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| Type: | Resource | |
| Storage: | The size of this resource is 47.3 KB | |
| Created: | Jul 05, 2021 at 2:42 p.m. | |
| Last updated: | Aug 06, 2021 at 6:21 p.m. (Metadata update) | |
| Published date: | Aug 06, 2021 at 6:21 p.m. | |
| DOI: | 10.4211/hs.dc8fd2aad42e40ebb7f441bb2afc6751 | |
| Citation: | See how to cite this resource |
| Sharing Status: | Published |
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| Views: | 908 |
| Downloads: | 5 |
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Abstract
The Center for Experimental Study of Subsurface Environmental Processes (CESEP) conducted an intermediate-scale laboratory experiment to validate a developed framework for designing CO2-sequesteration monitoring systems based on using brine leakage as an early indictor for CO2 leakage. The developed framework incorporates the linear uncertainty analysis tool in PEST with the global optimizer of Genetic Algorithm and a FEFLOW-based transport model to find the best monitoring locations to detect the leakage and provide the designer with useful data to make remediation-related predictions. In an ~8m long soil tank, a brine leakage plume from the storage zone to the shallow aquifer was monitored using the system designed by this framework. The collected high-resolution data was then used to calibrate the model and make the predictions of interest, which were eventually compared to experimental measurements to evaluate the data informativity and thus validate the framework applicability. Acquired data from the monitoring system included transient measurements of the hydraulic heads and plume concentrations. In additions, the tracer injection rates, tank inflows and outflows were also measured. The conducted experiment and the testing system are described in detail in a research article developed by the dataset authors and entitled "Monitoring Brine Leakage from Deep Geologic Formations Storing Carbon Dioxide: Design Framework Validation Using Intermediate-Scale Experiment". For any questions, users are referred to the data owners.
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Funding Agencies
This resource was created using funding from the following sources:
| Agency Name | Award Title | Award Number |
|---|---|---|
| National Science Foundation | Collaborative Research: A New Inverse Theory for Joint Parameter and Boundary Conditions Estimation to Improve Characterization of Deep Geologic Formations and Leakage Monitoring | 1702060 |
Contributors
People or Organizations that contributed technically, materially, financially, or provided general support for the creation of the resource's content but are not considered authors.
| Name | Organization | Address | Phone | Author Identifiers |
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| Andrew Trautz | Colorado School of Mines | Colorado, US | ||
| Ye Zhang | University of Wyoming | |||
| Cody Goebe | Colorado School of Mines | |||
| Analise Butler | Colorado School of Mines |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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