Software for CO[sub.2] Storage in Natural Gas Reservoirs
The paper presents a simulation-based approach for optimizing CO[sub.2] injection into depleted gas reservoirs, with the goal of enhancing underground CO[sub.2] storage. The research employs a two-dimensional dynamic reservoir model, developed using Darcy’s law, to describe gas flow in a pressure-ho...
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Veröffentlicht in: | Energies (Basel) 2024-10, Vol.17 (19) |
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container_title | Energies (Basel) |
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creator | Eparu, Cristian Nicolae Suditu, Silvian Doukeh, Rami Stoica, Doru Bogdan Ghetiu, Iuliana Veronica Prundurel, Alina Stan, Ioana Gabriela Dumitrache, Liviu |
description | The paper presents a simulation-based approach for optimizing CO[sub.2] injection into depleted gas reservoirs, with the goal of enhancing underground CO[sub.2] storage. The research employs a two-dimensional dynamic reservoir model, developed using Darcy’s law, to describe gas flow in a pressure-homogeneous porous medium, along with real gas equations. The model integrates the Du Fort–Frenkel and finite-difference methods to accurately simulate the behavior of CO[sub.2] during injection and storage. Real data from an operational gas storage facility were used to calibrate the model. CO2sim v1 software, specifically developed for this purpose, simulates CO[sub.2] injection cycles and quiescence phases, enabling the optimization of storage capacity and energy efficiency. The reservoir model, based on the engineering of the geological structure, is discretized into approximately 16,000 cells and solved using the finite-difference method, allowing for rapid simulation of CO[sub.2] injection and quiescence processes. The average computation time for a 150-day cycle is approximately 5 min. Simulation results indicate that increasing the number of injection wells and carefully controlling the injection rates significantly improves the distribution of CO[sub.2] within the reservoir, thereby enhancing storage efficiency. Additionally, appropriate well placement and prolonged quiescence periods lead to better CO[sub.2] dispersion, increasing the storage potential while reducing energy costs. The study concludes that further development of the software, along with comprehensive technical and economic assessments, is required to fully optimize CO[sub.2] storage on a commercial scale. |
doi_str_mv | 10.3390/en17194984 |
format | Article |
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The research employs a two-dimensional dynamic reservoir model, developed using Darcy’s law, to describe gas flow in a pressure-homogeneous porous medium, along with real gas equations. The model integrates the Du Fort–Frenkel and finite-difference methods to accurately simulate the behavior of CO[sub.2] during injection and storage. Real data from an operational gas storage facility were used to calibrate the model. CO2sim v1 software, specifically developed for this purpose, simulates CO[sub.2] injection cycles and quiescence phases, enabling the optimization of storage capacity and energy efficiency. The reservoir model, based on the engineering of the geological structure, is discretized into approximately 16,000 cells and solved using the finite-difference method, allowing for rapid simulation of CO[sub.2] injection and quiescence processes. The average computation time for a 150-day cycle is approximately 5 min. Simulation results indicate that increasing the number of injection wells and carefully controlling the injection rates significantly improves the distribution of CO[sub.2] within the reservoir, thereby enhancing storage efficiency. Additionally, appropriate well placement and prolonged quiescence periods lead to better CO[sub.2] dispersion, increasing the storage potential while reducing energy costs. The study concludes that further development of the software, along with comprehensive technical and economic assessments, is required to fully optimize CO[sub.2] storage on a commercial scale.</description><identifier>ISSN: 1996-1073</identifier><identifier>EISSN: 1996-1073</identifier><identifier>DOI: 10.3390/en17194984</identifier><language>eng</language><publisher>MDPI AG</publisher><subject>Air quality management ; Carbon sequestration ; Gas fields ; Methods</subject><ispartof>Energies (Basel), 2024-10, Vol.17 (19)</ispartof><rights>COPYRIGHT 2024 MDPI AG</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,861,27905,27906</link.rule.ids></links><search><creatorcontrib>Eparu, Cristian Nicolae</creatorcontrib><creatorcontrib>Suditu, Silvian</creatorcontrib><creatorcontrib>Doukeh, Rami</creatorcontrib><creatorcontrib>Stoica, Doru Bogdan</creatorcontrib><creatorcontrib>Ghetiu, Iuliana Veronica</creatorcontrib><creatorcontrib>Prundurel, Alina</creatorcontrib><creatorcontrib>Stan, Ioana Gabriela</creatorcontrib><creatorcontrib>Dumitrache, Liviu</creatorcontrib><title>Software for CO[sub.2] Storage in Natural Gas Reservoirs</title><title>Energies (Basel)</title><description>The paper presents a simulation-based approach for optimizing CO[sub.2] injection into depleted gas reservoirs, with the goal of enhancing underground CO[sub.2] storage. The research employs a two-dimensional dynamic reservoir model, developed using Darcy’s law, to describe gas flow in a pressure-homogeneous porous medium, along with real gas equations. The model integrates the Du Fort–Frenkel and finite-difference methods to accurately simulate the behavior of CO[sub.2] during injection and storage. Real data from an operational gas storage facility were used to calibrate the model. CO2sim v1 software, specifically developed for this purpose, simulates CO[sub.2] injection cycles and quiescence phases, enabling the optimization of storage capacity and energy efficiency. The reservoir model, based on the engineering of the geological structure, is discretized into approximately 16,000 cells and solved using the finite-difference method, allowing for rapid simulation of CO[sub.2] injection and quiescence processes. The average computation time for a 150-day cycle is approximately 5 min. Simulation results indicate that increasing the number of injection wells and carefully controlling the injection rates significantly improves the distribution of CO[sub.2] within the reservoir, thereby enhancing storage efficiency. Additionally, appropriate well placement and prolonged quiescence periods lead to better CO[sub.2] dispersion, increasing the storage potential while reducing energy costs. 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The research employs a two-dimensional dynamic reservoir model, developed using Darcy’s law, to describe gas flow in a pressure-homogeneous porous medium, along with real gas equations. The model integrates the Du Fort–Frenkel and finite-difference methods to accurately simulate the behavior of CO[sub.2] during injection and storage. Real data from an operational gas storage facility were used to calibrate the model. CO2sim v1 software, specifically developed for this purpose, simulates CO[sub.2] injection cycles and quiescence phases, enabling the optimization of storage capacity and energy efficiency. The reservoir model, based on the engineering of the geological structure, is discretized into approximately 16,000 cells and solved using the finite-difference method, allowing for rapid simulation of CO[sub.2] injection and quiescence processes. The average computation time for a 150-day cycle is approximately 5 min. Simulation results indicate that increasing the number of injection wells and carefully controlling the injection rates significantly improves the distribution of CO[sub.2] within the reservoir, thereby enhancing storage efficiency. Additionally, appropriate well placement and prolonged quiescence periods lead to better CO[sub.2] dispersion, increasing the storage potential while reducing energy costs. The study concludes that further development of the software, along with comprehensive technical and economic assessments, is required to fully optimize CO[sub.2] storage on a commercial scale.</abstract><pub>MDPI AG</pub><doi>10.3390/en17194984</doi></addata></record> |
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source | DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; MDPI - Multidisciplinary Digital Publishing Institute |
subjects | Air quality management Carbon sequestration Gas fields Methods |
title | Software for CO[sub.2] Storage in Natural Gas Reservoirs |
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