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At least 163 records · Page 9

Powersheds

Powersheds is an open scientific software project for simulating river–reservoir cascades. It combines the performance of Rust with a friendly Python interface to model storage, pool elevation, head, releases, spills, routing lags, and power generation at hourly resolution. Designed for coupling with power-system models, simulations are driven by plant-level target power schedules and report realized generation after accounting for hydrologic and operational constraints.

Turner, Sean [Oak Ridge National Laboratory (ORNL)↗

NRAP-Open-IAM Analytical Reservoir Model: Development and Testing

Geological carbon sequestration (GCS) is a key technology for reducing global carbon dioxide (CO 2 ) emissions. Over the last decade, the U.S. Department of Energy has invested in understanding the science base, developing practical implementation methods, and demonstrating secure GCS technologies to mitigate the environmental impacts associated with the atmospheric release of CO 2 . As part of the National Risk Assessment Partnership, a systems-level risk assessment tool, called the NRAP-Open-IAM, has been developed to conduct risk assessment and enable safe operations at a GCS site. The current NRAP-Open-IAM contains a simple reservoir model component that calculates the evolution of CO 2 saturation and fluid pressure in a storage reservoir during CO 2 injection operations. This report presents the development and testing of a new analytical reservoir reduced-order model (ROM), which is extended from an existing semi-analytical model for estimation of CO 2 and brine leakage along legacy wells, and enhances the capability of the NRAP-Open-IAM to simulate more types of reservoir conditions. The developed model is validated against three reference studies, and the results indicate that the new ROM predicts the behavior of the two-phase fluids (brine and injected CO 2 ) well and is applicable to different reservoir simulation boundary conditions (i.e., constant pressure boundary and infinite-acting boundary) without a priori user specification of the boundary type. Sensitivity analysis for a set of model parameters is performed using 4,000 synthetic cases prepared via a fully automated process and using machine-learning-based feature selection. The stochastic analysis identifies gravitational number (i.e., ratio of gravitational forces to viscous force) and distance between the injection well and observation location as the most impactful parameters for matching the pressure and CO 2 saturation, respectively, between the numerical simulations and the ROM. This report details the possible ROM uncertainties and serves as a guide for users to understand the use and limitations of this ROM. The code implementation of the model will be released as a module within the NRAP-Open-IAM.

54 ENVIRONMENTAL SCIENCES↗

Hydraulic and Thermal Stimulation Program at Raft River Idaho, A DOE EGS

A Department of Energy Enhanced Geothermal System (EGS) stimulation program has injected over 254 million gallons of water into the well RRG-9 ST1 since the summer of 2013. Three major stimulations have been conducted during the program increasing injection flow rates from less than 20 gpm to 550 gpm. Geologic, water chemistry, microseismic activity, and borehole imaging data have been used to develop a conceptual model describing possible flow paths of this injected water. This model contains two major fracture zones one of which intersects the RRG-9 ST1 wellbore. Modified Hall and injectivity index plots constructed using injection flow rates, surface temperatures, and wellhead pressures show steady improvement in the injectivity of the well. Here, the injectivity index has risen from 0.15 gpm/psi to 2.0 gpm/ psi. A pressure falloff test conducted on April 28, 2015 indicates a reservoir permeability of 1,220 md and -5.38 skin factor. The well stimulation program was simulated numerically using an Idaho National Laboratory reservoir simulation code, FALCON. These simulations show a significant increase in the permeability of connecting fracture pathways after each stimulation event.

Enhanced geothermal system↗

Skin factor and potential formation damage from chemical and mechanical processes in a naturally fractured carbonate aquifer with implications to CO 2 sequestration

Here, in this study, we investigate formation damage due to acidization and water injection tests into the naturally fractured carbonate Middle Duperow Formation at Kevin Dome, Montana, potentially diminishing the chance of a future successful Geological Carbon Sequestration (GCS) project. Multiple well-test analytical models, correlated with core description and lithology data, are used to determine flow behavior and communication between the water injection interval and surrounding formations. An improved three-dimensional (3D) geologic model with dual-continuum matrix and fracture properties is constructed based on most recent seismic, core, and water sample measurements. Brine injection is simulated to verify the interpretation from the analytical models, followed by CO 2 injection simulation. Geochemical calculations are performed to understand the in-situ processes that led to formation damage. Our findings suggest: (1) there are two possible scenarios that could lead to a positive total effective skin factor and permeability decline: partial penetration and formation damage; (2) analytical models indicate a positive total skin factor, contradicting results of a previous study suggesting that the well was mildly stimulated; (3) numerical simulation supports the formation damage hypothesis by matching the pressure buildup observed during the latter two brine injection tests; (4) several mechanical and chemical processes may have occurred during injection to clog the matrix/fracture system: anhydrite fines migration and/or calcite precipitation. We then make preventative suggestions for future GCS projects into carbonate reservoirs and remediation recommendations for GCS operation at the Kevin Dome.

54 ENVIRONMENTAL SCIENCES↗

Wabash CarbonSAFE Static and Dynamic Modeling: Task 9.0 (Technical Report)

The objective of the Wabash CarbonSAFE project’s static and dynamic modeling task is to assess the feasibility of storing 50 million tonnes (1.67 million metric tonnes annually; MMTA) of industrially-sourced carbon dioxide (CO 2 ) in a commercial-scale geological storage complex at Wabash Valley Resources LLC (WVR) gasification facility near Terre Haute, Indiana over a period of 30 years. The targeted formations for storing CO 2 are: 1) Mt. Simon Sandstone (MSS) and the 2) Potosi Dolomite (Knox Group). All of the available data from the recently drilled Wabash #1 stratigraphic test well (now plugged and abandoned) were used in the construction of both the static and dynamic models. Geologic models were constructed to characterize both the Mt. Simon Sandstone and Potosi Dolomite storage complexes. Dynamic simulation models were constructed and used to assess the feasibility of injecting CO 2 into the Mt. Simon and Potosi formations. The geocellular models for the Potosi Dolomite and Mt. Simon Sandstone were built using Petrel™, Schlumberger’s reservoir modeling software. The dynamic simulations were run using Landmark’s Nexus ® reservoir simulation software.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Numerical Modeling of CO2 Sequestration within a Five-Spot Well Pattern in the Morrow B Sandstone of the Farnsworth Hydrocarbon Field: Comparison of the TOUGHREACT, STOMP-EOR, and GEM Simulators

The objectives of this study were (1) to assess the fate and impact of CO2 injected into the Morrow B Sandstone in the Farnsworth Unit (FWU) through numerical non-isothermal reactive transport modeling, and (2) to compare the performance of three major reactive solute transport simulators, TOUGHREACT, STOMP-EOR, and GEM, under the same input conditions. The models were based on a quarter of a five-spot well pattern where CO2 was injected on a water-alternating-gas schedule for the first 25 years of the 1000 year simulation. The reservoir pore fluid consisted of water with or without petroleum. The results of the models have numerous broad similarities, such as the pattern of reservoir cooling caused by the injected fluids, a large initial pH drop followed by gradual pH neutralization, the long-term persistence of an immiscible CO2 gas phase, the continuous dissolution of calcite, very small decreases in porosity, and the increasing importance over time of carbonate mineral CO2 sequestration. The models differed in their predicted fluid pressure evolutions; amounts of mineral precipitation and dissolution; and distribution of CO2 among immiscible gas, petroleum, formation water, and carbonate minerals. The results of the study show the usefulness of numerical simulations in identifying broad patterns of behavior associated with CO2 injection, but also point to significant uncertainties in the numerical values of many model output parameters.

STOMP↗

Failure Analysis–Informed Risk Assessment Framework for Geological Carbon Storage Using Numerical Simulation and Machine Learning

Geological carbon storage (GCS) is recognized as a critical technology for achieving large-scale reductions in anthropogenic carbon dioxide (CO 2 ) emissions. Ensuring long-term containment and safety requires robust risk assessment frameworks that account for geological uncertainty and identify potential failure scenarios. Among various indicators, the area of review (AoR) serves as a key metric for evaluating storage performance, regulatory compliance, and monitoring design, as it delineates the spatial extent impacted by pressure buildup and plume migration. However, conventional AoR-based risk assessments typically perturb parameters within narrow uncertainty bounds, potentially overlooking rare but high-impact events arising from extreme geological conditions. In this study, we present a failure analysis–informed risk assessment framework for large-scale GCS projects to improve site prescreening and monitoring design. A suite of 300 numerical simulations was generated using stochastic geological models that vary five key parameters: net-to-gross ratio, anisotropy azimuth, porosity multiplier, permeability multiplier, and vertical-to-horizontal permeability ratio. Among these, 200 realizations represent normal geological uncertainty, while 100 additional cases explore extreme yet plausible conditions for failure-case analysis. The AoR was simulated and computed from pressure and CO 2 saturation fields, where the baseline AoR boundary, representing the extent predicted under typical geological uncertainty, was defined as the union of 200 normal-range simulations, and failure was identified when extreme-range cases exceeded this baseline. Results show that incorporating broader parameter uncertainty produces significantly larger AoR extents, underscoring the potential underestimation of risk under conventional uncertainty ranges. Furthermore, spatial probability maps derived from failure-induced AoR exceedance identify regions requiring enhanced monitoring attention. Various machine learning (ML)–based classifiers were developed to predict failure occurrence from geological parameters, with the random forest model achieving the highest performance (F1-score of 0.986). Consistent findings from correlation coefficient, feature importance, and Sobol sensitivity analyses reveal that low net-to-gross ratios and permeability multipliers are the dominant risk drivers, reflecting reduced reservoir connectivity and limited pressure dissipation. Altogether, these results provide a novel framework for risk-informed site prescreening and monitoring design that explicitly considers rare but high-impact geological scenarios in GCS projects.

25 ENERGY STORAGE↗

Deformation of pores in response to uniaxial and hydrostatic stress cycling in Marcellus Shale: Implications for gas recovery

One of the main challenges during gas production from shale reservoirs is low recovery rate. One contributing factor to this outcome is an insufficient understanding of pore systems, especially pore behaviour following changes in reservoir conditions or resulting from gas production practices. Because the pressure in the producing well can be controlled, understanding the effects of pressure variation on the pore size distribution and methane trapping is necessary to help design optimal conditions to improve the gas recovery rate. This work is the first systematic study of sub-millimeter pore deformation in shale caused by uniaxial and hydrostatic stress up to 100 MPa. Overmature samples from the Middle Devonian Marcellus Shale were analyzed using neutron scattering (SANS and USANS) techniques to interpret the response of nanopores to stress cycling of magnitude and duration compatible with the hydraulic fracturing treatments. Experiments reported here are performed at a series of uniaxial pressures up to 100 MPa and at hydrostatic pressures of deuterated methane 0 and 50 MPa. Since at the original depth of the shale samples’ burial of 2184 m the hydrostatic pressure is approximately 27 MPa and the lithostatic pressure is about 55 MPa, the experimental conditions reasonably well simulate the reservoir pressure regime. Our SANS and USANS results show that different pore sizes are affected by uniaxial stress in different ways. Specifically, in the pore size range from 1 nm to 800 nm, a decrease of pore density with pressure is observed, with the most depleted being mesopores of about 100 nm in diameter. The observed decrease is likely related to deformation of kerogen, followed by a loss of pore nano-volume, as well as methane trapped in the micropores. For pores larger than 5 μm, USANS data suggest that the negative trend is reversed at above 74 MPa, and the number density of large macropores may increase with increased stress even above the original value. The increased number of macropores at high pressure may create new interconnected conduits for gas migration, resulting in a better recovery rate. Another important finding of this study is an irreversible rearrangement of pore size distribution taking place after pressure cycling. Furthermore, this irreversible reorganization of pore size distribution should be taken into account during management of well production to maximize recovery rate.

03 NATURAL GAS↗

Pore-scale visualization of natural hydrate-bearing sediments

Accurate modeling of gas hydrate reservoir productivity and geomechanical risks associated with subsurface dissociation of natural gas hydrates (NGH) requires the determination of model parameters through physical testing on natural hydrate-bearing sediments (HBS). This involves investigating the hydro-mechanical behavior of undisturbed hydrate samples from nature under in situ conditions using pressure core characterization and analysis, which provides a unique opportunity for research. By employing state-of-the-art micro computed tomography imagery on cryogenically preserved, hydrate-bearing sediment samples, we can determine hydrate saturation as well as permeability with and without the presence of hydrates in the sediment. Furthermore, utilizing a machine learning based image segmentation technique, it is possible to extract pore space and grain information. Subsections of the entire image volume were used to determine anisotropic permeabilities using a finite-difference method Stokes solver (FDMSS). Additionally, permeability measurements on whole pressure and temperature preserved hydrate-bearing core were analyzed by utilizing the National Energy Technology Laboratory’s (NETL) Pressure Core Characterization and X-ray CT Visualization Tool (PCXT) to manipulate, cut, and analyze pressure preserved sediment. Permeabilities were measured under a broad range of vertical stress states to simulate expected pressure changes during production scenarios, and the results show that permeabilities derived from images are in agreement with those from traditional core derived experiments. The collected stress-dependent permeability, permeability anisotropy, and corresponding gas hydrate saturations provide valuable input into numerical simulations of reservoir productivity. These properties have been proven to be key parameters determining a long-term reservoir response under depressurization.

Liu, Mengwei [Oak Ridge Institute for Science and ↗

Informing field-scale CO 2 storage simulations with sandbox experiments: The effect of small-scale heterogeneities

Small-scale heterogeneities can significantly affect the fate of the CO 2 plume and trapping during CO 2 migration. We conducted geologic carbon storage field-scale simulations to investigate the impact of small-scale heterogeneities on plume dynamics and trapping performance. Small-scale heterogeneities have been shown to increase the amount of trapped CO 2 during buoyancy-driven flow. The trapped CO 2 saturation is validated by previous sandbox experimental work during buoyancy-driven flow in realistic heterogeneous domains and is implemented through the critical CO 2 saturation parameter (i.e., the first non-zero value in the drainage CO 2 relative permeability curve). Depending on the type and degree of heterogeneity, various critical CO 2 saturation values are exhibited. Furthermore, we investigated the effect of small-scale heterogeneities when multiple capillary pressure models are employed. This study demonstrates that an increase in critical CO 2 saturation reduces the CO 2 plume size and lateral extent, accompanying an increase in residual trapping and a decrease in solubility trapping. Lastly, we show that independent of the capillary pressure model used, an increase in critical saturation leads to similar CO 2 plume dynamics distribution and trapping performance. These results emphasize the importance of quantifying the effect of small-scale heterogeneity as they affect the large-scale behavior of the CO 2 plume.

58 GEOSCIENCES↗

The EGS Collab Project – Stimulations at Two Depths

The EGS Collab project, supported by the US Department of Energy, is performing intensively monitored rock stimulation and flow tests at the 10-m scale in an underground research laboratory to address challenges in implementing enhanced geothermal systems (EGS). Data and observations from the field tests are compared to simulations to understand processes and build confidence in numerical modeling of the processes. We have completed Experiment 1 (of 3), which examined hydraulic fracturing in a well-characterized underground fractured phyllite test bed at a depth of approximately 1.5 km at the Sanford Underground Research Facility (SURF) in Lead, South Dakota. Testbed characterization included fracture mapping, borehole acoustic and optical televiewers, full waveform sonic, conductivity, resistivity, temperature, campaign p- and s-wave investigations and electrical resistance tomography. Borehole geophysical techniques including passive seismic, continuous active source seismic monitoring, electrical resistance tomography, fiber-based distributed strain, distributed temperature, and distributed acoustic monitoring, were used to carefully monitor stimulation events and flow tests. More than a dozen stimulations and nearly one year of flow tests were performed. Quality data and detailed observations were collected and analyzed during stimulation and water flow tests using ambient temperature and chilled water. We achieved adaptive control of the tests using real-time monitoring and rapid dissemination of data and near-real-time simulation. More detailed numerical simulation was performed to answer key experimental design questions, forecast fracture propagation trajectories and extents, and analyze and evaluate results. Data are freely available from the Geothermal Data Repository. Experiment 2 examines the potential for hydraulic shearing in amphibolite at a depth of about 1.25 km at SURF. This site has a different set of stress and fracture conditions than Experiment 1. The Experiment 2 testbed consists of nine subhorizontal boreholes configured in two fans of two boreholes which surround the testbed and contain grouted-in electrical resistance tomography, seismic sensors, active seismic sources and distributed fiber sensors. A “five-spot” set of test wells that extends from a custom mined alcove includes an injection well and four production/monitoring wells. The testbed was characterized geophysically and hydrologically, and three stimulations have been performed using the Step-Rate Injection Method for Fracture In-Situ Properties (SIMFIP) tool to measure strains, and a new strain quantifying tool (downhole robotic strain analysis tool -DORSA) was deployed in a monitoring hole during stimulation. Real-time data were broadcast during stimulations to allow real-time response to arising issues.

EGS Collab, Enhanced Geothermal Systems, EGS, fiel↗

Optimizing district energy systems by integrating Borehole Thermal Energy Storage Using a Mixed-Integer Linear Programming g-function framework with a Multi-Timescale Rolling Horizon method

Shallow geothermal has gained increasing attention in recent years; however, a reliable framework for its accurate incorporation into large-scale energy system optimization remains lacking. This study proposes a Mixed-Integer Linear Programming (MILP) framework combined with the g-function approach to integrate Borehole Thermal Energy Storage (BTES) technology into energy system optimization. Validation against a Modelica-based reservoir network simulation demonstrates that the proposed framework effectively captures the ground thermal response under varying energy loads and accurately estimates the borefield energy supply. To enhance scalability, a Rolling Horizon with Multi-Timescale (RH-MTS) method is further introduced, reducing computational time by 73 % for the 1-year optimization model with only minor loss of optimality. The framework is demonstrated through the case study of the UC Berkeley campus. Results indicate that BTES is a cost-effective and low-carbon solution: two borefields comprising 382 boreholes can meet 8.0 % and 6.6 % of the total campus heating and cooling demand, respectively, at an average energy rate of 0.70–0.77 USD/kWh and carbon intensity of 0.54 kg-CO2/kWh. Short-term analysis reveals a 35%–65% decline in BTES energy flow after 3–6 months of continuous heating/cooling operation, while long-term simulation shows that annual energy production of BTES can vary by up to 12.0 % after four years before stabilizing. Overall, this study develops a novel optimization framework that couples physics-based g-function method with MILP optimization framework, thereby advancing methodological development for shallow-geothermal integration and providing actionable guidance for BTES deployment in district-energy systems.

Yang, Jiahui↗

Effect of initial water saturation on the performance of fracturing fluids with and without polyallylamine under simulated EGS conditions

Objectives/Scope: StimuFrac (US Patents 9,873,828 B2 and 9,447,315 B2), a CO 2 - reactive polymer aqueous solution [polyallylamine (PAA) 1wt% in water] combined with CO 2 , can be used as a potentially less water-intensive fracturing fluid for enhanced geothermal systems (EGS). Our previous results show that in hot dry rock (HDR), PAA/CO 2 fracturing fluids outperformed other fluids such as water, CO 2 , and CO 2 /water in generating large fractures with less fluid consumed. The objective of this work is to investigate the effect of initial water saturation on the performance of StimuFrac by conducting hydraulic fracturing tests with ½ foot cubic rock samples held under representative EGS stress/temperature conditions and by using cyclic injection strategies (under constant injection rate). The resulting fracture hydraulic conductivities, breakdown pressures, and volumes of fluids required are compared. Methods/Procedures/Process: To simulate geothermal reservoir conditions, in all tests, the rock sample was held under triaxial confinement and at 200 °C, and different volumes of water were initially injected into the rock sample before any fracturing processes were initiated. For the single-cycle PAA (or water) alternating CO 2 (PAG or WAG) injection fracturing experiments, one complete cycle consisted of two steps: (1) injecting a PAA slug (or water slug) followed by (2) injecting CO 2 to initiate and propagate the fracture. For experiments involving multiple injection cycles, the CO 2 injection pressure is increased until it peaks and begins to decline (indicating fracture initiation at this moment), and then continued being injected for another 30 seconds to propagate the fracture. Then, these two-step cycles [injection of PAA (or water) followed by CO 2 injection (up to 2-4 mL/min)] are repeated. Applications/Significance/Novelty: The results of this study suggest that water saturation significantly affects the fracturing fluid transmission into the rock pore space, thus affecting the fracture initiation and propagation. In this study, fracturing tests via a single injection cycle or multiple injection cycles were performed. Splitting the rock samples in half after testing reveals that fracture propagation is significantly limited under high water saturation conditions (three-day initial water injection) compared to stimulation experiments performed in hot dry rock. The fractures propagate less than 1/3 of the distance from the wellbore to the outer rock surface, and in some cases, no fracture is generated. This may be caused by leak-off dominating the fracturing process and the fluid injection rate is insufficient to overcome leak-off, even under high injection rate conditions. Additionally, CO 2 could be leaking off into the wellbore annulus and this may be making it more difficult to generate sufficiently high-pressure gradients away from the near-wellbore region. Under low water saturation conditions (dry rock or after 1-day initial water injection), PAA/CO 2 consistently generated significantly larger fractures compared with the other fluids. CO 2 generated large fractures only in the hot dry rock and only when using high injection rates, though data variability is high.

58 GEOSCIENCES↗

Joint impedance and facies inversion of time-lapse seismic data for improving monitoring of CO 2 incidentally stored from CO 2 EOR

Time-lapse seismic monitoring is an effective and proven technology for mapping the distribution of CO 2 in a subsurface reservoir. When injected CO 2 displaces other reservoir fluids, porous-medium properties are changed and thus the seismic impedance changes, causing time-lapse seismic amplitude differences in the injection zones. The analysis and interpretation of images created from these amplitude differences can provide information about reservoir architecture and the CO 2 migration within the reservoir. Incorporating seismic inversion and rock physics into the interpretation of time-lapse seismic data can considerably improve the modeling and monitoring to detect and assess the location of CO 2 over time. The joint inversion method presented in this paper has an integral representation of the geology in the inversion algorithm using elastic facies, which provides information about the spatial distribution of the geologic heterogeneities controlling the movement of fluids in the reservoir. The method was successfully applied to time-lapse seismic data from a mature oil field undergoing CO 2 enhanced oil recovery. The estimated seismic acoustic impedances and facies reflect the characteristics of individual geologic facies and fluid conditions of the reservoir subject to CO 2 injection. Finally, the probabilities estimated by the joint impedance and facies inversion for the reservoir's litho-fluid facies can be used for forecasting CO 2 saturation and pressure changes within the target reservoir.

4D seismic↗

Time-lapse seismic inversion for CO 2 saturation with SeisCO2Net: An application to Frio-II site

Seismic monitoring of geological CO 2 storage (GCS) involves highly nonlinear seismic inversion and petrophysical inversion, making it challenging to estimate CO 2 volume efficiently and detect possible early CO 2 leakages. Deep learning (DL) using convolutional neural networks (CNNs) has shown promise in solving highly nonlinear seismic inversion problems. However, direct estimation of CO 2 plume extent/saturation from time-lapse seismic gathers using DL is still underexplored, with no reported field applications to date. The investigation of field data is primarily hindered by scarcity of field data for neural network training. Other obstacles include highly nonlinear seismic-petrophysics inverse relationship, and presence of noise in field seismic data. We introduce SeisCO2Net, a deep CNN that predicts CO 2 saturation maps directly from time-lapse full waveform shot gathers. For training, we use site-specific geological information, fluid flow physics, rock physics, and seismic modeling to generate synthetic datasets that closely resemble the CO 2 storage site. Synthetic tests show promising results, inspiring us to apply SeisCO2Net's trained weights on field data collected at Frio-II GCS site by leveraging transfer learning principles. As reference, we compare SeisCO2Net's predicted CO 2 saturation maps with results obtained from physics-based inversion. Our analyses show both methods display similar CO 2 plume shapes, reasonable CO 2 plume characteristics, and comparable saturation values. Our results suggest pre-training CNNs on physics-informed synthetic datasets and then applying the learned weights to field data is a viable approach to estimating field CO 2 saturation. This method effectively addresses the scarcity of field training data, thus encouraging the feasibility of long-term GCS monitoring.

58 GEOSCIENCES↗

Impact of Rock Wettability and Mineralization on CO 2 Storage Efficiency in Basalt Reservoirs

Basalt formations have emerged as highly promising targets for geological CO 2 storage due to their abundance of reactive silicate minerals that can rapidly convert dissolved CO 2 into stable carbonate minerals. The efficiency of CO 2 trapping in basalts, however, depends not only on their geochemical reactivity but also on reservoir wettability, which governs how CO 2 partitions among structural, residual, solubility, and mineral trapping mechanisms. However, wettability and mineral kinetics have largely been examined separately, wettability for plume migration and kinetics in terms of mineralization, leaving their coupled impact unquantified. Here, we systematically integrate th ese processes in a reservoir-scale reactive transport model to quantify the impact of three distinct wettability conditions (water-wet, mixed-wet, and CO 2 -wet) on plume migration, mineral precipitation, pore-scale blockage, and long-term immobilization. Results show that under ideal conditions (no mineralization), water-wet systems exhibited plume aspect ratios up to 28% higher than CO 2 -wet systems and promoted at least 60% greater residual trapping. When mineralization was incorporated, mineral trapping accounted for 57%, 53%, and 46% of the total immobilized CO 2 in water-wet, mixed-wet, and CO 2 -wet systems, respectively. Dissolved CO 2 contributed 43-46%, while residual trapping remained below 5%, and mobile CO 2 was substantially reduced due to mineralization, demonstrating that as the system becomes more water-wet, CO 2 is more effectively converted into stable carbonate minerals, although extensive mineral precipitation may lead to pore clogging. A global Sobol-Morris sensitivity analysis further reveals that the kinetic parameters of reactive minerals are the most influential factor, followed by wettability, while salinity has only a minor influence. Furthermore, these findings highlight that wettability is not merely a flow property but a fundamental control on CO 2 mineralization in basalts, with direct implications for site selection for storage projects.

Basalts↗

WBM-Hydro-ReEDS

WBM-hydro-ReEDS is a tool for converting daily reservoir release simulations from the WMB model to monthly, plant-level hydropower generation estimates, and then to inputs for the ReEDS model.

Turner, Sean [Oak Ridge National Laboratory (ORNL)↗

A Non-Invasive Approach for Elucidating the Spatial Distribution of In-Situ Stress in Deep Subsurface Geologic Formations Considered for CO 2 Storage (Final Report)

The primary objectives of this project were to: develop a new, non-invasive method to define the orientation and magnitude of in-situ stresses in deep geologic formations (depths that exceed 1500 meters) considered for carbon dioxide (CO 2 ) sequestration; to demonstrate the method at a real field site; and, to extend current technical capabilities and reduce costs of acquiring information about deep-stress fields. This investigation was segmented into five tasks, including Project Management (Task 1) and four technical tasks (Tasks 2 through 5). The results of the technical tasks are described in this document.

02 PETROLEUM↗