Integration of geophysical, core and production data to evaluate gas reservoir performance: A study from Saldanadi field
Abstract The present study offers a comprehensive, integrated assessment for characterising the Saldanadi gas reservoir, understanding its dynamic behaviour, and assessing its future development potential through simulation. The objective of this study is to develop an integrated 3D reservoir model...
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| Autor*in: |
Rahman, Md Aliur [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2024 |
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| Schlagwörter: |
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| Anmerkung: |
© Indian Academy of Sciences 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Übergeordnetes Werk: |
Enthalten in: Journal of earth system science - Bangalore : Indian Acad. of Sciences, 1980, 133(2024), 1 vom: 27. Feb. |
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| Übergeordnetes Werk: |
volume:133 ; year:2024 ; number:1 ; day:27 ; month:02 |
| Links: |
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| DOI / URN: |
10.1007/s12040-024-02258-7 |
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| Katalog-ID: |
SPR054934656 |
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| 520 | |a Abstract The present study offers a comprehensive, integrated assessment for characterising the Saldanadi gas reservoir, understanding its dynamic behaviour, and assessing its future development potential through simulation. The objective of this study is to develop an integrated 3D reservoir model and validate the static model through dynamic simulation. The Saldanadi reservoir has presented unique challenges from the outset, given its heterogeneity in petrophysical parameter distributions, encompassing the porosity, permeability, net-to-gross ratio, fluid saturation, and gas sand thickness. As a result, the field must be reassessed, and a reliable reservoir model must be developed for production forecasting. Utilising seismic data, wireline logs, drill stem tests (DSTs), and core data, we leveraged Petrel software to distribute reservoir parameters throughout the field, culminating in a 3D reservoir static model that was subsequently validated using the Eclipse reservoir simulator, with historical production data serving as a benchmark. Our updated reservoir model estimated gas initially in place at 149.63 × $ 10^{8} $ $ sm^{3} $, considering four potential gas sands. The historical production profile was reviewed to determine the reservoir's performance and dynamic characteristics, and forecasts were made accordingly. Our study suggests that the validated model will serve as the guiding constraint for future development strategies and the pursuit of an optimal recovery factor. | ||
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10.1007/s12040-024-02258-7 doi (DE-627)SPR054934656 (SPR)s12040-024-02258-7-e DE-627 ger DE-627 rakwb eng Rahman, Md Aliur verfasserin (orcid)0009-0002-3424-8170 aut Integration of geophysical, core and production data to evaluate gas reservoir performance: A study from Saldanadi field 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Indian Academy of Sciences 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The present study offers a comprehensive, integrated assessment for characterising the Saldanadi gas reservoir, understanding its dynamic behaviour, and assessing its future development potential through simulation. The objective of this study is to develop an integrated 3D reservoir model and validate the static model through dynamic simulation. The Saldanadi reservoir has presented unique challenges from the outset, given its heterogeneity in petrophysical parameter distributions, encompassing the porosity, permeability, net-to-gross ratio, fluid saturation, and gas sand thickness. As a result, the field must be reassessed, and a reliable reservoir model must be developed for production forecasting. Utilising seismic data, wireline logs, drill stem tests (DSTs), and core data, we leveraged Petrel software to distribute reservoir parameters throughout the field, culminating in a 3D reservoir static model that was subsequently validated using the Eclipse reservoir simulator, with historical production data serving as a benchmark. Our updated reservoir model estimated gas initially in place at 149.63 × $ 10^{8} $ $ sm^{3} $, considering four potential gas sands. The historical production profile was reviewed to determine the reservoir's performance and dynamic characteristics, and forecasts were made accordingly. Our study suggests that the validated model will serve as the guiding constraint for future development strategies and the pursuit of an optimal recovery factor. Integrated reservoir modelling (dpeaa)DE-He213 reservoir heterogeneity (dpeaa)DE-He213 dynamic simulation (dpeaa)DE-He213 reservoir model validation (dpeaa)DE-He213 historical matching (dpeaa)DE-He213 Islam, Md Amirul aut Kabir, Jahangir aut Ahmed, A S Daiyan aut Zico, M Nur Alam aut Khan, Md Yamin aut Enthalten in Journal of earth system science Bangalore : Indian Acad. of Sciences, 1980 133(2024), 1 vom: 27. Feb. (DE-627)349877327 (DE-600)2081712-5 0973-774X nnns volume:133 year:2024 number:1 day:27 month:02 https://dx.doi.org/10.1007/s12040-024-02258-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 133 2024 1 27 02 |
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10.1007/s12040-024-02258-7 doi (DE-627)SPR054934656 (SPR)s12040-024-02258-7-e DE-627 ger DE-627 rakwb eng Rahman, Md Aliur verfasserin (orcid)0009-0002-3424-8170 aut Integration of geophysical, core and production data to evaluate gas reservoir performance: A study from Saldanadi field 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Indian Academy of Sciences 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The present study offers a comprehensive, integrated assessment for characterising the Saldanadi gas reservoir, understanding its dynamic behaviour, and assessing its future development potential through simulation. The objective of this study is to develop an integrated 3D reservoir model and validate the static model through dynamic simulation. The Saldanadi reservoir has presented unique challenges from the outset, given its heterogeneity in petrophysical parameter distributions, encompassing the porosity, permeability, net-to-gross ratio, fluid saturation, and gas sand thickness. As a result, the field must be reassessed, and a reliable reservoir model must be developed for production forecasting. Utilising seismic data, wireline logs, drill stem tests (DSTs), and core data, we leveraged Petrel software to distribute reservoir parameters throughout the field, culminating in a 3D reservoir static model that was subsequently validated using the Eclipse reservoir simulator, with historical production data serving as a benchmark. Our updated reservoir model estimated gas initially in place at 149.63 × $ 10^{8} $ $ sm^{3} $, considering four potential gas sands. The historical production profile was reviewed to determine the reservoir's performance and dynamic characteristics, and forecasts were made accordingly. Our study suggests that the validated model will serve as the guiding constraint for future development strategies and the pursuit of an optimal recovery factor. Integrated reservoir modelling (dpeaa)DE-He213 reservoir heterogeneity (dpeaa)DE-He213 dynamic simulation (dpeaa)DE-He213 reservoir model validation (dpeaa)DE-He213 historical matching (dpeaa)DE-He213 Islam, Md Amirul aut Kabir, Jahangir aut Ahmed, A S Daiyan aut Zico, M Nur Alam aut Khan, Md Yamin aut Enthalten in Journal of earth system science Bangalore : Indian Acad. of Sciences, 1980 133(2024), 1 vom: 27. Feb. (DE-627)349877327 (DE-600)2081712-5 0973-774X nnns volume:133 year:2024 number:1 day:27 month:02 https://dx.doi.org/10.1007/s12040-024-02258-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 133 2024 1 27 02 |
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10.1007/s12040-024-02258-7 doi (DE-627)SPR054934656 (SPR)s12040-024-02258-7-e DE-627 ger DE-627 rakwb eng Rahman, Md Aliur verfasserin (orcid)0009-0002-3424-8170 aut Integration of geophysical, core and production data to evaluate gas reservoir performance: A study from Saldanadi field 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Indian Academy of Sciences 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The present study offers a comprehensive, integrated assessment for characterising the Saldanadi gas reservoir, understanding its dynamic behaviour, and assessing its future development potential through simulation. The objective of this study is to develop an integrated 3D reservoir model and validate the static model through dynamic simulation. The Saldanadi reservoir has presented unique challenges from the outset, given its heterogeneity in petrophysical parameter distributions, encompassing the porosity, permeability, net-to-gross ratio, fluid saturation, and gas sand thickness. As a result, the field must be reassessed, and a reliable reservoir model must be developed for production forecasting. Utilising seismic data, wireline logs, drill stem tests (DSTs), and core data, we leveraged Petrel software to distribute reservoir parameters throughout the field, culminating in a 3D reservoir static model that was subsequently validated using the Eclipse reservoir simulator, with historical production data serving as a benchmark. Our updated reservoir model estimated gas initially in place at 149.63 × $ 10^{8} $ $ sm^{3} $, considering four potential gas sands. The historical production profile was reviewed to determine the reservoir's performance and dynamic characteristics, and forecasts were made accordingly. Our study suggests that the validated model will serve as the guiding constraint for future development strategies and the pursuit of an optimal recovery factor. Integrated reservoir modelling (dpeaa)DE-He213 reservoir heterogeneity (dpeaa)DE-He213 dynamic simulation (dpeaa)DE-He213 reservoir model validation (dpeaa)DE-He213 historical matching (dpeaa)DE-He213 Islam, Md Amirul aut Kabir, Jahangir aut Ahmed, A S Daiyan aut Zico, M Nur Alam aut Khan, Md Yamin aut Enthalten in Journal of earth system science Bangalore : Indian Acad. of Sciences, 1980 133(2024), 1 vom: 27. Feb. (DE-627)349877327 (DE-600)2081712-5 0973-774X nnns volume:133 year:2024 number:1 day:27 month:02 https://dx.doi.org/10.1007/s12040-024-02258-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 133 2024 1 27 02 |
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10.1007/s12040-024-02258-7 doi (DE-627)SPR054934656 (SPR)s12040-024-02258-7-e DE-627 ger DE-627 rakwb eng Rahman, Md Aliur verfasserin (orcid)0009-0002-3424-8170 aut Integration of geophysical, core and production data to evaluate gas reservoir performance: A study from Saldanadi field 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Indian Academy of Sciences 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The present study offers a comprehensive, integrated assessment for characterising the Saldanadi gas reservoir, understanding its dynamic behaviour, and assessing its future development potential through simulation. The objective of this study is to develop an integrated 3D reservoir model and validate the static model through dynamic simulation. The Saldanadi reservoir has presented unique challenges from the outset, given its heterogeneity in petrophysical parameter distributions, encompassing the porosity, permeability, net-to-gross ratio, fluid saturation, and gas sand thickness. As a result, the field must be reassessed, and a reliable reservoir model must be developed for production forecasting. Utilising seismic data, wireline logs, drill stem tests (DSTs), and core data, we leveraged Petrel software to distribute reservoir parameters throughout the field, culminating in a 3D reservoir static model that was subsequently validated using the Eclipse reservoir simulator, with historical production data serving as a benchmark. Our updated reservoir model estimated gas initially in place at 149.63 × $ 10^{8} $ $ sm^{3} $, considering four potential gas sands. The historical production profile was reviewed to determine the reservoir's performance and dynamic characteristics, and forecasts were made accordingly. Our study suggests that the validated model will serve as the guiding constraint for future development strategies and the pursuit of an optimal recovery factor. Integrated reservoir modelling (dpeaa)DE-He213 reservoir heterogeneity (dpeaa)DE-He213 dynamic simulation (dpeaa)DE-He213 reservoir model validation (dpeaa)DE-He213 historical matching (dpeaa)DE-He213 Islam, Md Amirul aut Kabir, Jahangir aut Ahmed, A S Daiyan aut Zico, M Nur Alam aut Khan, Md Yamin aut Enthalten in Journal of earth system science Bangalore : Indian Acad. of Sciences, 1980 133(2024), 1 vom: 27. Feb. (DE-627)349877327 (DE-600)2081712-5 0973-774X nnns volume:133 year:2024 number:1 day:27 month:02 https://dx.doi.org/10.1007/s12040-024-02258-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 133 2024 1 27 02 |
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10.1007/s12040-024-02258-7 doi (DE-627)SPR054934656 (SPR)s12040-024-02258-7-e DE-627 ger DE-627 rakwb eng Rahman, Md Aliur verfasserin (orcid)0009-0002-3424-8170 aut Integration of geophysical, core and production data to evaluate gas reservoir performance: A study from Saldanadi field 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Indian Academy of Sciences 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract The present study offers a comprehensive, integrated assessment for characterising the Saldanadi gas reservoir, understanding its dynamic behaviour, and assessing its future development potential through simulation. The objective of this study is to develop an integrated 3D reservoir model and validate the static model through dynamic simulation. The Saldanadi reservoir has presented unique challenges from the outset, given its heterogeneity in petrophysical parameter distributions, encompassing the porosity, permeability, net-to-gross ratio, fluid saturation, and gas sand thickness. As a result, the field must be reassessed, and a reliable reservoir model must be developed for production forecasting. Utilising seismic data, wireline logs, drill stem tests (DSTs), and core data, we leveraged Petrel software to distribute reservoir parameters throughout the field, culminating in a 3D reservoir static model that was subsequently validated using the Eclipse reservoir simulator, with historical production data serving as a benchmark. Our updated reservoir model estimated gas initially in place at 149.63 × $ 10^{8} $ $ sm^{3} $, considering four potential gas sands. The historical production profile was reviewed to determine the reservoir's performance and dynamic characteristics, and forecasts were made accordingly. Our study suggests that the validated model will serve as the guiding constraint for future development strategies and the pursuit of an optimal recovery factor. Integrated reservoir modelling (dpeaa)DE-He213 reservoir heterogeneity (dpeaa)DE-He213 dynamic simulation (dpeaa)DE-He213 reservoir model validation (dpeaa)DE-He213 historical matching (dpeaa)DE-He213 Islam, Md Amirul aut Kabir, Jahangir aut Ahmed, A S Daiyan aut Zico, M Nur Alam aut Khan, Md Yamin aut Enthalten in Journal of earth system science Bangalore : Indian Acad. of Sciences, 1980 133(2024), 1 vom: 27. Feb. (DE-627)349877327 (DE-600)2081712-5 0973-774X nnns volume:133 year:2024 number:1 day:27 month:02 https://dx.doi.org/10.1007/s12040-024-02258-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 133 2024 1 27 02 |
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Rahman, Md Aliur @@aut@@ Islam, Md Amirul @@aut@@ Kabir, Jahangir @@aut@@ Ahmed, A S Daiyan @@aut@@ Zico, M Nur Alam @@aut@@ Khan, Md Yamin @@aut@@ |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">SPR054934656</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240228064654.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">240228s2024 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s12040-024-02258-7</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR054934656</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s12040-024-02258-7-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Rahman, Md Aliur</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0009-0002-3424-8170</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Integration of geophysical, core and production data to evaluate gas reservoir performance: A study from Saldanadi field</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2024</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Indian Academy of Sciences 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract The present study offers a comprehensive, integrated assessment for characterising the Saldanadi gas reservoir, understanding its dynamic behaviour, and assessing its future development potential through simulation. The objective of this study is to develop an integrated 3D reservoir model and validate the static model through dynamic simulation. The Saldanadi reservoir has presented unique challenges from the outset, given its heterogeneity in petrophysical parameter distributions, encompassing the porosity, permeability, net-to-gross ratio, fluid saturation, and gas sand thickness. As a result, the field must be reassessed, and a reliable reservoir model must be developed for production forecasting. Utilising seismic data, wireline logs, drill stem tests (DSTs), and core data, we leveraged Petrel software to distribute reservoir parameters throughout the field, culminating in a 3D reservoir static model that was subsequently validated using the Eclipse reservoir simulator, with historical production data serving as a benchmark. Our updated reservoir model estimated gas initially in place at 149.63 × $ 10^{8} $ $ sm^{3} $, considering four potential gas sands. The historical production profile was reviewed to determine the reservoir's performance and dynamic characteristics, and forecasts were made accordingly. 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Rahman, Md Aliur |
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Integration of geophysical, core and production data to evaluate gas reservoir performance: A study from Saldanadi field Integrated reservoir modelling (dpeaa)DE-He213 reservoir heterogeneity (dpeaa)DE-He213 dynamic simulation (dpeaa)DE-He213 reservoir model validation (dpeaa)DE-He213 historical matching (dpeaa)DE-He213 |
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integration of geophysical, core and production data to evaluate gas reservoir performance: a study from saldanadi field |
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Integration of geophysical, core and production data to evaluate gas reservoir performance: A study from Saldanadi field |
| abstract |
Abstract The present study offers a comprehensive, integrated assessment for characterising the Saldanadi gas reservoir, understanding its dynamic behaviour, and assessing its future development potential through simulation. The objective of this study is to develop an integrated 3D reservoir model and validate the static model through dynamic simulation. The Saldanadi reservoir has presented unique challenges from the outset, given its heterogeneity in petrophysical parameter distributions, encompassing the porosity, permeability, net-to-gross ratio, fluid saturation, and gas sand thickness. As a result, the field must be reassessed, and a reliable reservoir model must be developed for production forecasting. Utilising seismic data, wireline logs, drill stem tests (DSTs), and core data, we leveraged Petrel software to distribute reservoir parameters throughout the field, culminating in a 3D reservoir static model that was subsequently validated using the Eclipse reservoir simulator, with historical production data serving as a benchmark. Our updated reservoir model estimated gas initially in place at 149.63 × $ 10^{8} $ $ sm^{3} $, considering four potential gas sands. The historical production profile was reviewed to determine the reservoir's performance and dynamic characteristics, and forecasts were made accordingly. Our study suggests that the validated model will serve as the guiding constraint for future development strategies and the pursuit of an optimal recovery factor. © Indian Academy of Sciences 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstractGer |
Abstract The present study offers a comprehensive, integrated assessment for characterising the Saldanadi gas reservoir, understanding its dynamic behaviour, and assessing its future development potential through simulation. The objective of this study is to develop an integrated 3D reservoir model and validate the static model through dynamic simulation. The Saldanadi reservoir has presented unique challenges from the outset, given its heterogeneity in petrophysical parameter distributions, encompassing the porosity, permeability, net-to-gross ratio, fluid saturation, and gas sand thickness. As a result, the field must be reassessed, and a reliable reservoir model must be developed for production forecasting. Utilising seismic data, wireline logs, drill stem tests (DSTs), and core data, we leveraged Petrel software to distribute reservoir parameters throughout the field, culminating in a 3D reservoir static model that was subsequently validated using the Eclipse reservoir simulator, with historical production data serving as a benchmark. Our updated reservoir model estimated gas initially in place at 149.63 × $ 10^{8} $ $ sm^{3} $, considering four potential gas sands. The historical production profile was reviewed to determine the reservoir's performance and dynamic characteristics, and forecasts were made accordingly. Our study suggests that the validated model will serve as the guiding constraint for future development strategies and the pursuit of an optimal recovery factor. © Indian Academy of Sciences 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstract_unstemmed |
Abstract The present study offers a comprehensive, integrated assessment for characterising the Saldanadi gas reservoir, understanding its dynamic behaviour, and assessing its future development potential through simulation. The objective of this study is to develop an integrated 3D reservoir model and validate the static model through dynamic simulation. The Saldanadi reservoir has presented unique challenges from the outset, given its heterogeneity in petrophysical parameter distributions, encompassing the porosity, permeability, net-to-gross ratio, fluid saturation, and gas sand thickness. As a result, the field must be reassessed, and a reliable reservoir model must be developed for production forecasting. Utilising seismic data, wireline logs, drill stem tests (DSTs), and core data, we leveraged Petrel software to distribute reservoir parameters throughout the field, culminating in a 3D reservoir static model that was subsequently validated using the Eclipse reservoir simulator, with historical production data serving as a benchmark. Our updated reservoir model estimated gas initially in place at 149.63 × $ 10^{8} $ $ sm^{3} $, considering four potential gas sands. The historical production profile was reviewed to determine the reservoir's performance and dynamic characteristics, and forecasts were made accordingly. Our study suggests that the validated model will serve as the guiding constraint for future development strategies and the pursuit of an optimal recovery factor. © Indian Academy of Sciences 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| title_short |
Integration of geophysical, core and production data to evaluate gas reservoir performance: A study from Saldanadi field |
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https://dx.doi.org/10.1007/s12040-024-02258-7 |
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Islam, Md Amirul Kabir, Jahangir Ahmed, A S Daiyan Zico, M Nur Alam Khan, Md Yamin |
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Islam, Md Amirul Kabir, Jahangir Ahmed, A S Daiyan Zico, M Nur Alam Khan, Md Yamin |
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10.1007/s12040-024-02258-7 |
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| score |
7.400337 |