introduce a new approach that couples hydrodynamics and poro-mechanics with dual-porosity flow diagnostics to analyse how poro-mechanics could impact reservoir dynamics in naturally fractured reservoirs without significantly increasing computational overhead. Our new poro-mechanical informed dual-porosity flow diagnostics account for steady-state and singlephase flow conditions in the fractured medium while the fracture-matrix fluid exchange is approximated using a physics-based transfer rate constant which models two-phase flow using an analytical solution for spontaneous imbibition or gravity drainage. The deformation of the system is described by the dualporosity poro-elastic theory, which is based on mixture theory and micromechanics to compute the effective stresses and strains of the rock matrix and fractures. The solutions to the fluid flow and rock deformation equations are coupled sequentially. The governing equations for fluid flow are discretised using a finite volume method with two-point flux-approximation while the governing equations for poro-mechanics are discretised using the virtual element method. The solution of the coupled system considers stress-dependent permeabilities for fractures and matrix. Our framework is implemented in the open source MATLAB Reservoir Simulation Toolbox (MRST). We present a case study using a fractured carbonate reservoir analogue to illustrate the integration of poro-mechanics within the dual-porosity flow diagnostics framework. The extended flow diagnostics calculations enable us to quickly screen how the dynamics in fractured reservoirs (e.g. reservoir connectivity, sweep efficiency, fracture-matrix transfer rates) are affected by the complex interactions between poro-mechanics and fluid flow where changes in pore pressure and effective stress modify petrophysical properties and hence impact reservoir dynamics. Due to the steady-state nature of the calculations and the effective coupling strategy, these calculations do not incur significant computational overheads. They hence provide an efficient complement to traditional reservoir simulation and uncertainty quantification workflows as they enable us to assess a broader range of reservoir uncertainties (e.g. geological, petrophysical and hydro-mechanical uncertainties). The capability of studying a much broader range of uncertainties allows the comparison and ranking from a large ensemble of reservoir models and select individual candidates for more detailed full-physics reservoir simulation studies without compromising on assessing the range of uncertainties inherent to fractured reservoirs.

Flow modelling challenges in fractured reservoirs have led to the development of many simulation methods. It is often unclear which method should be employed. High-resolution discrete fracture and matrix (DFM) studies on small-scale representative models allow us to identify dominant physical processes influencing flow. We propose a workflow that utilizes DFM studies to characterize subsurface flow dynamics. The improved understanding facilitates the selection of an appropriate method for large-scale simulations. Validation of the workflow was performed via application on a gas reservoir represented using an embedded discrete fracture model, followed by the comparison of results obtained from hybrid and dual-porosity representations against fully explicit simulations. The comparisons ascertain that the high-resolution small-scale DFM studies lead to a more accurate upscaled model for full field simulations. Additionally, we find that hybrid implicit–explicit representations of fractures generally outperform pure continuum-based models.

Fractures can have variable effects on fluid flow in a porous rock. Moderately conductive fractures may enhance the rock's overall effective permeability, while highly conductive fractures may completely dominate fluid transport. Fluid flow modeling is important to quantify the impact of fractures on the performance of a reservoir. However, simulating fluid flow is computationally intensive due to the heterogeneities introduced by the fracture network. In this work, complex fracture patterns are simplified using hybrid implicit-explicit representations to yield a computationally tractable model. Hybrid modeling requires the selection of a partitioning size to group fractures by size. Small fractures are upscaled with the rock matrix; large fractures are explicitly represented. Our study shows that, given a naturally fractured reservoir, an upper limit exists for the partitioning size and that this threshold partitioning size can be determined without trial and error. Using artificial and realistic fracture patterns, we created hybrid models using different partitioning sizes and subjected them to pressure drawdowns. Simulated production rates were compared against reference results obtained from simulations on the original fracture patterns. Beyond a threshold partitioning size unique to each fracture pattern, hybrid model results deviate significantly from reference solutions. The threshold is identified from the relationship between upscaled permeabilities and partitioning sizes and corresponds to the point where the effective permeability of small fractures begins to increase rapidly. The permeability-size relationship is obtained using numerical flow-based upscaling. For uniformly distributed fractures with no abutment relationships, the effective medium theory is shown to generate accurate permeability-size relationships.

Hydro-mechanical coupling is imperative when the stress disturbances induced by production/injection processes affect the reservoir performance. However, the application of coupled hydro-mechanical models in actual fullfield studies is still limited, mainly because of the high computational cost. Despite the existence of simplified coupling strategies (one-way coupling and loose coupling) that reduce the computational cost, numerical simulations remain challenging because of the significant computing time required to simulate coupled processes in complex and heterogeneous reservoir models. With the appropriate extension, flow diagnostics could also be used to screen and assess the impact of hydro-mechanical processes on reservoir performance so as to select a smaller number of models for detailed, and computationally costly, fully coupled hydro-mechanical simulations. We hence present an approach that allows us to extend the existing flow diagnostics to account for geomechanical effects without increasing the computational overhead significantly. Flow diagnostics approximate the dynamic reservoir behaviour in seconds by computing the time of flight and steady-state tracer distributions directly on the reservoir grid. Hence, the extended flow diagnostics simulations complement full-physics simulations for estimating reservoir connectivity, fluid-fronts distributions, fluid displacement efficiency and well allocation factors under geomechanical effect. The acceleration of the proposed hydro-mechanical coupling is achieved by: 1) the representation of the dynamic behaviour through the use of flow diagnostics simulations (Møyner et al., 2014); 2) the formulation of the hydromechanical problem to account for steady-state conditions based on poro-elastic theory (Coussy, 1994, 2004); 3) a sequential stress-flow coupling using stress-dependent permeability as a coupling term. This coupling strategy ensures stability and fast convergence of the hydro-mechanical solution using a stress-fixed split strategy (Kim et al., 2011a, 2011b) and yields a significant reduction of the CPU time. Two cases studies were analysed based on the SPE 10 Model (Christie and Blunt, 2001) in which the effect of a 5-spot injection pattern subjected to a gravity load is studied, and the effect of mechanical heterogeneity is considered. These examples demonstrate the application of the proposed methodology to assess geomechanical impact in highly heterogeneous formations and the importance of not only account for petrophysical heterogeneities when assessing reservoir performance but also for the heterogeneity of mechanical properties as these alter the petrophysical properties when stress-sensitive reservoirs are produced. Geomechanically informed flow diagnostics account for coupled hydro-mechanical effects that can alter the performance of stress-sensitive reservoirs during production.

Naturally fractured reservoirs hold significant reserves but are highly heterogeneous and are challenging to simulate flow in. Dual Porosity (DP) methods, although widely used, require fine tuning using production data and thus lack predictive capability in green field applications. The Embedded Discrete Fracture Model (EDFM), which explicitly represents complex fracture network geometries at the cost of computational efficiency, is an excellent tool that can complement the DP method. Using EDFM, we study water coning phenomena in a green fractured Latin American gas field. We do this by simulating gas flow in a stochastically generated sector model representative of the field. EDFM simulations performed using different well rates revealed three possible flow regimes that the field may experience: stable flooding at low flow rates, coning with matrix production at moderate flow rates, and coning without matrix production at high flow rates. These results have implications in field development plans and can also be used for validating any DP models that may be used for full field simulations in the future. Through this study, we demonstrated how EDFM can be used, before any field production, to gain insights into the flow behaviour in a green field.