A new approach based on VIKOR and Monte-Carlo algorithms for determining the most efficient enhanced oil recovery methods: EOR screening
Abstract Most of oil reservoirs in the world have faced decrease in production and they are in the second half of their life cycle. Therefore, tertiary and enhanced oil recovery (EOR) techniques are needed for continuous production from these reservoirs. As choosing the most appropriate EOR methods...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Hajinorouz, Maryam [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2023 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s) 2023 |
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| Übergeordnetes Werk: |
Enthalten in: Journal of petroleum exploration and production technology - Berlin : Springer, 2011, 14(2023), 2 vom: 01. Dez., Seite 623-643 |
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| Übergeordnetes Werk: |
volume:14 ; year:2023 ; number:2 ; day:01 ; month:12 ; pages:623-643 |
| Links: |
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| DOI / URN: |
10.1007/s13202-023-01726-y |
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SPR054970776 |
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| 100 | 1 | |a Hajinorouz, Maryam |e verfasserin |4 aut | |
| 245 | 1 | 2 | |a A new approach based on VIKOR and Monte-Carlo algorithms for determining the most efficient enhanced oil recovery methods: EOR screening |
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| 520 | |a Abstract Most of oil reservoirs in the world have faced decrease in production and they are in the second half of their life cycle. Therefore, tertiary and enhanced oil recovery (EOR) techniques are needed for continuous production from these reservoirs. As choosing the most appropriate EOR methods for a reservoir is a challenging task for reservoir engineers, screening of EOR approaches is of high importance before any full field simulation and experiments. Enhanced oil recovery screening is a multiple criteria decision-making (MCDM) problem and hence, a systematic statistical algorithm based on MCDM can be used for this purpose. In this study, for the first time, a new EOR screening method is proposed by using VIKOR and Monte-Carlo algorithms. The approach used a large database of successful EOR projects around the world and was applied to 12 various EOR methods including a wide range of conditions and properties. Pre-processing was performed on the gathered database and then based on reservoir engineering analyses and using a pairwise comparison matrix, initial weights were considered for the parameters in each EOR method. Afterward, these weights were used in the proposed VIKOR MCDM calculation algorithm and the corresponding numerical values of EOR techniques for each reservoir were obtained. Finally, the EOR method with the highest corresponding value was selected as the most suitable method. Results demonstrated that by using the presented approach, a high classification accuracy of 98% was obtained for different cases, which shows the proficiency and robustness of the developed screening algorithm. In addition, the reliability of the developed method was validated using data obtained from 11 oil reservoirs in the southwest of Iran. Also, the results were compared with the results of previous studies and they were in a very good match. The developed approach is less expensive and faster than full field simulation method and can be used as an efficient EOR screening approach for reservoirs with different properties in the world. | ||
| 650 | 4 | |a Enhanced oil recovery |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Screening |7 (dpeaa)DE-He213 | |
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| 650 | 4 | |a Monte-Carlo |7 (dpeaa)DE-He213 | |
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| 700 | 1 | |a Alavi, Seyed Enayatollah |4 aut | |
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10.1007/s13202-023-01726-y doi (DE-627)SPR054970776 (SPR)s13202-023-01726-y-e DE-627 ger DE-627 rakwb eng Hajinorouz, Maryam verfasserin aut A new approach based on VIKOR and Monte-Carlo algorithms for determining the most efficient enhanced oil recovery methods: EOR screening 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract Most of oil reservoirs in the world have faced decrease in production and they are in the second half of their life cycle. Therefore, tertiary and enhanced oil recovery (EOR) techniques are needed for continuous production from these reservoirs. As choosing the most appropriate EOR methods for a reservoir is a challenging task for reservoir engineers, screening of EOR approaches is of high importance before any full field simulation and experiments. Enhanced oil recovery screening is a multiple criteria decision-making (MCDM) problem and hence, a systematic statistical algorithm based on MCDM can be used for this purpose. In this study, for the first time, a new EOR screening method is proposed by using VIKOR and Monte-Carlo algorithms. The approach used a large database of successful EOR projects around the world and was applied to 12 various EOR methods including a wide range of conditions and properties. Pre-processing was performed on the gathered database and then based on reservoir engineering analyses and using a pairwise comparison matrix, initial weights were considered for the parameters in each EOR method. Afterward, these weights were used in the proposed VIKOR MCDM calculation algorithm and the corresponding numerical values of EOR techniques for each reservoir were obtained. Finally, the EOR method with the highest corresponding value was selected as the most suitable method. Results demonstrated that by using the presented approach, a high classification accuracy of 98% was obtained for different cases, which shows the proficiency and robustness of the developed screening algorithm. In addition, the reliability of the developed method was validated using data obtained from 11 oil reservoirs in the southwest of Iran. Also, the results were compared with the results of previous studies and they were in a very good match. The developed approach is less expensive and faster than full field simulation method and can be used as an efficient EOR screening approach for reservoirs with different properties in the world. Enhanced oil recovery (dpeaa)DE-He213 Screening (dpeaa)DE-He213 MCDM (dpeaa)DE-He213 VIKOR (dpeaa)DE-He213 Monte-Carlo (dpeaa)DE-He213 Reservoir engineering (dpeaa)DE-He213 Alavi, Seyed Enayatollah aut Enthalten in Journal of petroleum exploration and production technology Berlin : Springer, 2011 14(2023), 2 vom: 01. Dez., Seite 623-643 (DE-627)647654148 (DE-600)2595714-4 2190-0566 nnns volume:14 year:2023 number:2 day:01 month:12 pages:623-643 https://dx.doi.org/10.1007/s13202-023-01726-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_2129 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2023 2 01 12 623-643 |
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10.1007/s13202-023-01726-y doi (DE-627)SPR054970776 (SPR)s13202-023-01726-y-e DE-627 ger DE-627 rakwb eng Hajinorouz, Maryam verfasserin aut A new approach based on VIKOR and Monte-Carlo algorithms for determining the most efficient enhanced oil recovery methods: EOR screening 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract Most of oil reservoirs in the world have faced decrease in production and they are in the second half of their life cycle. Therefore, tertiary and enhanced oil recovery (EOR) techniques are needed for continuous production from these reservoirs. As choosing the most appropriate EOR methods for a reservoir is a challenging task for reservoir engineers, screening of EOR approaches is of high importance before any full field simulation and experiments. Enhanced oil recovery screening is a multiple criteria decision-making (MCDM) problem and hence, a systematic statistical algorithm based on MCDM can be used for this purpose. In this study, for the first time, a new EOR screening method is proposed by using VIKOR and Monte-Carlo algorithms. The approach used a large database of successful EOR projects around the world and was applied to 12 various EOR methods including a wide range of conditions and properties. Pre-processing was performed on the gathered database and then based on reservoir engineering analyses and using a pairwise comparison matrix, initial weights were considered for the parameters in each EOR method. Afterward, these weights were used in the proposed VIKOR MCDM calculation algorithm and the corresponding numerical values of EOR techniques for each reservoir were obtained. Finally, the EOR method with the highest corresponding value was selected as the most suitable method. Results demonstrated that by using the presented approach, a high classification accuracy of 98% was obtained for different cases, which shows the proficiency and robustness of the developed screening algorithm. In addition, the reliability of the developed method was validated using data obtained from 11 oil reservoirs in the southwest of Iran. Also, the results were compared with the results of previous studies and they were in a very good match. The developed approach is less expensive and faster than full field simulation method and can be used as an efficient EOR screening approach for reservoirs with different properties in the world. Enhanced oil recovery (dpeaa)DE-He213 Screening (dpeaa)DE-He213 MCDM (dpeaa)DE-He213 VIKOR (dpeaa)DE-He213 Monte-Carlo (dpeaa)DE-He213 Reservoir engineering (dpeaa)DE-He213 Alavi, Seyed Enayatollah aut Enthalten in Journal of petroleum exploration and production technology Berlin : Springer, 2011 14(2023), 2 vom: 01. Dez., Seite 623-643 (DE-627)647654148 (DE-600)2595714-4 2190-0566 nnns volume:14 year:2023 number:2 day:01 month:12 pages:623-643 https://dx.doi.org/10.1007/s13202-023-01726-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_2129 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2023 2 01 12 623-643 |
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10.1007/s13202-023-01726-y doi (DE-627)SPR054970776 (SPR)s13202-023-01726-y-e DE-627 ger DE-627 rakwb eng Hajinorouz, Maryam verfasserin aut A new approach based on VIKOR and Monte-Carlo algorithms for determining the most efficient enhanced oil recovery methods: EOR screening 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract Most of oil reservoirs in the world have faced decrease in production and they are in the second half of their life cycle. Therefore, tertiary and enhanced oil recovery (EOR) techniques are needed for continuous production from these reservoirs. As choosing the most appropriate EOR methods for a reservoir is a challenging task for reservoir engineers, screening of EOR approaches is of high importance before any full field simulation and experiments. Enhanced oil recovery screening is a multiple criteria decision-making (MCDM) problem and hence, a systematic statistical algorithm based on MCDM can be used for this purpose. In this study, for the first time, a new EOR screening method is proposed by using VIKOR and Monte-Carlo algorithms. The approach used a large database of successful EOR projects around the world and was applied to 12 various EOR methods including a wide range of conditions and properties. Pre-processing was performed on the gathered database and then based on reservoir engineering analyses and using a pairwise comparison matrix, initial weights were considered for the parameters in each EOR method. Afterward, these weights were used in the proposed VIKOR MCDM calculation algorithm and the corresponding numerical values of EOR techniques for each reservoir were obtained. Finally, the EOR method with the highest corresponding value was selected as the most suitable method. Results demonstrated that by using the presented approach, a high classification accuracy of 98% was obtained for different cases, which shows the proficiency and robustness of the developed screening algorithm. In addition, the reliability of the developed method was validated using data obtained from 11 oil reservoirs in the southwest of Iran. Also, the results were compared with the results of previous studies and they were in a very good match. The developed approach is less expensive and faster than full field simulation method and can be used as an efficient EOR screening approach for reservoirs with different properties in the world. Enhanced oil recovery (dpeaa)DE-He213 Screening (dpeaa)DE-He213 MCDM (dpeaa)DE-He213 VIKOR (dpeaa)DE-He213 Monte-Carlo (dpeaa)DE-He213 Reservoir engineering (dpeaa)DE-He213 Alavi, Seyed Enayatollah aut Enthalten in Journal of petroleum exploration and production technology Berlin : Springer, 2011 14(2023), 2 vom: 01. Dez., Seite 623-643 (DE-627)647654148 (DE-600)2595714-4 2190-0566 nnns volume:14 year:2023 number:2 day:01 month:12 pages:623-643 https://dx.doi.org/10.1007/s13202-023-01726-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_2129 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2023 2 01 12 623-643 |
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10.1007/s13202-023-01726-y doi (DE-627)SPR054970776 (SPR)s13202-023-01726-y-e DE-627 ger DE-627 rakwb eng Hajinorouz, Maryam verfasserin aut A new approach based on VIKOR and Monte-Carlo algorithms for determining the most efficient enhanced oil recovery methods: EOR screening 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract Most of oil reservoirs in the world have faced decrease in production and they are in the second half of their life cycle. Therefore, tertiary and enhanced oil recovery (EOR) techniques are needed for continuous production from these reservoirs. As choosing the most appropriate EOR methods for a reservoir is a challenging task for reservoir engineers, screening of EOR approaches is of high importance before any full field simulation and experiments. Enhanced oil recovery screening is a multiple criteria decision-making (MCDM) problem and hence, a systematic statistical algorithm based on MCDM can be used for this purpose. In this study, for the first time, a new EOR screening method is proposed by using VIKOR and Monte-Carlo algorithms. The approach used a large database of successful EOR projects around the world and was applied to 12 various EOR methods including a wide range of conditions and properties. Pre-processing was performed on the gathered database and then based on reservoir engineering analyses and using a pairwise comparison matrix, initial weights were considered for the parameters in each EOR method. Afterward, these weights were used in the proposed VIKOR MCDM calculation algorithm and the corresponding numerical values of EOR techniques for each reservoir were obtained. Finally, the EOR method with the highest corresponding value was selected as the most suitable method. Results demonstrated that by using the presented approach, a high classification accuracy of 98% was obtained for different cases, which shows the proficiency and robustness of the developed screening algorithm. In addition, the reliability of the developed method was validated using data obtained from 11 oil reservoirs in the southwest of Iran. Also, the results were compared with the results of previous studies and they were in a very good match. The developed approach is less expensive and faster than full field simulation method and can be used as an efficient EOR screening approach for reservoirs with different properties in the world. Enhanced oil recovery (dpeaa)DE-He213 Screening (dpeaa)DE-He213 MCDM (dpeaa)DE-He213 VIKOR (dpeaa)DE-He213 Monte-Carlo (dpeaa)DE-He213 Reservoir engineering (dpeaa)DE-He213 Alavi, Seyed Enayatollah aut Enthalten in Journal of petroleum exploration and production technology Berlin : Springer, 2011 14(2023), 2 vom: 01. Dez., Seite 623-643 (DE-627)647654148 (DE-600)2595714-4 2190-0566 nnns volume:14 year:2023 number:2 day:01 month:12 pages:623-643 https://dx.doi.org/10.1007/s13202-023-01726-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_2129 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2023 2 01 12 623-643 |
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10.1007/s13202-023-01726-y doi (DE-627)SPR054970776 (SPR)s13202-023-01726-y-e DE-627 ger DE-627 rakwb eng Hajinorouz, Maryam verfasserin aut A new approach based on VIKOR and Monte-Carlo algorithms for determining the most efficient enhanced oil recovery methods: EOR screening 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract Most of oil reservoirs in the world have faced decrease in production and they are in the second half of their life cycle. Therefore, tertiary and enhanced oil recovery (EOR) techniques are needed for continuous production from these reservoirs. As choosing the most appropriate EOR methods for a reservoir is a challenging task for reservoir engineers, screening of EOR approaches is of high importance before any full field simulation and experiments. Enhanced oil recovery screening is a multiple criteria decision-making (MCDM) problem and hence, a systematic statistical algorithm based on MCDM can be used for this purpose. In this study, for the first time, a new EOR screening method is proposed by using VIKOR and Monte-Carlo algorithms. The approach used a large database of successful EOR projects around the world and was applied to 12 various EOR methods including a wide range of conditions and properties. Pre-processing was performed on the gathered database and then based on reservoir engineering analyses and using a pairwise comparison matrix, initial weights were considered for the parameters in each EOR method. Afterward, these weights were used in the proposed VIKOR MCDM calculation algorithm and the corresponding numerical values of EOR techniques for each reservoir were obtained. Finally, the EOR method with the highest corresponding value was selected as the most suitable method. Results demonstrated that by using the presented approach, a high classification accuracy of 98% was obtained for different cases, which shows the proficiency and robustness of the developed screening algorithm. In addition, the reliability of the developed method was validated using data obtained from 11 oil reservoirs in the southwest of Iran. Also, the results were compared with the results of previous studies and they were in a very good match. The developed approach is less expensive and faster than full field simulation method and can be used as an efficient EOR screening approach for reservoirs with different properties in the world. Enhanced oil recovery (dpeaa)DE-He213 Screening (dpeaa)DE-He213 MCDM (dpeaa)DE-He213 VIKOR (dpeaa)DE-He213 Monte-Carlo (dpeaa)DE-He213 Reservoir engineering (dpeaa)DE-He213 Alavi, Seyed Enayatollah aut Enthalten in Journal of petroleum exploration and production technology Berlin : Springer, 2011 14(2023), 2 vom: 01. Dez., Seite 623-643 (DE-627)647654148 (DE-600)2595714-4 2190-0566 nnns volume:14 year:2023 number:2 day:01 month:12 pages:623-643 https://dx.doi.org/10.1007/s13202-023-01726-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_2129 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2023 2 01 12 623-643 |
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English |
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A new approach based on VIKOR and Monte-Carlo algorithms for determining the most efficient enhanced oil recovery methods: EOR screening |
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Abstract Most of oil reservoirs in the world have faced decrease in production and they are in the second half of their life cycle. Therefore, tertiary and enhanced oil recovery (EOR) techniques are needed for continuous production from these reservoirs. As choosing the most appropriate EOR methods for a reservoir is a challenging task for reservoir engineers, screening of EOR approaches is of high importance before any full field simulation and experiments. Enhanced oil recovery screening is a multiple criteria decision-making (MCDM) problem and hence, a systematic statistical algorithm based on MCDM can be used for this purpose. In this study, for the first time, a new EOR screening method is proposed by using VIKOR and Monte-Carlo algorithms. The approach used a large database of successful EOR projects around the world and was applied to 12 various EOR methods including a wide range of conditions and properties. Pre-processing was performed on the gathered database and then based on reservoir engineering analyses and using a pairwise comparison matrix, initial weights were considered for the parameters in each EOR method. Afterward, these weights were used in the proposed VIKOR MCDM calculation algorithm and the corresponding numerical values of EOR techniques for each reservoir were obtained. Finally, the EOR method with the highest corresponding value was selected as the most suitable method. Results demonstrated that by using the presented approach, a high classification accuracy of 98% was obtained for different cases, which shows the proficiency and robustness of the developed screening algorithm. In addition, the reliability of the developed method was validated using data obtained from 11 oil reservoirs in the southwest of Iran. Also, the results were compared with the results of previous studies and they were in a very good match. The developed approach is less expensive and faster than full field simulation method and can be used as an efficient EOR screening approach for reservoirs with different properties in the world. © The Author(s) 2023 |
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Abstract Most of oil reservoirs in the world have faced decrease in production and they are in the second half of their life cycle. Therefore, tertiary and enhanced oil recovery (EOR) techniques are needed for continuous production from these reservoirs. As choosing the most appropriate EOR methods for a reservoir is a challenging task for reservoir engineers, screening of EOR approaches is of high importance before any full field simulation and experiments. Enhanced oil recovery screening is a multiple criteria decision-making (MCDM) problem and hence, a systematic statistical algorithm based on MCDM can be used for this purpose. In this study, for the first time, a new EOR screening method is proposed by using VIKOR and Monte-Carlo algorithms. The approach used a large database of successful EOR projects around the world and was applied to 12 various EOR methods including a wide range of conditions and properties. Pre-processing was performed on the gathered database and then based on reservoir engineering analyses and using a pairwise comparison matrix, initial weights were considered for the parameters in each EOR method. Afterward, these weights were used in the proposed VIKOR MCDM calculation algorithm and the corresponding numerical values of EOR techniques for each reservoir were obtained. Finally, the EOR method with the highest corresponding value was selected as the most suitable method. Results demonstrated that by using the presented approach, a high classification accuracy of 98% was obtained for different cases, which shows the proficiency and robustness of the developed screening algorithm. In addition, the reliability of the developed method was validated using data obtained from 11 oil reservoirs in the southwest of Iran. Also, the results were compared with the results of previous studies and they were in a very good match. The developed approach is less expensive and faster than full field simulation method and can be used as an efficient EOR screening approach for reservoirs with different properties in the world. © The Author(s) 2023 |
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Abstract Most of oil reservoirs in the world have faced decrease in production and they are in the second half of their life cycle. Therefore, tertiary and enhanced oil recovery (EOR) techniques are needed for continuous production from these reservoirs. As choosing the most appropriate EOR methods for a reservoir is a challenging task for reservoir engineers, screening of EOR approaches is of high importance before any full field simulation and experiments. Enhanced oil recovery screening is a multiple criteria decision-making (MCDM) problem and hence, a systematic statistical algorithm based on MCDM can be used for this purpose. In this study, for the first time, a new EOR screening method is proposed by using VIKOR and Monte-Carlo algorithms. The approach used a large database of successful EOR projects around the world and was applied to 12 various EOR methods including a wide range of conditions and properties. Pre-processing was performed on the gathered database and then based on reservoir engineering analyses and using a pairwise comparison matrix, initial weights were considered for the parameters in each EOR method. Afterward, these weights were used in the proposed VIKOR MCDM calculation algorithm and the corresponding numerical values of EOR techniques for each reservoir were obtained. Finally, the EOR method with the highest corresponding value was selected as the most suitable method. Results demonstrated that by using the presented approach, a high classification accuracy of 98% was obtained for different cases, which shows the proficiency and robustness of the developed screening algorithm. In addition, the reliability of the developed method was validated using data obtained from 11 oil reservoirs in the southwest of Iran. Also, the results were compared with the results of previous studies and they were in a very good match. The developed approach is less expensive and faster than full field simulation method and can be used as an efficient EOR screening approach for reservoirs with different properties in the world. © The Author(s) 2023 |
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Therefore, tertiary and enhanced oil recovery (EOR) techniques are needed for continuous production from these reservoirs. As choosing the most appropriate EOR methods for a reservoir is a challenging task for reservoir engineers, screening of EOR approaches is of high importance before any full field simulation and experiments. Enhanced oil recovery screening is a multiple criteria decision-making (MCDM) problem and hence, a systematic statistical algorithm based on MCDM can be used for this purpose. In this study, for the first time, a new EOR screening method is proposed by using VIKOR and Monte-Carlo algorithms. The approach used a large database of successful EOR projects around the world and was applied to 12 various EOR methods including a wide range of conditions and properties. Pre-processing was performed on the gathered database and then based on reservoir engineering analyses and using a pairwise comparison matrix, initial weights were considered for the parameters in each EOR method. Afterward, these weights were used in the proposed VIKOR MCDM calculation algorithm and the corresponding numerical values of EOR techniques for each reservoir were obtained. Finally, the EOR method with the highest corresponding value was selected as the most suitable method. Results demonstrated that by using the presented approach, a high classification accuracy of 98% was obtained for different cases, which shows the proficiency and robustness of the developed screening algorithm. In addition, the reliability of the developed method was validated using data obtained from 11 oil reservoirs in the southwest of Iran. Also, the results were compared with the results of previous studies and they were in a very good match. The developed approach is less expensive and faster than full field simulation method and can be used as an efficient EOR screening approach for reservoirs with different properties in the world.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Enhanced oil recovery</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Screening</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">MCDM</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">VIKOR</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Monte-Carlo</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Reservoir engineering</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Alavi, Seyed Enayatollah</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Journal of petroleum exploration and production technology</subfield><subfield code="d">Berlin : Springer, 2011</subfield><subfield code="g">14(2023), 2 vom: 01. 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