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All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Carbon Sequestration

Carbon Sequestration- the process of capturing the CO2 released by the burning of fossil fuels and storing it deep withing the Earth, trapped by a non-porous layer of rock.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2013

Interface Induced Carbonate Mineralization: A Fundamental Geochemical Process Relevant to Carbon Sequestration

Carbonate mineralization and polymorphic formation are key issues in underground CO 2 storage and biomineralization processes and closely related to mineral substrates. We investigated effects of mineral surfaces, solution chemistry, and anhydrous organic solvent on nucleation and growth of Ca-Mg-carbonate minerals. The effect of substrates of mica, diopside, tremolite, and hematite on calcite nucleation and growth in both experimental and natural environments were investigated using SEM, XRD, and EBSD methods. EBSD analysis can determine orientations between substrates and calcite crystals effectively.

58 GEOSCIENCES↗
DOE OSTI2015

Correction to Capillary Pressure–Saturation Relations for Supercritical CO 2 and Brine in Limestone/Dolomite Sands: Implications for Geologic Carbon Sequestration in Carbonate Reservoirs

Our previous publication on capillary pressure-saturation (P c -S w ) relations in carbonate sands contained P c values that were offset from their true equilibrium values. Original Figures 2, 3, and 4 showed nonequilibrium P c values that were close to the intended equilibrium P c . The modified figures using the equilibrium P c data are shown below. Other elements of the original paper and its conclusions remain unaffected. Further corrections to the Supporting Information are also available. We apologize for the inconvenience caused to readers.

58 GEOSCIENCES↗
DOE OSTI2014

Basin-Scale Leakage Risks from Geologic Carbon Sequestration: Impact on Carbon Capture and Storage Energy Market Competitiveness

This three-year project, performed by Princeton University in partnership with the University of Minnesota and Brookhaven National Laboratory, examined geologic carbon sequestration in regard to CO 2 leakage and potential subsurface liabilities. The research resulted in basin-scale analyses of CO 2 and brine leakage in light of uncertainties in the characteristics of leakage processes, and generated frameworks to monetize the risks of leakage interference with competing subsurface resources. The geographic focus was the Michigan sedimentary basin, for which a 3D topographical model was constructed to represent the hydrostratigraphy. Specifically for Ottawa County, a statistical analysis of the hydraulic properties of underlying sedimentary formations was conducted. For plausible scenarios of injection into the Mt. Simon sandstone, leakage rates were estimated and fluxes into shallow drinking-water aquifers were found to be less than natural analogs of CO 2 fluxes. We developed the Leakage Impact Valuation (LIV) model in which we identified stakeholders and estimated costs associated with leakage events. It was found that costs could be incurred even in the absence of legal action or other subsurface interference because there are substantial costs of finding and fixing the leak and from injection interruption. We developed a model framework called RISCS, which can be used to predict monetized risk of interference with subsurface resources by combining basin-scale leakage predictions with the LIV method. The project has also developed a cost calculator called the Economic and Policy Drivers Module (EPDM), which comprehensively calculates the costs of carbon sequestration and leakage, and can be used to examine major drivers for subsurface leakage liabilities in relation to specific injection scenarios and leakage events. Finally, we examined the competiveness of CCS in the energy market. This analysis, though qualitative, shows that financial incentives, such as a carbon tax, are needed for coal combustion with CCS to gain market share. In another part of the project we studied the role of geochemical reactions in affecting the probability of CO 2 leakage. A basin-scale simulation tool was modified to account for changes in leakage rates due to permeability alterations, based on simplified mathematical rules for the important geochemical reactions between acidified brines and caprock minerals. In studies of reactive flows in fractured caprocks, we examined the potential for permeability increases, and the extent to which existing reactive transport models would or would not be able to predict it. Using caprock specimens from the Eau Claire and Amherstburg, we found that substantial increases in permeability are possible for caprocks that have significant carbonate content, but minimal alteration is expected otherwise. We also found that while the permeability increase may be substantial, it is much less than what would be predicted from hydrodynamic models based on mechanical aperture alone because the roughness that is generated tends to inhibit flow.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Probabilistic evaluation of shallow groundwater resources at a hypothetical carbon sequestration site

Carbon sequestration in geologic reservoirs is an important approach for mitigating greenhouse gases emissions to the atmosphere. This study first develops an integrated Monte Carlo method for simulating CO 2 and brine leakage from carbon sequestration and subsequent geochemical interactions in shallow aquifers. Then, we estimate probability distributions of five risk proxies related to the likelihood and volume of changes in pH, total dissolved solids, and trace concentrations of lead, arsenic, and cadmium for two possible consequence thresholds. The results indicate that shallow groundwater resources may degrade locally around leakage points by reduced pH and increased total dissolved solids (TDS). The volumes of pH and TDS plumes are most sensitive to aquifer porosity, permeability, and CO 2 and brine leakage rates. The estimated plume size of pH change is the largest, while that of cadmium is the smallest among the risk proxies. Plume volume distributions of arsenic and lead are similar to those of TDS. The scientific results from this study provide substantial insight for understanding risks of deep fluids leaking into shallow aquifers, determining the area of review, and designing monitoring networks at carbon sequestration sites.

58 GEOSCIENCES↗
DOE OSTI2013

Assessment of Brine Management for Geologic Carbon Sequestration

Geologic carbon sequestration (GCS) is the injection of carbon dioxide (CO 2 ), typically captured from stationary emission sources, into deep geologic formations to prevent its entry into the atmosphere. Active pilot facilities run by regional United States (US) carbon sequestration partnerships inject on the order of one million metric tonnes (mt) CO 2 annually while the US electric power sector emits over 2000 million mt-CO 2 annually. GCS is likely to play an increasing role in US carbon mitigation initiatives, but scaling up GCS poses several challenges. Injecting CO 2 into sedimentary basins raises fluid pressure in the pore space, which is typically already occupied by naturally occurring, or native, brine. The resulting elevated pore pressures increase the likelihood of induced seismicity, of brine or CO 2 escaping into potable groundwater resources, and of CO 2 escaping into the atmosphere. Brine extraction is one method for pressure management, in which brine in the injection formation is brought to the surface through extraction wells. Removal of the brine makes room for the CO 2 and decreases pressurization. Although the technology required for brine extraction is mature, this form of pressure management will only be applicable if there are cost-­effective and sustainable methods of disposing of the extracted brine. Brine extraction, treatment, and disposal may increase the already substantial capital, energy, and water demands of Carbon dioxide Capture and Sequestration (CCS). But, regionally specific brine management strategies may be able to treat the extracted water as a source of revenue, energy, and water to subsidize CCS costs, while minimizing environmental impacts. By this approach, value from the extracted water would be recovered before disposing of any resulting byproducts. Until a price is placed on carbon, we expect that utilities and other CO 2 sources will be reluctant to invest in capital intensive, high risk GCS projects; early technical, economic, and environmental assessments of brine management are extremely valuable for determining the potential role of GCS in the US. We performed a first order feasibility and economic assessment, at three different locations in the US, of twelve GCS extracted-­water management options, including: geothermal energy extraction, desalination, salt and mineral harvesting, rare-­earth element harvesting, aquaculture, algae biodiesel production, road de-­icing, enhanced geothermal system (EGS) recharge, underground reinjection, landfill disposal, ocean disposal, and evaporation pond disposal. Three saline aquifers from different regions of the US were selected as hypothetical GCS project sites to encompass variation in parameters that are relevant to the feasibility and economics of brine disposal. The three aquifers are the southern Mt. Simon Sandstone Formation in the Illinois Basin, IL; the Vedder Formation in the southern San Joaquin Basin, CA; and the Jasper Interval in the eastern Texas Gulf Basin, TX. These aquifers are candidates for GCS due to their physical characteristics and their close proximity to large CO 2 emission sources. Feasibility and impacts were calculated using one mt-­CO 2 injected as the functional unit of brine management. Scenarios were performed for typical 1000MW coal-­fired power plants (CFPP) that incurred an assumed 24 percent carbon capture energy penalty (EP), injected 90 percent of CO 2 emissions (~9 million mt-­ CO 2 injected annually), and treated extracted water onsite. Net present value (NPV), land requirements, laws and regulations, and technological limits were determined for each stage of disposal, and used to estimate feasibility. The boundary of the assessment began once extracted water was brought to the surface, and ended once the water evaporated, was injected underground, or was discharged into surface water bodies. Results of the assessment were generated, stored, and analyzed using Microsoft Excel spreadsheets and ESRI Geographical Information System (GIS) maps. Conclusions about the relative benefits and impacts of alternative brine-­management strategies were highly sensitive to local climate and weather, and aquifer water chemistry. The NPV of certain scenarios ranged from -­$50/mt-­CO 2 (a cost) to +$10/mt-­CO 2 (revenue). The land footprint of the scenarios in this study ranged from <1 km 2 to 100 km 2 . Brine extraction as a pressure management tool for GCS has potential for improving the economics and for minimizing the environmental impacts of CCS. In order to maximize this potential, careful analysis of each saline aquifer and region must be conducted to determine a regionally appropriate brine use sequence (BUS) at the time of site selection. Models that use GIS will be essential tools in determining such sequences for individual CFPP. Future studies that perform risk and life cycle assessments (LCA) of BUS scenarios, incorporate additional impact metrics into the BUS model, and enhance the temporal sensitivity of the model would improve the robustness of this regional assessment method.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Fourier-MIONet: Fourier-enhanced multiple-input neural operators for multiphase modeling of geological carbon sequestration

Geologic carbon sequestration (GCS) is a safety-critical technology that aims to reduce the amount of carbon dioxide in the atmosphere, which also places high demands on reliability. Multiphase flow in porous media is essential to understand CO 2 migration and pressure fields in the subsurface associated with GCS. However, numerical simulation for such problems in 4D is computationally challenging and expensive, due to the multiphysics and multiscale nature of the highly nonlinear governing partial differential equations (PDEs). It prevents us from considering multiple subsurface scenarios and conducting real-time optimization. Here, we develop a Fourier-enhanced multiple-input neural operator (Fourier-MIONet) to learn the solution operator of the problem of multiphase flow in porous media. Fourier-MIONet utilizes the recently developed framework of the multiple-input deep neural operators (MIONet) and incorporates the Fourier neural operator (FNO) in the network architecture. Once Fourier-MIONet is trained, it can predict the evolution of saturation and pressure of the multiphase flow under various reservoir conditions, such as permeability and porosity heterogeneity, anisotropy, injection configurations, and multiphase flow properties. Compared to the enhanced FNO (U-FNO), the proposed Fourier-MIONet has 90% fewer unknown parameters, and it can be trained in significantly less time (about 3.5 times faster) with much lower CPU memory (<15%) and GPU memory (<35%) requirements, to achieve similar prediction accuracy. In addition to the lower computational cost, Fourier-MIONet can be trained with only 6 snapshots of time to predict the PDE solutions for 30 years. Furthermore, we observed that Fourier-MIONet can maintain good accuracy when predicting out-of-distribution (OOD) data. The excellent generalizability of Fourier-MIONet is enabled by its adherence to the physical principle that the solution to a PDE is continuous over time. Furthermore, the developed Fourier-MIONet makes it possible to solve the long-time evolution of geological carbon sequestration in a large-scale three-dimensional space accurately and efficiently.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Geochemical and geomechanical alteration of siliciclastic reservoir rock by supercritical CO 2 -saturated brine formed during geological carbon sequestration

Geologic carbon sequestration (GCS) is a method for storing CO 2 and mitigating greenhouse gas emissions. During GCS, carbon dioxide dissolves into pore water, resulting in a low-pH brine that can react with reservoir rock minerals. This work evaluates the effects of geochemical reactions on geomechanical integrity of representative siliciclastic reservoir samples obtained from the Mt. Simon formation. Rock samples were aged 4 or 8 weeks in CO 2 -saturated brine under reservoir conditions, and in N 2 -saturated brine as a control. Post-aging, CT scans revealed more extensive micro-fracture development along horizontal bedding planes at grain edges in CO 2 versus N 2 -aged samples. Digital analysis of CO 2 -aged samples showed porosity increase from 8.1% to 15.8%. Scanning electron microscopy unearthed the loss of clay cementation, greater exposure of quartz and K-feldspar grains, and apparent surface roughening (confirmed by laser profilometry) in CO 2 -aged samples, but not in N 2 -aged samples. Fracture toughness as evaluated by scratch testing was reduced by 32.1% after 4 weeks in scCO 2 -saturated brine and 69.5% after 8 weeks. The main reason for weakening appears to be detachment of clays from quartz and feldspar grain surfaces, resulting in weakening of the rock matrix. Rock weakening may alter the geomechanical stability of storage formations.

58 GEOSCIENCES↗
NASA NTRS2007

Using NASA Techniques to Atmospherically Correct AWiFS Data for Carbon Sequestration Studies

Carbon dioxide is a greenhouse gas emitted in a number of ways, including the burning of fossil fuels and the conversion of forest to agriculture. Research has begun to quantify the ability of vegetative land cover and oceans to absorb and store carbon dioxide. The USDA (U.S. Department of Agriculture) Forest Service is currently evaluating a DSS (decision support system) developed by researchers at the NASA Ames Research Center called CASA-CQUEST (Carnegie-Ames-Stanford Approach-Carbon Query and Evaluation Support Tools). CASA-CQUEST is capable of estimating levels of carbon sequestration based on different land cover types and of predicting the effects of land use change on atmospheric carbon amounts to assist land use management decisions. The CASA-CQUEST DSS currently uses land cover data acquired from MODIS (the Moderate Resolution Imaging Spectroradiometer), and the CASA-CQUEST project team is involved in several projects that use moderate-resolution land cover data derived from Landsat surface reflectance. Landsat offers higher spatial resolution than MODIS, allowing for increased ability to detect land use changes and forest disturbance. However, because of the rate at which changes occur and the fact that disturbances can be hidden by regrowth, updated land cover classifications may be required before the launch of the Landsat Data Continuity Mission, and consistent classifications will be needed after that time. This candidate solution investigates the potential of using NASA atmospheric correction techniques to produce science-quality surface reflectance data from the Indian Remote Sensing Advanced Wide-Field Sensor on the RESOURCESAT-1 mission to produce land cover classification maps for the CASA-CQUEST DSS.

Holekamp, Kara L.↗
DOE OSTI2024

Efficient and generalizable nested Fourier-DeepONet for three-dimensional geological carbon sequestration

Geological carbon sequestration (GCS) involves injecting CO2 into subsurface geological formationsfor permanent storage. Numerical simulations could guide decisions in GCS projects by predictingCO 2 migration pathways and the pressure distribution in storage formation. However, these simula-tions are often computationally expensive due to highly coupled physics and large spatial-temporalsimulation domains. Surrogate modelling with data-driven machine learning has become a promis-ing alternative to accelerate physics-based simulations. Among these, the Fourier neural operator(FNO) has been applied to three-dimensional synthetic subsurface models. Despite its good accuracyin simulating CO 2 plume migration, it requires large computational resources in training and alsolacks generalizability. Here, to further improve performance, we have developed a nested Fourier-DeepONet by combining the expressiveness of the FNO with the modularity of a deep operatornetwork (DeepONet). This new framework is twice as efficient as a nested FNO for training and has atleast 80% lower GPU memory requirement due to its flexibility to treat temporal coordinates sepa-rately. These performance improvements are achieved without compromising prediction accuracy.In addition, the generalization and extrapolation ability of nested Fourier-DeepONet beyond thetraining range has been thoroughly evaluated. Nested Fourier-DeepONet outperformed the nestedFNO for extrapolation in time with more than 50% reduced error. It also exhibited good extrapolationaccuracy beyond the training range in terms of reservoir properties, number of wells, and injectionrate.

Lee, Jonathan E. [Department of Chemical and Envir↗