SEARCH · Search NASA
Results for “Carbon Sequestration”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Stability and Growth of Methane Hydrates in Confined Media for Carbon Sequestration
Not provided.
Soil moisture controls over carbon sequestration and greenhouse gas emissions: a review
Not Available
Techno-economic analysis of indirect carbonation processes for carbon sequestration using mining waste
A comprehensive assessment of process design, cost efficiency, critical mineral recovery, and CO 2 storage in mine tailings.
Leveraging Machine Learning Tools to Update the National Carbon Sequestration Database (NATCARB)
GSA (Geological Society of America) Connects 2022, Denver CO, October 7-10, 2022
Regional Geology Capstone Report for the Midwestern Regional Carbon Sequestration Partnership
This capstone report summarizes the regional characterization of geologic storage subtasks performed under MRCSP Phase III.
Economic Analysis of Geologic Carbon Sequestration Projects.
Abstract not provided.
Potential seismicity along basement faults Induced by geological carbon sequestration.
Abstract not provided.
Southwest Regional Partnership on Carbon Sequestration (Phase III) Underground Source of Drinking Water Monitoring at the Farnsworth Unit
The Ogallala aquifer is identified as the only underground source of drinking water (USDW) aquifer in the vicinity of the FWU. Throughout the span of the SWP project at the FWU, groundwater samples from the Ogallala Aquifer were collected and analyzed on a regular basis to obtain information that reflects the water quality baseline and any potential leakage, and to facilitate effective simulations and risk assessment. To date, hundreds of samples have been collected and tested. The water analysis results suggest that the Ogallala groundwater quality maintains stable and potable, and no leakage is indicated by these data.
CO2 Plume Imaging with Accelerated Deep Learning-based Data Assimilation Considering Multiple Realizations: Application to the Illinois Basin-Decatur Carbon Sequestration Project
We propose a fast and efficient deep learning workflow for near real-time data assimilation, forecasting and visualization of CO2 plume evolution in saline aquifer and demonstrate its application at a field site. Unlike the previous work, this study incorporates the impact of spatial heterogeneity using multiple realizations. In the proposed workflow, a neural network model utilizes available monitoring data such as downhole pressure measurements as input and predicts the propagating pressure ‘front’ using the diffusive time of flight (DTOF) map which is considered as representative reservoir image of the flow field. The DTOF is the arrival time of pressure front propagation, which can be computed by the Fast Marching Method rapidly without flow simulations. Reservoir model calibration can be implemented by selecting the training data samples that describe the predicted DTOF map based on observed data. The power and efficacy of our workflow is demonstrated by application to the Illinois Basin-Decatur Project.
Monitor Potential Fracture Growth in Carbon Sequestration Reservoirs using Distributed Strain Sensing
Develop and validate a displacement discontinuity model and inversion framework using distributed strain sensing (DSS) for real-time fracture monitoring and improved localization in subsurface applications.
Tools for Data Collection, Curation, and Discovery to Support Carbon Sequestration Insights
AGU Fall Meeting 2020 (Conference), Virtual, December 1- 17, 2020.
Potential of soil carbon sequestration to mitigate climate change
Explore the source record for details and available documents.
Field-scale simulation of geologic carbon sequestration in faulted and fractured natural formations
Explore the source record for details and available documents.
Comparison of MeshGraphNet Techniques for Subsurface Behavior Prediction during CO2 Sequestration
Carbon sequestration is a vital part of the effort to mitigate anthropogenic climate change. Previously, we have shown that Graph Neural Networks (GNNs) provide the ability to extract meaningful insights during prediction of subsurface behavior in carbon storage projects. However, these models have struggled with long-term prediction accuracy due to error accumulation caused by autoregressive prediction. This research leverages the Illinois Basin – Decatur Project (IBDP) dataset to examine strategies for minimizing loss over time in a MeshGraphNet GNN model to improve reliability of predictions while minimizing inferencing time.
Supply chain optimization of sustainable aviation fuel from carinata in the Southeastern United States
We report carinata is a purpose-grown oilseed feedstock for renewable fuels, including sustainable aviation fuel (SAF) that can replace conventional aviation fuel (CAF). Given carinata is a new crop in the Southeastern United States, it is crucial to analyze its sustainability from a supply chain perspective. This study developed a mixed-integer linear programming (MILP) model and simulated it for 20 years, starting from a farm (county-level data) and ending at the airport. About 2.06 million ha in Alabama, Florida, and Georgia combined were found suitable for carinata production. Given the three-year rotation period, about 0.69 million hectares can be cultivated annually, approximately 65% of which was in Georgia. About 2.4% of the combined SAF annual demand of four major airports (about 210 thousand t) in the study area is satisfied at that level of carinata cultivation. However, all available SAF was supplied to the Atlanta airport as this decision minimizes the supply chain cost. A total of 1343 storage units, one oil extraction mill, and one biorefinery were needed to meet the overall demand. We found that SW Georgia is the top supplier of carinata seeds. The unit cost of production and carbon intensity were estimated to be $\$$0.89 L -1 (or $\$$26.79 GJ -1 ) and 0.91 kg CO 2 e L -1 (or 27.28 kg CO 2 e GJ -1 ), respectively. This carbon intensity of carinata-based SAF was 67.8% lower than that of CAF. With variations included in SAF demand, yield, and soil carbon sequestration, carbon savings remained between 66.5% and 67.8%. Given the GHG advantage of SAF over CAF, there is justification for subsidies required to make SAF competitive.