{"title":"Rapid screening of saline aquifers for CO2 sequestration: A focus on storage capacity and injectivity index","authors":"Milad Balvayeh , Ali Ramezani , Behzad Rostami","doi":"10.1016/j.geoen.2025.214174","DOIUrl":null,"url":null,"abstract":"<div><div>This study aims to develop a robust and accurate method for evaluating the storage capacity and injectivity index for CO<sub>2</sub> storage in saline aquifers. The screening out procedure includes defining objective functions assessing candidates' feasibility, such as storage capacity and injectivity. Aquifers should be able to store a large volume of CO<sub>2</sub> and enable efficient CO<sub>2</sub> injection. To achieve this, each objective's technical parameters need to be identified and understood. Researchers reviewed past studies to identify global key parameters and their ranges. Based on the information, a series of simulations were conducted using design of experimental and statistical techniques to further investigate the most important parameters. The results of the simulations show that compressibility, depth, and pressure gradient have the greatest impact on storage capacity. Graphs were created using these parameters to quickly estimate storage efficiency. Within the studied parameter range, the maximum storage efficiency, defined as the ratio of storable pore volume to total pore volume, was approximately 14 %. For injectivity, permeability, thickness, and depth were identified as the most important parameters. The flow capacity, which is the product of permeability and thickness (kh), was used for screening in this section. It was determined that structures with kh values less than 900 mD-m are almost uneconomical for projects. Conversely, flow capacity values above 15000 mD-m indicate favorable conditions for project implementation. For other values, the economic feasibility of the project can be assessed without further simulation by using the estimated equations and graphs derived from the study. Finally, after reviewing and comparing the model results with operational cases, it was determined that the presented model has the ability to be quickly and practically used in the field.</div></div>","PeriodicalId":100578,"journal":{"name":"Geoenergy Science and Engineering","volume":"256 ","pages":"Article 214174"},"PeriodicalIF":4.6000,"publicationDate":"2025-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geoenergy Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949891025005329","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
This study aims to develop a robust and accurate method for evaluating the storage capacity and injectivity index for CO2 storage in saline aquifers. The screening out procedure includes defining objective functions assessing candidates' feasibility, such as storage capacity and injectivity. Aquifers should be able to store a large volume of CO2 and enable efficient CO2 injection. To achieve this, each objective's technical parameters need to be identified and understood. Researchers reviewed past studies to identify global key parameters and their ranges. Based on the information, a series of simulations were conducted using design of experimental and statistical techniques to further investigate the most important parameters. The results of the simulations show that compressibility, depth, and pressure gradient have the greatest impact on storage capacity. Graphs were created using these parameters to quickly estimate storage efficiency. Within the studied parameter range, the maximum storage efficiency, defined as the ratio of storable pore volume to total pore volume, was approximately 14 %. For injectivity, permeability, thickness, and depth were identified as the most important parameters. The flow capacity, which is the product of permeability and thickness (kh), was used for screening in this section. It was determined that structures with kh values less than 900 mD-m are almost uneconomical for projects. Conversely, flow capacity values above 15000 mD-m indicate favorable conditions for project implementation. For other values, the economic feasibility of the project can be assessed without further simulation by using the estimated equations and graphs derived from the study. Finally, after reviewing and comparing the model results with operational cases, it was determined that the presented model has the ability to be quickly and practically used in the field.