Nearly half of the Netherlands’ natural gas consump tion is allocated to heating, with direct -use geothermal heating being one of the available low-carbon energy solutions. A geothermal well doublet, designed with the two primary aims of research and commercial heat supply, is currently being installed on the campus of Delft University of Technology. The project is a key national research infrastructure and is being incorporated into the European sustainable and distributed infrastructure (EPOS: European Plate Observing System, https://www.epos-eu.org/), such that accessibility and data availability will be as wide as possible. All observations will be included in a digital-twin framework, which will allow us to make better decisions in future geothermal projects. The project includes a comprehens ive research program, involving the installation of a wide range of instruments alongside an extensive logging and coring program and monitoring network. The doublet has been cored, with substantial continuous samples from the heterogeneous reservoir, alongside a large suite of well logs in both the reservoir and overlying geological units. Such investigation is rarely undertaken in geothermal projects. A fiber-optic cable will monitor the producer well all the way down to the reservoir section, at approximately 2300m depth, in the Lower Cretaceous Delft Sandstone that is used as a geothermal reservoir in a series of existing and planned doublets in the West Netherlands Basin. A local seismic monitoring network has been installed in the surrounding area with the aim of monitoring very low-magnitude natural or induced seismicity. A vertical observation well with electromagnetic sensors will be drilled in the near future between the injector and producer to monitor cold-front propagation. This paper presents the initial modeling for the project and steps towards the production of a digital twin. Two modeling examples in the paper will emp hasize current operational challenges relevant to the project.@en

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.@en

Subsurface porous rocks hold significant hydrogen (H₂) storage potential to support an H₂-based energy future. Understanding H₂ flow and trapping in subsurface rocks is crucial to reliably evaluate their storage efficiency. In this work, we perform cyclic H₂ flow visualization experiments on a layered rock sample with varying pore and throat sizes. During drainage, H₂ follows a path consisting of large pores and throats, through a low permeability rock layer, substantially reducing H₂ storage capacity. Moreover, due to the rock heterogeneity and depending on the experimental flow strategy, imbibition unexpectedly results in higher H₂ saturation compared to drainage. These results emphasize that small-scale rock heterogeneity, which is often unaccounted for in reservoir-scale models, plays a vital role in H₂ displacement and trapping in subsurface porous media, with implications for efficient storage strategies.

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Microporosity is commonly assumed to be non-connected porosity and not commonly studied in geoengineering industry. However, the presence of micropores plays a key role in connecting macropores and it can contribute significantly to the overall flow performance. In this study, targeted CO₂ storage carbonate fields in Southeast Asia have significant amounts of microporosity ranging from 10 to 60% of the total measured porosity. Microporosity can only be seen in high resolution images. To study the unresolved and the resolved microporosity, Middle Miocene carbonate samples from CO₂ storage candidate fields were scanned using lower resolution micro-computed micro-tomography (micro-CT) and higher resolution synchrotron light source to understand the pore scale structure of the carbonate sample at different length scales. This paper proposes a proof-of-concept upscaling method that integrates multiscale 3D imaging techniques and trendline analysis to establish porosity-permeability relationships with microporosity insight. After image acquisition and processing, the images were divided into smaller sub-volumes. Pore-scale modelling was conducted to predict the permeability using Darcy-Brinkman-Stokes (DBS) model. Then, a nano-scale porosity-permeability transform is generated using natural log trendline fitting based on simulation results. The porosity-permeability transform is further extended to three cases to cover the low case, mid case, and high case of datapoint fittings and is further validated with laboratory measured data. The established porosity-permeability transforms in this study have been applied to compare with petrophysical derived porosity-permeability transforms with better performance (higher R² value) for low permeability datapoint. The multiscale imaging upscaling workflow has integrated machine learning during image segmentation with pore-scale modelling and trendline fitting during the upscaling study. It emphasises the importance of seeing the unseen (unresolved microporous phase) to understand the internal texture and microstructure of a rock sample in order to understand the connectivity of the overall flow performance in a carbonate rock.

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Sketch-based interface and modelling is an approach to reservoir modelling that allows rapid and intuitive creation of 3D reservoir models to test and evaluate geological concepts and hypotheses and thus explore the impact of geological uncertainty on reservoir behaviour. A key advantage of such modelling is the quick creation and quantitative evaluation of reservoir model prototypes. Flow diagnostics capture key aspects of reservoir flow behaviour under simplified physical conditions that enable the rapid solution of the governing equations, and are essential for such quantitative evaluation. In this paper, we demonstrate a novel and highly efficient implementation of a flow diagnostics framework, illustrated with applications to geological storage of CO2. Our implementation permits ‘on-the-fly’ estimation of the key reservoir properties that control CO2 migration and storage during the active injection period when viscous forces dominate. The results substantially improve the efficiency of traditional reservoir modelling and simulation workflows by highlighting key reservoir uncertainties that need to be evaluated in subsequent full-physics reservoir simulations that account for the complex interplay of viscous, gravity, and capillary forces.

The methods are implemented in the open-source Rapid Reservoir Modelling software, which includes a simple to use graphical user interface with no steep learning curve. We present proof-of-concept studies of the new flow diagnostics implementation to investigate the CO2 storage potential of sketched 3D models of shallow marine sandstone tongues and deep water slope channels.@en

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.

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Energy derived from geothermal systems is essential to the energy transition. Inherent geological and a lack of data requires the use of computer-driven modelling and simulation to aid decision-making. To make sound decisions, many reservoir models that encapsulate different geological scenarios should be analysed such that the impact of geological uncertainty on geothermal energy production can be evaluated adequately. Current geomodelling workflows, however, are too time consuming to build and explore different contrasting geological scenarios at various scales. In this study we used the open-source Rapid Reservoir Modelling (RRM) software to design different geological scenarios of a shallow marine succession hosting a potential geothermal reservoir and analyse how multi-scale geological features impact reservoir flow. RRM allows users to quickly create and explore realistic 3D geological models from intuitive 2D sketches. Models arecreated in minutes while flow diagnostics allow us to analyse fluid-flow behavior in real-time. Models are then imported into commercial reservoir simulation packages to investigate the effect of heterogeneity and scale on geothermal energy production. We show how we can quickly evaluate how different scales of heterogeneity impact geothermal production estimates and which heterogeneities must be represented in reservoir models to obtain reliable results about the possible reservoir behaviours.@en

Sketch-based modelling with flow diagnostics provides a prototyping approach to quickly build geomodels and generate quantitative results to evaluate volumetrics and flow behaviour. This approach allows users to rapidly test the sensitivity of model outputs to different geological concepts and uncertain parameters, and informs selection of geological concepts, scales and resolutions to be investigated in more detailed models. Rapid Reservoir Modelling (RRM) is a sketch-based modelling tool with an intuitive interface that allows users to rapidly sketch geological models in 3D. Geological models that capture the essence of heterogeneity of interest and related uncertainty can be created within minutes. Flow diagnostics then instantly computes key indicators of predicted flow and storage behaviour within seconds. Here we apply the prototyping approach to three aspects of geoenergy modelling: (1) scenario screening to identify heterogeneities with the most impact; (2) use of mini-models and hierarchical models to derive effective properties; and (3) training of geoscientists and engineers to investigate the impact of geological interpretations on storage volumes and connectivity. Geomodels addressing all three aspects are constructed and analysed quickly, using simple, geologically intuitive workflows that do not require prior geomodelling expertise.@en

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.

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Understanding the impact of fractures on fluid flow is fundamental for developing geoenergy reservoirs. Pressure transient analysis could play a key role for fracture characterization purposes if better links can be established between the pressure derivative responses (p′) and the fracture properties. However, pressure transient analysis is particularly challenging in the presence of fractures because they can manifest themselves in many different p′ curves. In this work, we aim to provide a proof-of-concept machine learning approach that allows us to effectively handle the diversity in fracture-related p′ curves by automatically classifying them and identifying the characteristic fracture patterns. We created a synthetic dataset from numerical simulation that comprised 2560 p′ curves that represent a wide range of fracture network properties. We developed an unsupervised machine learning approach that can distinguish the temporal variations in the p′ curves by combining dynamic time warping with k-medoids clustering. Our results suggest that the approach is effective at recognizing similar shapes in the p′ curves if the second pressure derivatives are used as the classification variable. Our analysis indicated that 12 clusters were appropriate to describe the full collection of p′ curves in this particular dataset. The classification exercise also allowed us to identify the key geological features that influence the p′ curves in this particular dataset, namely (1) the distance from the wellbore to the closest fracture(s), (2) the local/global fracture connectivity, and (3) the local/global fracture intensity. With additional training data to account for a broader range of fracture network properties, the proposed classification method could be expanded to other naturally fractured reservoirs and eventually serve as an interpretation framework for understanding how complex fracture network properties impact pressure transient behaviour.@en

The traditional model of solid dissolution in porous media consists of three dissolution regimes (uniform, compact, wormhole)-or patterns-that are established depending on the relative dominance of reaction rate, flow, and diffusion. In this work, we investigate the evolution of pore structure using numerical simulations during acid injection on two models of increasing complexity. We investigate the boundaries between dissolution regimes and characterize the existence of a fourth dissolution regime called channeling, where initially fast flow pathways are preferentially widened by dissolution. Channeling occurs in cases where the distribution in pore throat size results in orders of magnitude differences in flow rate for different flow pathways. This focusing of dissolution along only dominant flow paths induces an immediate, large change in permeability with a comparatively small change in porosity, resulting in a porosity-permeability relationship unlike any that has been previously seen. This work suggests that the traditional conceptual model of dissolution regimes must be updated to incorporate the channeling regime for reliable forecasting of dissolution in applications like geothermal energy production and geologic carbon storage.

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This poster outlines a hierarchical, multiscale modelling approach that is adapted from proven hydrocarbon reservoir characterization workflows to determine which 3D sedimentological and stratigraphic heterogeneity types at which temporal and spatial scales and in which configurations are most important for successful long-term CO2 storage. The approach is particularly in saline aquifers that are data-poor but have the potential to store large CO2 volumes. It uses the Representative Element Volume (REV) concept and associated upscaling methodology to characterise sedimentological heterogeneity types, and it leverages novel modelling tools that facilitate rapid model construction and prototyping, geometrically accurate representation of key geological heterogeneities in models, and computationally efficient simulation of all CO2 trapping mechanisms over relevant spatial and temporal scales.@en

Production of subsurface heat from geothermal sources and subsurface storage of heat (and cool) are important for energy transition. Doublets for geothermal and warm- and cold wells for aquifer thermal energy storage (ATES) depend on circulation of fluids and heat. Estimating the potential and feasibility of such systems requires a careful analysis with simulation of fluid flow and heat transport. As building models and running simulations are time-consuming, a prototyping approach is beneficial to quickly assess viability and sensitivity of such systems. Sketch-based geological modelling combined with flow diagnostics forms the ideal for such a prototyping approach. Geological models can be sketched in 3D in a couple of minutes. Flow diagnostics then provides several key metrics on predicted flow behaviour. The quick turnaround time from sketching to quantitative results is key to understand the impact of heterogeneity on flow and helps to decide which detailed geological models and flow simulations are useful to carry out. This prototyping approach is applied to aquifers in shallow marine deposits, as proxy for thermal breakthrough time in geothermal doublet system and to estimate well spacing between cold and hot wells for ATES.@en

We discuss the application of the new open-source Rapid Reservoir Modelling software (RRM) to create a suite of 3D reservoir models of a complex carbonate formation where each model is increasingly more refined such that progressively more small-scale geological structures are preserved. Using flow diagnostics we then calculate key metrics for the dynamic reservoir behaviour to quantify the similarities and dissimilarities of the flow behaviour across the different models. This analysis allows us to identify at which scale geological heterogeneities need to be resolved in the reservoir model to capture the essential flow behaviours. The workflow presented in this study hence allows us to efficiently and effectively test different geological concepts and analyse how multi-scale geological heterogeneities that may need to be represented in a reservoir model impact the predicted dynamic response, so as to design more reliable and robust reservoir models for a broad range of geoenergy applications.@en

We use a method combining experimental design, sketch-based reservoir modelling, and flow diagnostics to rapidly screen the impact of sedimentological heterogeneities on CO2 migration and storage by stratigraphic trapping. Experimental design allows efficient exploration of a wide parameter space, sketch-based modelling enables rapid construction of deterministic models of interpreted geological scenarios, and flow diagnostics provide computationally cheap approximations of full-physics, multiphase simulations that are reasonable for many subsurface-flow conditions. Integrated sketch-based reservoir modelling and flow diagnostics are implemented in open source research code (Rapid Reservoir Modelling, RRM). The method is applied to two case studies: (1) the Triassic Sherwood Sandstone Group and Bunter Sandstone Formation, UK, which comprise fluvial-aeolian sandstones, floodplain and sabkha heteroliths, and lacustrine mudstones; and (2) the Jurassic Johansen and Cook formations, offshore western Norway, which record progradation of a wave-dominated delta system. Results for the two case studies are compared using effective permeability (kx, ky, kz) and pore volume injected at breakthrough time (a measure of how much injected fluid is stored in the model volume as a result of stratigraphic trapping).@en

We use a method combining experimental design, sketch-based reservoir modelling, and single-phase flow diagnostics to rapidly screen the impact of sedimentological heterogeneities that constitute baffles and barriers to CO2 migration in the Johansen and Cook formations at the Northern Lights CO2 storage site. The types and spatial organisation of sedimentological heterogeneities in the wave-dominated deltaic sandstones of the Johansen-Cook storage unit are constrained using core data from the 31/5-7 (Eos) well, previous interpretations of seismic data and regional well-log correlations, and outcrop and subsurface analogues. Delta planform geometry, clinoform dip, and facies-association interfingering extent along clinoforms control: (1) the distribution and connectivity of high-permeability medial and proximal delta-front sandstones, (2) effective horizontal and vertical permeability characteristics of the storage unit, and (3) pore volumes injected at breakthrough time (which approximates the efficiency of stratigraphic baffling). In addition, the lateral continuity of carbonate-cemented concretionary layers along transgressive surfaces impacts effective vertical permeability, and bioturbation intensity impacts effective horizontal and vertical permeability. The combined effects of these and other heterogeneities are also influential. Our results suggest that the baffling effect on CO2 migration and retention of sedimentological heterogeneity is an important precursor for later capillary, dissolution and mineral trapping.@en

Hypothesis

Underground hydrogen (H2) storage is a potentially viable solution for large-scale cyclic H2 storage; however, the behavior of H2 at subsurface pressure and temperature conditions is poorly known. This work investigates if the pore-scale displacement processes in H2-brine systems in a porous sandstone can be sufficiently well defined to enable effective and economic storage operations. In particular, this study investigates trapping, dissolution, and wettability of H2-brine systems at the pore-scale, at conditions that are realistic for subsurface H2 storage.

Experiments

We have performed in situ X-ray imaging during a flow experiment to investigate pore-scale processes during H2 injection and displacement in a brine saturated Bentheimer sandstone sample at temperature and pressure conditions representative of underground reservoirs. Two injection schemes were followed for imbibition: displacement of H2 with H2-equilibrated brine and with non-H2-equilibrated brine. The results from the two cycles were compared with each other.

Findings

The sandstone was found to be wetting to the brine and non-wetting to H2 after both displacement cycles, with average contact angles of 54° and 53°, for H2-equilibrated and non-H2-equilibrated brine, respectively. We also found a higher recovery of H2 (43.1%) when displaced with non-H2-equilibrated brine compared to that of H2-equilibrated brine (31.6%), indicating potential dissolution of H2 in the unequilibrated, imbibing brine at reservoir conditions. Our results suggest that underground H2 storage may indeed be a suitable strategy for energy storage, but considerable further research is needed to fully comprehend the pore-scale interactions at reservoir conditions.@en

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.@en