Data-driven approach for evaluation of formation damage during the injection process
Abstract Waterflooding is among the most common oil recovery methods which is implemented in the most of oil-producing countries. The goal of a waterflooding operation is pushing the low-pressure remained oil of reservoir toward the producer wells to enhance the oil recovery factor. One of the impor...
Ausführliche Beschreibung
Autor*in: |
Shabani, Ali [verfasserIn] Jahangiri, Hamid Reza [verfasserIn] Shahrabadi, Abbas [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
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2019 |
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Übergeordnetes Werk: |
Enthalten in: Journal of petroleum exploration and production technology - Berlin : Springer, 2011, 10(2019), 2 vom: 24. Aug., Seite 699-710 |
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Übergeordnetes Werk: |
volume:10 ; year:2019 ; number:2 ; day:24 ; month:08 ; pages:699-710 |
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DOI / URN: |
10.1007/s13202-019-00764-9 |
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Katalog-ID: |
SPR039035077 |
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520 | |a Abstract Waterflooding is among the most common oil recovery methods which is implemented in the most of oil-producing countries. The goal of a waterflooding operation is pushing the low-pressure remained oil of reservoir toward the producer wells to enhance the oil recovery factor. One of the important objects of a waterflooding operation management is understanding the quality of connection between the injectors and the producers of the reservoir. Capacitance resistance model (CRM) is a data-driven method which can estimate the production rate of each producer and the connectivity factor between each pair of wells, by history matching of the injection and production data. The estimated connectivity factor can be used for understanding the quality of connection between the wells. In the waterflooding operation, the injected water always has the potential of causing formation damage by invasion of foreign particles deep bed filtration (DBF), mobilization of indigenous particles (fines migration), scale formation, etc. The formation damage can weaken the quality of connection (connectivity factor), between the injectors and producers of the field, increasing the skin of injection well. In this paper, DBF is used for creation of formation damage in synthetic reservoir models. Then, it has been tried to find the existence and amount of formation damage by evaluating the connectivity factor of CRM. Finally, the results of that have been used for prediction of skin variation in a real case by using the connectivity factor of CRM. | ||
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700 | 1 | |a Jahangiri, Hamid Reza |e verfasserin |4 aut | |
700 | 1 | |a Shahrabadi, Abbas |e verfasserin |4 aut | |
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10.1007/s13202-019-00764-9 doi (DE-627)SPR039035077 (SPR)s13202-019-00764-9-e DE-627 ger DE-627 rakwb eng 540 ASE Shabani, Ali verfasserin aut Data-driven approach for evaluation of formation damage during the injection process 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Waterflooding is among the most common oil recovery methods which is implemented in the most of oil-producing countries. The goal of a waterflooding operation is pushing the low-pressure remained oil of reservoir toward the producer wells to enhance the oil recovery factor. One of the important objects of a waterflooding operation management is understanding the quality of connection between the injectors and the producers of the reservoir. Capacitance resistance model (CRM) is a data-driven method which can estimate the production rate of each producer and the connectivity factor between each pair of wells, by history matching of the injection and production data. The estimated connectivity factor can be used for understanding the quality of connection between the wells. In the waterflooding operation, the injected water always has the potential of causing formation damage by invasion of foreign particles deep bed filtration (DBF), mobilization of indigenous particles (fines migration), scale formation, etc. The formation damage can weaken the quality of connection (connectivity factor), between the injectors and producers of the field, increasing the skin of injection well. In this paper, DBF is used for creation of formation damage in synthetic reservoir models. Then, it has been tried to find the existence and amount of formation damage by evaluating the connectivity factor of CRM. Finally, the results of that have been used for prediction of skin variation in a real case by using the connectivity factor of CRM. CRM (dpeaa)DE-He213 Connectivity factor (dpeaa)DE-He213 DBF (dpeaa)DE-He213 Formation damage (dpeaa)DE-He213 Skin (dpeaa)DE-He213 Jahangiri, Hamid Reza verfasserin aut Shahrabadi, Abbas verfasserin aut Enthalten in Journal of petroleum exploration and production technology Berlin : Springer, 2011 10(2019), 2 vom: 24. Aug., Seite 699-710 (DE-627)647654148 (DE-600)2595714-4 2190-0566 nnns volume:10 year:2019 number:2 day:24 month:08 pages:699-710 https://dx.doi.org/10.1007/s13202-019-00764-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA 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 10 2019 2 24 08 699-710 |
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10.1007/s13202-019-00764-9 doi (DE-627)SPR039035077 (SPR)s13202-019-00764-9-e DE-627 ger DE-627 rakwb eng 540 ASE Shabani, Ali verfasserin aut Data-driven approach for evaluation of formation damage during the injection process 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Waterflooding is among the most common oil recovery methods which is implemented in the most of oil-producing countries. The goal of a waterflooding operation is pushing the low-pressure remained oil of reservoir toward the producer wells to enhance the oil recovery factor. One of the important objects of a waterflooding operation management is understanding the quality of connection between the injectors and the producers of the reservoir. Capacitance resistance model (CRM) is a data-driven method which can estimate the production rate of each producer and the connectivity factor between each pair of wells, by history matching of the injection and production data. The estimated connectivity factor can be used for understanding the quality of connection between the wells. In the waterflooding operation, the injected water always has the potential of causing formation damage by invasion of foreign particles deep bed filtration (DBF), mobilization of indigenous particles (fines migration), scale formation, etc. The formation damage can weaken the quality of connection (connectivity factor), between the injectors and producers of the field, increasing the skin of injection well. In this paper, DBF is used for creation of formation damage in synthetic reservoir models. Then, it has been tried to find the existence and amount of formation damage by evaluating the connectivity factor of CRM. Finally, the results of that have been used for prediction of skin variation in a real case by using the connectivity factor of CRM. CRM (dpeaa)DE-He213 Connectivity factor (dpeaa)DE-He213 DBF (dpeaa)DE-He213 Formation damage (dpeaa)DE-He213 Skin (dpeaa)DE-He213 Jahangiri, Hamid Reza verfasserin aut Shahrabadi, Abbas verfasserin aut Enthalten in Journal of petroleum exploration and production technology Berlin : Springer, 2011 10(2019), 2 vom: 24. Aug., Seite 699-710 (DE-627)647654148 (DE-600)2595714-4 2190-0566 nnns volume:10 year:2019 number:2 day:24 month:08 pages:699-710 https://dx.doi.org/10.1007/s13202-019-00764-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA 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 10 2019 2 24 08 699-710 |
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10.1007/s13202-019-00764-9 doi (DE-627)SPR039035077 (SPR)s13202-019-00764-9-e DE-627 ger DE-627 rakwb eng 540 ASE Shabani, Ali verfasserin aut Data-driven approach for evaluation of formation damage during the injection process 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Waterflooding is among the most common oil recovery methods which is implemented in the most of oil-producing countries. The goal of a waterflooding operation is pushing the low-pressure remained oil of reservoir toward the producer wells to enhance the oil recovery factor. One of the important objects of a waterflooding operation management is understanding the quality of connection between the injectors and the producers of the reservoir. Capacitance resistance model (CRM) is a data-driven method which can estimate the production rate of each producer and the connectivity factor between each pair of wells, by history matching of the injection and production data. The estimated connectivity factor can be used for understanding the quality of connection between the wells. In the waterflooding operation, the injected water always has the potential of causing formation damage by invasion of foreign particles deep bed filtration (DBF), mobilization of indigenous particles (fines migration), scale formation, etc. The formation damage can weaken the quality of connection (connectivity factor), between the injectors and producers of the field, increasing the skin of injection well. In this paper, DBF is used for creation of formation damage in synthetic reservoir models. Then, it has been tried to find the existence and amount of formation damage by evaluating the connectivity factor of CRM. Finally, the results of that have been used for prediction of skin variation in a real case by using the connectivity factor of CRM. CRM (dpeaa)DE-He213 Connectivity factor (dpeaa)DE-He213 DBF (dpeaa)DE-He213 Formation damage (dpeaa)DE-He213 Skin (dpeaa)DE-He213 Jahangiri, Hamid Reza verfasserin aut Shahrabadi, Abbas verfasserin aut Enthalten in Journal of petroleum exploration and production technology Berlin : Springer, 2011 10(2019), 2 vom: 24. Aug., Seite 699-710 (DE-627)647654148 (DE-600)2595714-4 2190-0566 nnns volume:10 year:2019 number:2 day:24 month:08 pages:699-710 https://dx.doi.org/10.1007/s13202-019-00764-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA 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 10 2019 2 24 08 699-710 |
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10.1007/s13202-019-00764-9 doi (DE-627)SPR039035077 (SPR)s13202-019-00764-9-e DE-627 ger DE-627 rakwb eng 540 ASE Shabani, Ali verfasserin aut Data-driven approach for evaluation of formation damage during the injection process 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Waterflooding is among the most common oil recovery methods which is implemented in the most of oil-producing countries. The goal of a waterflooding operation is pushing the low-pressure remained oil of reservoir toward the producer wells to enhance the oil recovery factor. One of the important objects of a waterflooding operation management is understanding the quality of connection between the injectors and the producers of the reservoir. Capacitance resistance model (CRM) is a data-driven method which can estimate the production rate of each producer and the connectivity factor between each pair of wells, by history matching of the injection and production data. The estimated connectivity factor can be used for understanding the quality of connection between the wells. In the waterflooding operation, the injected water always has the potential of causing formation damage by invasion of foreign particles deep bed filtration (DBF), mobilization of indigenous particles (fines migration), scale formation, etc. The formation damage can weaken the quality of connection (connectivity factor), between the injectors and producers of the field, increasing the skin of injection well. In this paper, DBF is used for creation of formation damage in synthetic reservoir models. Then, it has been tried to find the existence and amount of formation damage by evaluating the connectivity factor of CRM. Finally, the results of that have been used for prediction of skin variation in a real case by using the connectivity factor of CRM. CRM (dpeaa)DE-He213 Connectivity factor (dpeaa)DE-He213 DBF (dpeaa)DE-He213 Formation damage (dpeaa)DE-He213 Skin (dpeaa)DE-He213 Jahangiri, Hamid Reza verfasserin aut Shahrabadi, Abbas verfasserin aut Enthalten in Journal of petroleum exploration and production technology Berlin : Springer, 2011 10(2019), 2 vom: 24. Aug., Seite 699-710 (DE-627)647654148 (DE-600)2595714-4 2190-0566 nnns volume:10 year:2019 number:2 day:24 month:08 pages:699-710 https://dx.doi.org/10.1007/s13202-019-00764-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA 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 10 2019 2 24 08 699-710 |
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10.1007/s13202-019-00764-9 doi (DE-627)SPR039035077 (SPR)s13202-019-00764-9-e DE-627 ger DE-627 rakwb eng 540 ASE Shabani, Ali verfasserin aut Data-driven approach for evaluation of formation damage during the injection process 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Waterflooding is among the most common oil recovery methods which is implemented in the most of oil-producing countries. The goal of a waterflooding operation is pushing the low-pressure remained oil of reservoir toward the producer wells to enhance the oil recovery factor. One of the important objects of a waterflooding operation management is understanding the quality of connection between the injectors and the producers of the reservoir. Capacitance resistance model (CRM) is a data-driven method which can estimate the production rate of each producer and the connectivity factor between each pair of wells, by history matching of the injection and production data. The estimated connectivity factor can be used for understanding the quality of connection between the wells. In the waterflooding operation, the injected water always has the potential of causing formation damage by invasion of foreign particles deep bed filtration (DBF), mobilization of indigenous particles (fines migration), scale formation, etc. The formation damage can weaken the quality of connection (connectivity factor), between the injectors and producers of the field, increasing the skin of injection well. In this paper, DBF is used for creation of formation damage in synthetic reservoir models. Then, it has been tried to find the existence and amount of formation damage by evaluating the connectivity factor of CRM. Finally, the results of that have been used for prediction of skin variation in a real case by using the connectivity factor of CRM. CRM (dpeaa)DE-He213 Connectivity factor (dpeaa)DE-He213 DBF (dpeaa)DE-He213 Formation damage (dpeaa)DE-He213 Skin (dpeaa)DE-He213 Jahangiri, Hamid Reza verfasserin aut Shahrabadi, Abbas verfasserin aut Enthalten in Journal of petroleum exploration and production technology Berlin : Springer, 2011 10(2019), 2 vom: 24. Aug., Seite 699-710 (DE-627)647654148 (DE-600)2595714-4 2190-0566 nnns volume:10 year:2019 number:2 day:24 month:08 pages:699-710 https://dx.doi.org/10.1007/s13202-019-00764-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA 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 10 2019 2 24 08 699-710 |
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Data-driven approach for evaluation of formation damage during the injection process |
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Abstract Waterflooding is among the most common oil recovery methods which is implemented in the most of oil-producing countries. The goal of a waterflooding operation is pushing the low-pressure remained oil of reservoir toward the producer wells to enhance the oil recovery factor. One of the important objects of a waterflooding operation management is understanding the quality of connection between the injectors and the producers of the reservoir. Capacitance resistance model (CRM) is a data-driven method which can estimate the production rate of each producer and the connectivity factor between each pair of wells, by history matching of the injection and production data. The estimated connectivity factor can be used for understanding the quality of connection between the wells. In the waterflooding operation, the injected water always has the potential of causing formation damage by invasion of foreign particles deep bed filtration (DBF), mobilization of indigenous particles (fines migration), scale formation, etc. The formation damage can weaken the quality of connection (connectivity factor), between the injectors and producers of the field, increasing the skin of injection well. In this paper, DBF is used for creation of formation damage in synthetic reservoir models. Then, it has been tried to find the existence and amount of formation damage by evaluating the connectivity factor of CRM. Finally, the results of that have been used for prediction of skin variation in a real case by using the connectivity factor of CRM. |
abstractGer |
Abstract Waterflooding is among the most common oil recovery methods which is implemented in the most of oil-producing countries. The goal of a waterflooding operation is pushing the low-pressure remained oil of reservoir toward the producer wells to enhance the oil recovery factor. One of the important objects of a waterflooding operation management is understanding the quality of connection between the injectors and the producers of the reservoir. Capacitance resistance model (CRM) is a data-driven method which can estimate the production rate of each producer and the connectivity factor between each pair of wells, by history matching of the injection and production data. The estimated connectivity factor can be used for understanding the quality of connection between the wells. In the waterflooding operation, the injected water always has the potential of causing formation damage by invasion of foreign particles deep bed filtration (DBF), mobilization of indigenous particles (fines migration), scale formation, etc. The formation damage can weaken the quality of connection (connectivity factor), between the injectors and producers of the field, increasing the skin of injection well. In this paper, DBF is used for creation of formation damage in synthetic reservoir models. Then, it has been tried to find the existence and amount of formation damage by evaluating the connectivity factor of CRM. Finally, the results of that have been used for prediction of skin variation in a real case by using the connectivity factor of CRM. |
abstract_unstemmed |
Abstract Waterflooding is among the most common oil recovery methods which is implemented in the most of oil-producing countries. The goal of a waterflooding operation is pushing the low-pressure remained oil of reservoir toward the producer wells to enhance the oil recovery factor. One of the important objects of a waterflooding operation management is understanding the quality of connection between the injectors and the producers of the reservoir. Capacitance resistance model (CRM) is a data-driven method which can estimate the production rate of each producer and the connectivity factor between each pair of wells, by history matching of the injection and production data. The estimated connectivity factor can be used for understanding the quality of connection between the wells. In the waterflooding operation, the injected water always has the potential of causing formation damage by invasion of foreign particles deep bed filtration (DBF), mobilization of indigenous particles (fines migration), scale formation, etc. The formation damage can weaken the quality of connection (connectivity factor), between the injectors and producers of the field, increasing the skin of injection well. In this paper, DBF is used for creation of formation damage in synthetic reservoir models. Then, it has been tried to find the existence and amount of formation damage by evaluating the connectivity factor of CRM. Finally, the results of that have been used for prediction of skin variation in a real case by using the connectivity factor of CRM. |
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