Capillary pinning refers to the immobilization of CO₂ at capillary barriers when the uprising CO₂ pressure is lower than the capillary entry pressure of the overlaying pore throats. Also known as local capillary trapping, it has been proposed as a fifth geologic CO₂ storage mechanism, alongside structural, solubility, residual, and mineral trapping. Despite extensive research, the fragmented terminology surrounding capillary pinning has led to confusion, making it challenging to synthesize findings effectively. Often conflated with mechanisms such as residual and hysteresis trapping, capillary pinning is commonly underestimated or completely overlooked in reservoir-scale models. Furthermore, difficulties in characterizing and upscaling small-scale geologic heterogeneities that influence capillary pinning contribute to significant uncertainties, with estimates of CO₂ trapped via this mechanism ranging from 3 % to 100 % of total CO₂ trapped via capillary actions. This review explores the fundamental mechanisms, experimental findings, and modeling approaches for assessing CO₂ capillary pinning in carbon capture and storage (CCS). It seeks to bridge the gap between the reservoir engineering community, with its extensive expertise in hydrocarbon recovery but that needs adjustments for CCS applications, and the subsurface storage community, which stands to benefit from this knowledge but often lacks access to relevant literature. Additionally, the study identifies key research opportunities to advance the understanding of capillary pinning in sedimentary rocks, ultimately enhancing the efficacy and reliability of CCS operations.

We use a combination of experimental design, sketch-based reservoir modelling and flow diagnostics to rapidly screen the impact of sedimentological heterogeneities that constitute baffles and barriers on CO ₂ migration in depleted hydrocarbon reservoirs and saline aquifers of the Sherwood Sandstone Group and Bunter Sandstone Formation, UK. These storage units consist of fluvial sandstones with subordinate aeolian sand-stones, floodplain and sabkha heteroliths and lacustrine mudstones. The predominant control on effective hor-izontal permeability is the lateral continuity of aeolian-sandstone intervals. Effective vertical permeability is controlled by the lateral extent, thickness and abundance of lacustrine-mudstone layers and aeolian-sandstone layers, and the mean lateral extent and mean vertical spacing of carbonate-cemented basal channel lags in fluvial facies-association layers. The baffling effect on CO ₂ migration and retention is approximated by the pore vol-ume injected at breakthrough time, which is controlled largely by three heterogeneities, in order of decreasing impact: (1) the lateral continuity of aeolian-sandstone intervals; (2) the lateral extent of lacustrine-mudstone lay-ers; and (3) the thickness and abundance of fluvial-sandstone, aeolian-sandstone, floodplain-and-sabkha-heter-olith and lacustrine-mudstone layers. Future effort should be focused on characterizing these three heterogeneities as a precursor for later capillary, dissolution and mineral trapping.

Subsurface reservoir models have a high degree of uncertainty regarding reservoir geometry and structure. A range of conceptual models should therefore be generated to explore how fluids-in-place, reservoir dynamics, and development decisions are affected by such uncertainty. The rapid reservoir modelling (RRM) workflow has been developed to prototype reservoir models across scales and test their dynamic behaviour. RRM complements existing workflows in that conceptual models can be prototyped, explored, compared, and ranked rapidly prior to detailed reservoir modelling. Reservoir geology is sketched in 2D with geological operators and translated in real-time into geologically correct 3D models. Flow diagnostics provide quantitative information for these reservoir model prototypes about their static and dynamic behaviours. A tracing algorithm is reviewed and implemented to compute time-of-flight and tracer concentrations efficiently on unstructured grids. Numerical well testing (NWT) is adopted in RRM to further interrogate the reservoir model. A new edge-based fast marching method is developed and implemented to solve the diffusive time-of-flight for approximating pressure transients efficiently on unstructured tetrahedral meshes. We demonstrate that an implementation of the workflow consisting of integrated sketch-based interface modelling, unstructured mesh generation, flow diagnostics, and numerical well testing is possible.

Hydrocarbon reservoir models have a high degree of uncertainty regarding their reservoir geometry and structure. A range of conceptual models should therefore be generated to explore how first-order uncertainties impact fluids-in-place, reservoir dynamics, and development decisions. However, it is very time consuming to generate and explore a large number of conceptual models using conventional reservoir modelling and simulation workflows. Key reservoir concepts are therefore often locked in early and are difficult to change later. To overcome this challenge, the Rapid Reservoir Modelling (RRM) software has been developed to prototype reservoir models across scales and test their dynamic behaviour. RRM complements existing workflows in that conceptual models can be prototyped, explored, compared, and ranked rapidly prior to detailed reservoir modelling. Reservoir geology is sketched in 2D with geological operators and translated in real-time into geologically correct 3D models. Flow diagnostics provide quantitative information for these reservoir model prototypes about their static and dynamic behaviours. Numerical well testing (NWT) is implemented to further interrogate the reservoir model. The combination of surface-based reservoir modelling with geological operators, flow diagnostics and NWT on unstructured grids enable, for the first time rapid prototyping of reservoir geologies with real-time feedback on fluid flow behaviour.

Flow diagnostics is a common way to rank and cluster ensembles of reservoir models depending on their approximate dynamic behavior before beginning full-physics reservoir simulation. Traditionally, they have been performed on corner-point grids inherent to geocellular models. The rapid-reservoir-modeling (RRM) concept aims at fast and intuitive prototyping of geologically realistic reservoir models. In RRM, complex reservoir heterogeneities are modeled as discrete volumes bounded by surfaces that are sketched in real time. The resulting reservoir models are discretized by use of fully unstructured tetrahedral meshes where the grid conforms to the reservoir geometry, hence preserving the original geological structures that have been modeled. This paper presents a computationally efficient work flow for flow diagnostics on fully unstructured grids. The control-volume finite-element method (CVFEM) is used to solve the elliptic pressure equation. The flux field is a multipoint flux approximation (MPFA). A new tracing algorithm is developed on a reduced monotone acyclic graph for the hyperbolic transport equations of time of flight (TOF) and tracer distributions. An optimal reordering technique is used to deal with each control volume locally such that the hyperbolic equations can be computed in an efficient node-by-node manner. This reordering algorithm scales linearly with the number of unknowns. The results of these computations allow us to estimate swept-reservoir volumes, injector/producer pairs, well-allocation factors, flow capacity, storage capacity, and dynamic Lorenz coefficients, which all help approximate the dynamic reservoir behavior. The total central-processing-unit (CPU) time, including grid generation and flow diagnostics, is typically a few seconds for meshes with O (100,000) unknowns. Such fast calculations provide, for the first time, real-time feedback in the dynamic reservoir behavior while models are prototyped.

Flow-diagnostics are a common way to rank and cluster ensembles of reservoir models based on their approximate dynamic behaviour prior to commencing full-physics reservoir simulation. Traditionally, flow diagnostics are carried out on corner-point grids inherent to geocellular models. The novel "Rapid Reservoir Modelling" (RRM) concept enables fast and intuitive prototyping and updating of reservoir models. In RRM, complex reservoir heterogeneities are modelled as discrete volumes bounded by surfaces that can be modified using simple sketching operations in real time. The resulting reservoir models are discretized using fully unstructured 3D meshes where the grid conforms to the reservoir geometry. This paper presents a new and computationally efficient numerical scheme that enables flow diagnostic calculations on fully unstructured grids. Time-of-flight and steady-state tracer distributions are computed directly on the grid. The results of these computations allows us to estimate swept reservoir volumes, injector-producer pairs, well-allocation factors, flow capacity, storage capacity and dynamic Lorenz coefficients which all help approximate the dynamic reservoir behaviour. We use the Control Volume Finite Element Method (CVFEM) to solve the elliptic pressure equation. A scalable matrix solver (SAMG) is used to invert the linear system. A new edge-based CVFEM is developed to solve hyperbolic transport equations for time-of-flight and tracer distributions. An optimal reordering technique is employed to deal with each control volume locally such that the hyperbolic equations can be computed in an efficient node-by-node manner. This reordering algorithm scales linearly with the number of unknowns. The total CPU time, including grid generation and flow diagnostics, is typically below 3 seconds for grids with 50k unknowns. Such fast calculations provide, for the first time, real-time feedback on changes in the dynamic reservoir behaviour while the reservoir model is updated.

Constructing or refining complex reservoir models at the appraisal, development, or production stage is a challenging and time-consuming task that entails a high degree of uncertainty. The challenge is significantly increased by the lack of modeling, simulation and visualization tools that allow prototyping of reservoir models and development concepts, and which are simple and intuitive to use. Conventional modeling workflows, facilitated by commercially available software packages, have remained essentially unchanged for the past decade. However, these are slow, often requiring many months from initial model concepts to flow simulation or other outputs; moreover, many model concepts, such as large scale reservoir architecture, become fixed early in the process and are difficult to retrospectively change. Such workflows are poorly suited to rapid prototyping of a range of reservoir model concepts, well trajectories and development options, and testing of how these might impact on reservoir behavior. We present a new reservoir modeling and simulation approach termed Rapid Reservoir Modeling (RRM) that allows such prototyping and complements existing workflows. In RRM, reservoir geometries that describe geologic heterogeneities (e.g. faults, stratigraphic, sedimentologic and/or diagenetic features) are modelled as discrete volumes bounded by surfaces, without reference to a predefined grid. These surfaces, and also well trajectories, are created and modified using intuitive, interactive techniques from computer visualization, such as Sketch Based Interfaces and Modeling (SBIM). Input data can be sourced from seismic, geocellular or flow simulation models, outcrop analogues, conceptual model libraries or blank screen. RRM outputs can be exported to conventional workflows at any stage. Gridding or meshing of the models within the RRM framework allows rapid calculation of key reservoir properties and dynamic behaviors linked with well trajectories and development plans. We demonstrate here a prototype of the RRM workflow using a number of examples. The work is significant because it allows, for the first time, application of rapid prototyping methods in reservoir modeling and simulation. Such methods are widely used in other fields of engineering design and allow improved scoping of concepts and options prior, or in addition, to detailed modeling. Moreover, SBIM can be used on a range of hardware architectures, including table tops and surface PCs, fostering collaboration within integrated asset teams.