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DOE OSTI2023

Assessing pore network heterogeneity across multiple scales to inform CO2 injection models

Geologic heterogeneity is a key feature that must be considered when translations of scaled data are performed. This paper presents the assessment of geologic heterogeneity using a multiscale workflow that includes image analysis-based methods coupled with well log analysis to provide data in which fractals and machine learning methods estimate the carbon dioxide (CO 2 ) storage resource potential of a reservoir. The heterogeneity of rock properties of the complex Bell Creek reservoir in Montana, USA, was explored at the pore scale (~nm to mm), core scale (~mm to m), and well scale (~cm to m). The data used in this study included advanced image analysis of micro-CT (computed tomography) images (pore scale), thin sections (pore scale), plugs and core images (core scale) and well logs (well scale). The micro-CT images were segmented using a U-net segmentation approach into objects of pores and grains. Further, the segmented images were reconstructed into subvolumes of different sizes. Physical properties (porosity and permeability) and fractal dimensions were calculated for the various subvolumes, and Lorenz coefficient (Lc) values, a single parameter to describe the degree of heterogeneity within a pay zone section, were calculated from thin-section images and well logs. Porosity and fractal dimension values were used to estimate the 188-µm threshold of representative elementary volume (REV) in this study. Both the Lc and fractal dimension values were found to be negatively correlated. When these two parameters are combined, it is possible to discern differences in the complex porous networks of the samples analyzed in this study.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Quantifying the effects of pressure management for the Williston basin Brine Extraction and Storage Test (BEST) site using machine learning

Active reservoir management (ARM) through brine extraction can reduce pressure buildup during large-scale implementation of carbon capture and storage (CCS) projects. This study used machine learning (ML)-assisted approaches to analyze bottomhole pressure (BHP) responses to various brine injection and extraction scenarios. Field monitoring data were collected over a 2-year operation period at two injection wells and one extraction well (about 400 meters away) as part of a Brine Extraction and Storage Test (BEST) in the North Dakota portion of the Williston Basin. Injection activities increased the BHPs at the injection wells by around 0.70 MPa (~100 psi) during the operation period. Extraction activities demonstrated the capability to decrease the BHPs at the injection wells by approximately 0.21–0.34 MPa (30–50 psi) depending on the ratio of the extraction and injection well flow rates (the “extraction ratio” – a normalization procedure used in the analysis). The pressure reduction provided by the extraction well equated to 30%–50% of the pressure buildup at the injection well. Furthermore, this work shows how ML analytics can play a key role in estimating reservoir pressure responses for complex injection and extraction activities during pressure management practices of CCS projects.

58 GEOSCIENCES↗
DOE OSTI2024

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↗
DOE OSTI2024

Application of a Geochemically Informed Leak Detection (GILD) Model to CO 2 Injection Sites on the United States Gulf Coast

The Gulf Coast region possesses great potential for CO 2 enhanced oil recovery (EOR) and CO 2 storage. A geochemically informed leak detection (GILD) model has been applied to CO 2 injection sites on the Gulf Coast with considerations of measurement variability. The Jasper aquifer in Montgomery County, Texas, was chosen to demonstrate the method. Based on background data from wells in the area, combinations of mineral and fluid compositions were used to create 23 scenarios for the geochemical model. The output from the geochemical model was used to identify sensitive monitoring species, and response functions were generated for these as a function of the CO 2 leakage concentration. The sources of measurement variability for background conditions were characterized from the Jasper aquifer background data, and then normalized using the coefficient of variation of each species across the monitoring wells. Bayesian belief network (BBN) models were constructed, and measurement variability of different levels were added to compare leak detection probabilities. Increasing measurement variability decreased the power to detect a leak of a given size. For a moderately high CO 2 concentration of 0.2 mol/kg, the probability of detecting this leakage effect using pH as the monitoring variable in an aquifer with calcite decreases from 98% (no measurement variability) to 61% (medium variability) to 33% (high variability). The loss in power of the sampling protocol with increasing measurement variability is similar in magnitude when Ca 2+ or HCO 3 - is used as the monitoring parameter, but only for aquifers with calcite.

58 GEOSCIENCES↗
DOE OSTI2024

Advancing spatiotemporal forecasts of CO 2 plume migration using deep learning networks with transfer learning and interpretation analysis

Accurate and timely forecasts of CO 2 plume distribution throughout the injection and post-injection phases are crucial for detecting plume migration, assessing leakage risks, and supporting operational decisions in geologic carbon storage (GCS). Current convolutional neural network-based approaches primarily focus on spatial information and overlook temporal dependencies in plume distributions, thus limiting their ability to capture dynamic movement effects and provide accurate predictions of plume migration. In this work, we propose two deep learning models, Auto-Encoder (AE)-LSTM and Encoder-Decoder (ED)-ConvLSTM, each uniquely designed to capture both spatial and temporal features. We apply the proposed methods to forecast the dynamic distribution of CO 2 plumes based on 108 reservoir simulations over a 30-year injection and a 30-year post-injection period. The results indicate that the ED-ConvLSTM model outperforms the AE-LSTM model in accurately predicting the spatiotemporal dynamics of CO 2 plume migration, achieving R 2 values above 0.99. To provide a deeper understanding of these model predictions, we employ a gradient-based explanation method on the trained models. This approach provides insights into the influence of input variables on plume migration forecasts and uncovers the underlying prediction mechanisms of the proposed models. Furthermore, we introduce a transfer learning technique, enabling fast and accurate plume migration forecasting in the post-injection phase by leveraging the trained model during the injection phase. This reduces the necessity for extensive data collection or re-training. In conclusion, the methods proposed in our work enhances the performance and interpretability of CO 2 plume migration forecasts, thereby facilitating informed decision-making throughout the entire lifecycle of GCS applications.

58 GEOSCIENCES↗
DOE OSTI2024

An experimental investigation on the CO 2 storage capacity of the composite confining system

Assuring secure containment of stored CO 2 is of paramount importance—for climate change mitigation, for permitting, and for reassuring the public. Regional seals, such as those sealing petroleum accumulations, have proven to be effective for securing CO 2 . However, the goal of permanent sequestration can also be satisfied with “composite confining systems” consisting of multiple, possibly discontinuous flow barriers that, in aggregate, create a system with very high permeability anisotropy and effectively retard the vertical migration of CO 2 . This study focuses on investigating the barrier characteristics necessary for effective containment of CO 2 , using both physical flow experiments and modified invasion percolation simulations. The simulations are calibrated to the physical experiments and are used to further extend the analysis. Results show that for a composite confining system, a) even barriers with low capillary entry pressure contrast to the underlying flow unit can divert rising CO 2 ; b) curved or anticlinal barrier topography can enhance CO 2 trapping; c) fining-upward gradations make little difference to barrier effectiveness or CO 2 retention; d) longer barriers retain more CO 2 regardless of barrier topography. Finally, field-scale simulations have demonstrated the importance of barrier length for increasing CO 2 storage capacity. Furthermore, the results presented can be used to inform the development of new screening criteria for characterization and effectiveness of composite confining systems.

58 GEOSCIENCES↗
DOE OSTI2024

Impact of cement composition, brine concentration, diffusion rate, reaction rate and boundary condition on self-sealing predictions for cement-CO 2 systems

Geological CO 2 storage (GCS) plays an important role in curbing CO 2 emissions by reducing the carbon footprint of difficult to decarbonize operations and achieve negative CO 2 emissions through activities like Bioenergy with Carbon Capture and Storage (BECCS) and Direct Air Carbon Capture and Storage (DACCS). Leakage of CO 2 through wells is an important concern when it comes to deployment of large-scale GCS. Existing wells in sites that are otherwise suitable for GCS can act as conduits for stored CO 2 to escape the reservoir. There is broad consensus that the main risk of leakage through wellbores is via fractures/damaged pathways. The results from several studies evaluating the permeability evolution of cement fractures in wells upon leakage of CO 2 agree that smaller fracture apertures, slower brine velocities and higher brine residence times promote self-sealing of fractures by mineral precipitation. Quantitatively, however, the differences in sealing conditions are significant and are typically attributed to differences in experimental conditions or model assumptions. Here we examine the sensitivity of our model, describing CO 2 leakage through wellbores, to cement composition, brine concentration, diffusion rates, and reaction rates. We also evaluate the impact of the boundary condition to allow comparisons between observations from experiments performed at constant flow rate and model predictions made at constant pressure conditions. Our results show that diffusion and reactions rates have the most impact on the self-sealing criteria for cement-CO 2 systems. In addition, conditions associated with self-sealing of fractures at constant flow rate require longer fractures, smaller fracture apertures, and slower velocities than under constant pressure.

58 GEOSCIENCES↗
DOE OSTI2024

Impacts of irregularly-distributed acidified brine flow on geo-chemo-mechanical alteration in an artificial shale fracture under differential stress

The efficacy of geological carbon sequestration is reliant on the integrity of the caprock and its resistance to physical and chemical alteration. Caprocks with high abundance of reactive carbonates like calcite are susceptible to acid-promoted dissolution and can result in structural weakening. This work investigates the effect of acidified brine flow through an artificially fractured, high-carbonate (30 % by XRD) shale under differential compressive stress. Cylindrical samples were cut in half vertically and milled to create an artificial fracture with interlocking asperities and open channels. Samples were sheared with a single applied stress in a custom flow cell housed within an industrial CT scanner. Further, either acidic (pH 4) or reservoir-simulated (pH 9.5) brine was flowed through the artificial fracture for 7–8 days under reservoir pressure and room temperature. Model simulations indicate flow mainly occurred in open channels, with limited flow between overlapping asperities. Analysis of fracture surfaces by optical and scanning electron microscopy show increased surface alteration and roughness after exposure to pH 4 versus pH 9.5 brine indicating mineral dissolution/loss, and this effect is greater in areas that receive the highest brine flows. Similarly, surface analysis by scratch testing shows fracture toughness decreases more after exposure to acidic versus reservoir-simulated brine, with the greatest alteration in areas of highest acidic brine flows. Despite weakening, no shear slip occurred. Overall, the results indicate that acidified brine can result in significant physical and geomechanical alteration of irregular fracture surfaces in shale caprock, with greatest effects in preferential flow regions.

58 GEOSCIENCES↗
DOE OSTI2024

Heuristic algorithms for design of integrated monitoring of geologic carbon storage sites

Designs for Risk Evaluation and Management (DREAM) is a tool developed under the National Risk Assessment Partnership (NRAP) to enhance geologic carbon storage safety and efficiency. Using potential leakage scenarios generated externally by the users preferred history-matching approach, DREAM constructs ideal combinations of sensor locations in the right place at the right time to detect as many leaks as possible, detect them as early as possible, and minimize cost. This user-friendly tool, developed in Java, features a window-based GUI for input and a 3D visualization tool for viewing the domain space and optimized monitoring plans. DREAM's latest version accommodates real-world usage by allowing for joint optimization of wellbore point sensor placements and surface geophysics survey geometries, and by using more efficient multi-objective optimization algorithms. We show an example where, these two improvements combined allow us to support containment assurance and go from detecting 80–90 % of the potential CO 2 leakage to +99.7 %, a step-change improvement that can make the deciding difference in whether a site is suitable for geologic carbon storage. Though developed for geologic carbon storage, this tool would be equally applicable in many surface or offshore environmental monitoring projects.

58 GEOSCIENCES↗
DOE OSTI2024

Gigaton commercial-scale carbon storage and mineralization potential in stacked Columbia River basalt reservoirs

This work presents a detailed supercritical CO 2 storage resource estimation for the stacked basalt reservoirs in the Grande Ronde Basalt of the Columbia River Basalt Group in eastern Washington and Oregon. The assessment aims to derisk the commercialization potential of geologic carbon storage in basalt by leveraging both structural and mineralization trapping of CO 2 in basalt. The structural closures formed by anticlinal ridges and synclinal valleys in Yakima Fold Belt are excellent physical traps to accommodate injected supercritical CO 2 . Rigorous hydraulic testing, well logs and simulation results from the Wallula Basalt Pilot #1 well showed the occurrence of 17 suitable permeable injection zones (up to 2,496 mD) intercalated with dense seals (~2.6E-10 mD) in the Grand Ronde Basalt. In addition, geochemical studies showed fast reactions between supercritical CO 2 and dissolved basalt minerals to form stable carbonates. In conclusion, our calculation indicates up to 40 gigatons (P90) of mineralization storage resources exist in the Grande Ronde Basalt reservoirs.

58 GEOSCIENCES↗
DOE OSTI2024

An assessment of controlled source EM for monitoring subsurface CO 2 injection at the wyoming carbonSAFE geologic carbon storage site

Here we evaluate if electromagnetic (EM) geophysical methods for monitoring geologic carbon storage (GCS) efforts at the Wyoming CarbonSAFE project adjacent to the Dry Fork Station power plant near Gillette, Wyoming. This first involved acquiring both electric and magnetic fields at eleven different locations ranging in distance from immediately adjacent to 4 km from the plant. Passive EM measurements were made to provide spectral EM noise measurements generated by electricity production at the plant and to determine if useful magnetotelluric (MT) data can be successfully collected in the region. The processed data indicate that useful MT data can be collected as long as the site is located more than 2km away from the power plant as well as active roads and rail lines. Controlled source EM data were collected using three different source configurations, two of which connected to steel casings used to complete the injection wells. Comparing the EM noise measurements to the CSEM data show measurable electric and magnetic field signals at all sites. Next a series of three-dimensional (3D) numerical models were built that simulate resistivity changes caused by the proposed CO2 injection at depths ranging from 2.4 to 3.0km. These models were used to simulate various EM measurement configurations. The modeling shows that casing-source CSEM monitoring can provide sensitivity to the injected CO 2 if source electrodes are connected to the bottom of one or both of the injection wells.

58 GEOSCIENCES↗
DOE OSTI2024

Evaluating offshore legacy wells for geologic carbon storage: A case study from the Galveston and Brazos areas in the Gulf of Mexico

In this article, federal offshore waters in the Gulf of Mexico are of interest for large-scale geologic carbon storage (GCS). However, more than 80,000 offshore oil and gas wells exist in the region, which could impact the integrity of sealing intervals. In this study, we propose a screening methodology for ranking offshore legacy wells based on the challenge they may present to GCS. The methodology relies on the review of well regulatory records to 1) identify leakage pathways and assess the potential hazards that wells pose to planned GCS operations, 2) evaluate well features that impact the accessibility of wells to determine the feasibility of potential corrective actions, and 3) rank wells based on the overall challenge they may pose for GCS. We demonstrate our framework by evaluating the construction and abandonment of 156 wells across eight areas of interest (AOIs) in shallow federal waters along the Texas Gulf Coast. The majority (99.3 %) of wells considered were constructed and plugged in a manner that did not isolate prospective GCS targets in the Upper and Lower Miocene formations and may potentially require a challenging or uncertain corrective action prior to GCS. Dataset trends suggest that the observed well construction and plugging designs may be common in shallow offshore federal waters along the Texas Gulf Coast. Consequently, operators pursuing offshore GCS projects in the region may consider selecting areas that avoid challenging wells or performing robust evaluations of legacy well leakage risks to plan corrective action prior to CO 2 injection.

58 GEOSCIENCES↗
DOE OSTI2024

Can section 45Q tax credit foster decarbonization? A case study of geologic carbon storage at Acid Gas Injection wells in the Permian Basin

Carbon capture, utilization, and storage (CCUS) is an important pathway for meeting climate mitigation goals. While the economic viability of CCUS is well understood, previous studies do not evaluate the economic feasibility of carbon capture and storage (CCS) in the Permian Basin specifically regarding the new Section 45Q tax credits. We developed a technoeconomic analysis method, evaluated the economic feasibility of CCS at the acid gas injection (AGI) wells, and assessed the implication of Section 45Q tax credits for CCS at the AGIs. We find that the compressors, well depth, and the permit and monitoring costs drive the facility costs. Compressors are the predominant contributors to capital and operating expenditure driving the levelized cost of CO 2 storage. Strategic cost reduction measures identified include 1) sourcing of low-cost electricity and 2) optimizing operational efficiency in well operations. In evaluating the impact of the tax credits on CCS projects, facility scale proved decisive. We found that facilities with an annual injection rate exceeding 10,000 MT storage capacity demonstrate economic viability contingent upon the procurement of inputs at the least cost. The new construction of AGI wells were found to be economically viable at a storage capacity of 100,000 MT. The basin is heavily focused on CCUS (tax credit – $\$$65/MT CO 2 ), which overshadows CCS ($\$$85/MT CO 2 ) opportunities. Balancing the dual objectives of CCS and CCUS requires planning and coordination for optimal resource and pore space utilization to attain the basin's decarbonization potential. We also found that CCS on AGI is a lower cost CCS option as compared to CCS on other industries.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

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↗
DOE OSTI2026

A decade of progress in understanding and managing legacy well integrity for geologic carbon storage

This study reviews a decade of research progress in legacy well integrity and risk management for geologic carbon storage (GCS) to commemorate the 20 th anniversary of the Intergovernmental Panel on Climate Change’s 2005 Special Report on Carbon Capture and Storage. In the past ten years, legacy well research has benefited from global efforts to constrain emissions from abandoned oil and gas wells, a continued focus on well materials performance in the presence of CO 2 -rich fluids, and practical experience gained through GCS implementation. Field measurements of abandoned well emissions show that leakage is not universal or catastrophic but forms a continuum of low-to-moderate fluxes that depend on isolation integrity and environmental attenuation. Materials research has constrained the conditions under which Portland cements exhibit self-sealing and non-sealing behaviors, and has identified the impact of geomechanical properties, non-uniform pathway apertures, multi-phase flow, and impurities in the CO 2 stream, on leakage pathways as important new areas for investigation. GCS projects at brownfield sites have inspired the creation of new workflows that integrate various tools and technologies to manage legacy well leakage risks. GCS implementation has also motivated a push towards scenario-based well modeling that directly informs permit applications. These advances inspire new research questions for the coming decade, particularly around the level of legacy well leakage risk that is environmentally acceptable and tolerable to stakeholders when sequestering millions of tonnes of CO 2 annually.

Carbon capture and storage↗
DOE OSTI2026

Optimal CO 2 storage management considering safety constraints in multi-stakeholder multi-site GCS projects: A Markov game perspective

Geological carbon storage (GCS) projects could involve a diverse array of stakeholders or players from public, private, and regulatory sectors, each with different objectives and responsibilities. Given the complexity, scale, and long-term nature of GCS operations, determining whether individual stakeholders can independently optimize their interests — or whether collaborative coalition agreements are needed — remains a central question for effective GCS project planning and management. To access large, high-quality storage resources, future GCS deployment may increasingly occur in geologically connected sites, where shared geological features such as pressure space and reservoir pore capacity can lead to competitive behavior among stakeholders. In this work, we propose a paradigm based on Markov games to quantitatively investigate how different coalition structures affect the goals of stakeholders. We frame this multi-stakeholder multi-site problem as a multi-agent reinforcement learning problem with safety constraints. Our approach enables agents to learn optimal strategies while complying with safety regulations. We present an example where multiple operators are injecting CO 2 into their respective project areas in a geologically connected basin. To address the high computational cost of repeated simulations of high fidelity models, a previously developed surrogate model based on the Embed-to-Control (E2C) framework is employed. Our results demonstrate the effectiveness of the proposed framework in addressing optimal management of CO 2 storage when multiple stakeholders with different objectives and goals are involved.

58 GEOSCIENCES↗
DOE OSTI2026

Evolution of storage monitoring – update in response to commercial and regulatory drivers

Carbon Capture and Storage (CCS) is in transition from first-of-a kind projects and research-orientated pilots to commercially-motivated applications. Monitoring results from many newly developed and planned large scale commercial projects are limited; however, it is worthwhile to assess their evolution and consider new strategies as part of an effort to assess and document best practices. Commercial monitoring is targeted to activities that comply with regulatory drivers and de-risk investments. Commercial monitoring also supports accounting that storage has occurred and is tied to project financing. It deals with long time frames and large volumes injected into multiple wells and multiple projects in favorable areas. We see developing trends toward reproducible workflows that systematically reduce risks and clarify expectations for oversight and long-term surveillance. Monitoring techniques showing increasing trends include injection zone pressure as a history-matching and compliance tool. To reduce cost and environmental impact of time-lapse seismic data collection, deploying new approaches and tools, such as use of fibre and installed sources are increasingly applied. Concern over the risk of induced seismicity by regulatory bodies and the general public has increased, which has also resulted in increased monitoring. Some techniques used in the early research phases have been sidelined or used only in restricted applications. For example, geochemical analyses in the injection zone as well as the environment are now being deployed less than it was in research-oriented programs, except in the US where it is required by the permitting process. Expectations of frequent area-wide near surface monitoring have also decreased.

25 ENERGY STORAGE↗
DOE OSTI2026

Basin-scale analysis of Mokelumne River Formation for multi-well CO 2 injection

Large-scale carbon sequestration will likely require multiple projects injecting CO 2 into the same subsurface formation, raising concerns about safe operation and efficient use of storage capacity. This study evaluates the long-term response of the Mokelumne River Formation in California’s Sacramento Basin to multi-megaton CO 2 injection using three geologic models of the formation and the open-source simulator GEOS. The analysis focuses on three aspects of reservoir performance: (1) average pressure increase and dissolved CO 2 mass after 30 years for varying well counts and injection rates, (2) pressure interference in a multi-well configuration, and (3) dynamic storage capacity with identification of overpressure-prone regions. The results show that average formation pressure increases linearly with injected mass, while CO 2 dissolution exhibits mixed scaling: approximately linear with the number of wells but sublinear with injection rate, indicating that distributing injection across more wells enhances dissolution more effectively than increasing per-well rates. Pressure-interference effects are significant, with lower-permeability conditions delaying their onset but amplifying their magnitude at later times. Dynamic capacity, defined by the first occurrence of pressure exceeding the local overburden-based limit anywhere in the formation, varies across geologic models and assumed overburden pressure gradients. A lower fidelity geologic model predicts nearly twice the storage capacity of the two higher fidelity models, which consistently estimate approximately 1 Gt under the upper-bound overburden pressure gradient considered for the Sacramento Basin. In all model scenarios, overpressure develops away from injection wells, particularly in higher-elevation regions, highlighting the importance of basin-scale modelling for identifying risks beyond the immediate well vicinity.

Basin-scale↗