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| Type: | Resource | |
| Storage: | The size of this resource is 31.6 KB | |
| Created: | Feb 04, 2022 at 11:24 p.m. | |
| Last updated: | Feb 04, 2022 at 11:58 p.m. | |
| DOI: | 10.4211/hs.ea5d0091789043e8a8091ae43d314554 | |
| Citation: | See how to cite this resource |
| Sharing Status: | Published |
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| Views: | 605 |
| Downloads: | 6 |
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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 approach for designing control systems for the potential brine leakage from CO2 storage zones. The developed approach applies the technique of deep brine extraction to control the leakage, thus it incorporates the global optimizer of Genetic Algorithm (GA) and a FEFLOW-based transport model to find the best extraction locations in the storage zone that minimizes the needed amount of extracted brine. In an ~8m long soil tank, a brine leakage plume was controlled using the extraction system designed based on the GA results. Collected data was then used to first make sure that the GA results and boundary conditions were accurately applied in the experiment and second to evaluate whether the observed plume concentrations in the shallow aquifer met the predefined constraining limits in the optimization problem. Acquired data during the experiment included transient measurements of the injection and extraction flow rates as well as plume concentrations. 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 |
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| 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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