{"title":"Assessing ion interactions in low saline water flooding of sandstone reservoirs: numerical approach","authors":"Viswakanth Kandala, Suresh Kumar Govindarajan","doi":"10.1007/s12665-025-12194-4","DOIUrl":null,"url":null,"abstract":"<div><p>Low saline water flooding (LSWF) is a promising enhanced oil recovery (EOR) technique in petroleum engineering, offering a sustainable alternative to chemical EOR by targeting residual oil with minimal chemical use. However, the role of ion concentrations in influencing oil recovery remains insufficiently understood, creating a critical gap in LSWF optimization. This study addresses this gap by employing Sobol’ analysis, a global sensitivity analysis technique, to evaluate the impact of ion concentrations on oil recovery. Sobol’ analysis is applied over 81,920 samples for 2.3 pore volume injected (PVI) to assess the effects of multiphase fluid flow coupled with a reactive transport model. The results reveal that <span>\\([\\text {Na}^+]\\)</span>, <span>\\([\\text {Mg}^{2+}]\\)</span>, and <span>\\([\\text {Ca}^{2+}]\\)</span> significantly influence oil recovery, with strong interactions between <span>\\([\\text {Na}^+]\\)</span> and <span>\\([\\text {Ca}^{2+}]\\)</span>, as well as <span>\\([\\text {Ca}^{2+}]\\)</span> and <span>\\([\\text {Mg}^{2+}]\\)</span>. Among all, <span>\\([\\text {Na}^+]\\)</span> exhibits the highest Sobol’ first-order value, indicating its dominant role in recovery variation. Temporal analysis further suggests that interactive effects outweigh individual contributions. To manage uncertainties, cumulative probability values (<span>\\(\\hbox {P}_{{10}}\\)</span>, <span>\\(\\hbox {P}_{{50}}\\)</span>, and <span>\\(\\hbox {P}_{{90}}\\)</span>) are employed for optimization, minimizing variability in recovery predictions. Finally, this research provides a toolkit for evaluating ion interactions and optimizing LSWF, underscoring the role of ionic concentrations in sensitivity analysis, supporting decision making and risk assessment in upstream applications.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 7","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Earth Sciences","FirstCategoryId":"93","ListUrlMain":"https://link.springer.com/article/10.1007/s12665-025-12194-4","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Low saline water flooding (LSWF) is a promising enhanced oil recovery (EOR) technique in petroleum engineering, offering a sustainable alternative to chemical EOR by targeting residual oil with minimal chemical use. However, the role of ion concentrations in influencing oil recovery remains insufficiently understood, creating a critical gap in LSWF optimization. This study addresses this gap by employing Sobol’ analysis, a global sensitivity analysis technique, to evaluate the impact of ion concentrations on oil recovery. Sobol’ analysis is applied over 81,920 samples for 2.3 pore volume injected (PVI) to assess the effects of multiphase fluid flow coupled with a reactive transport model. The results reveal that \([\text {Na}^+]\), \([\text {Mg}^{2+}]\), and \([\text {Ca}^{2+}]\) significantly influence oil recovery, with strong interactions between \([\text {Na}^+]\) and \([\text {Ca}^{2+}]\), as well as \([\text {Ca}^{2+}]\) and \([\text {Mg}^{2+}]\). Among all, \([\text {Na}^+]\) exhibits the highest Sobol’ first-order value, indicating its dominant role in recovery variation. Temporal analysis further suggests that interactive effects outweigh individual contributions. To manage uncertainties, cumulative probability values (\(\hbox {P}_{{10}}\), \(\hbox {P}_{{50}}\), and \(\hbox {P}_{{90}}\)) are employed for optimization, minimizing variability in recovery predictions. Finally, this research provides a toolkit for evaluating ion interactions and optimizing LSWF, underscoring the role of ionic concentrations in sensitivity analysis, supporting decision making and risk assessment in upstream applications.
期刊介绍:
Environmental Earth Sciences is an international multidisciplinary journal concerned with all aspects of interaction between humans, natural resources, ecosystems, special climates or unique geographic zones, and the earth:
Water and soil contamination caused by waste management and disposal practices
Environmental problems associated with transportation by land, air, or water
Geological processes that may impact biosystems or humans
Man-made or naturally occurring geological or hydrological hazards
Environmental problems associated with the recovery of materials from the earth
Environmental problems caused by extraction of minerals, coal, and ores, as well as oil and gas, water and alternative energy sources
Environmental impacts of exploration and recultivation – Environmental impacts of hazardous materials
Management of environmental data and information in data banks and information systems
Dissemination of knowledge on techniques, methods, approaches and experiences to improve and remediate the environment
In pursuit of these topics, the geoscientific disciplines are invited to contribute their knowledge and experience. Major disciplines include: hydrogeology, hydrochemistry, geochemistry, geophysics, engineering geology, remediation science, natural resources management, environmental climatology and biota, environmental geography, soil science and geomicrobiology.