Electronic Thesis/Dissertation
 

Offshore Sub-seabed CO₂ Storage Resource Assessment & Site Selection Using Multi-Criteria Decision Model for Depleted Oil & Gas Wells

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Today, carbon dioxide levels are rising rapidly. Three million years earlier was last time CO₂ levels in the atmosphere remained this high during the “Pliocene mean warm period”, and the temperature stood 2° to 3° Celsius, or (3.6° to 5.4° Fahrenheit); greater than the “pre-industrial times”. The sea level remained 15 to 25 meters or (50 to 80 feet) greater than now. The increase in anthropogenic CO₂ (carbon dioxide) is accountable for about 2/3 of the total energy imbalance triggering global warming. To achieve the President of the United States' ambitious net zero economic emissions climate objective by 2050, considerable volumes of CO₂ will likely need to be captured, transported, and permanently sequestered (Council on Environmental Quality (CEQ)., 2022). This research presents a framework for subsea geological sequestration (GS) of offshore CO₂ and a methodology to assess the potential of subsurface resources. The goals of CO₂ injection will be pure sequestration, that is, the long-term storage of CO₂ in sub seabed depleted oil and gas wells. The literature review provides a description of assessment methods that deal with resource potential and storage capacities at various scales.We developed the methodology presented in this report for an assessment based on the analysis of publicly available data on thousands of depleted oil and gas sands. The valued resource is the pore-space volume where CO₂ may be inserted and held for multi millenniums. This report uses the methodology based on the multi-criteria decision model to integrate ambiguity and accepted unpredictability into volumetric constraints.The practice also includes a statistical assessment based on size, number of possible storage locations, and categorize possible storage value in tons with a graphical map that includes longitude and latitude for accurate site selection. This research will provide a storage capacity value in millions of tons as well as all the parameters used for each site during the site selection using the Multi-Criteria Decision Model (MCDM), TOPSIS. The result of this study will help to significantly reduce greenhouse gas emissions by providing organizations with a comprehensive tool and places where CO₂ can be stored.

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