A complex gas hydrate system imaged jointly using MCS and OBS data from the northern South China Sea
Abstract Much of our knowledge of gas hydrate in the Dongsha area of the South China Sea has been gained through intensive geophysical surveys and drilling. However, many factors remain unclear, such as the co-existence of shallow gas hydrate and deeper gas hydrate. This lack of clarity is partially...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Liu, Bin [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Nature B.V. 2020 |
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| Übergeordnetes Werk: |
Enthalten in: Marine geophysical research - Springer Netherlands, 1970, 41(2020), 4 vom: 23. Sept. |
|---|---|
| Übergeordnetes Werk: |
volume:41 ; year:2020 ; number:4 ; day:23 ; month:09 |
| Links: |
|---|
| DOI / URN: |
10.1007/s11001-020-09414-w |
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| 520 | |a Abstract Much of our knowledge of gas hydrate in the Dongsha area of the South China Sea has been gained through intensive geophysical surveys and drilling. However, many factors remain unclear, such as the co-existence of shallow gas hydrate and deeper gas hydrate. This lack of clarity is partially due to the lack of a depth-domain velocity model and accurate imagery of the gas hydrate-bearing sediments. In this study, pre-stack depth migration (PSDM) is used to produce subsurface images using a depth-domain velocity model from OBS tomography as the migration velocity. A simple initial velocity model was built using the seafloor depth information derived from multi-channel seismic (MCS) data. This simple model was used to build a more accurate velocity model by using first arrival time tomography from OBS data. Three different approaches were used to assess the reliability of the velocity model. Resolution tests and uncertainties analysis were used to further evaluate the model. The final PSDM image revealed some features more clearly than they were seen on the time migration image. These features help better explain the complex gas hydrate system. The depth of a bottom-simulating reflector (BSR) was picked directly from the PSDM image. This BSR is very consistent with the drilling result. Our work highlights the importance of PSDM in the study of gas hydrate in complex settings and highlights the potential and value of using OBS refraction in building shallow velocity models. | ||
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| 700 | 1 | |a Zhang, Heng |4 aut | |
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10.1007/s11001-020-09414-w doi (DE-627)OLC2121497048 (DE-He213)s11001-020-09414-w-p DE-627 ger DE-627 rakwb eng 550 VZ 16,13 ssgn Liu, Bin verfasserin aut A complex gas hydrate system imaged jointly using MCS and OBS data from the northern South China Sea 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Nature B.V. 2020 Abstract Much of our knowledge of gas hydrate in the Dongsha area of the South China Sea has been gained through intensive geophysical surveys and drilling. However, many factors remain unclear, such as the co-existence of shallow gas hydrate and deeper gas hydrate. This lack of clarity is partially due to the lack of a depth-domain velocity model and accurate imagery of the gas hydrate-bearing sediments. In this study, pre-stack depth migration (PSDM) is used to produce subsurface images using a depth-domain velocity model from OBS tomography as the migration velocity. A simple initial velocity model was built using the seafloor depth information derived from multi-channel seismic (MCS) data. This simple model was used to build a more accurate velocity model by using first arrival time tomography from OBS data. Three different approaches were used to assess the reliability of the velocity model. Resolution tests and uncertainties analysis were used to further evaluate the model. The final PSDM image revealed some features more clearly than they were seen on the time migration image. These features help better explain the complex gas hydrate system. The depth of a bottom-simulating reflector (BSR) was picked directly from the PSDM image. This BSR is very consistent with the drilling result. Our work highlights the importance of PSDM in the study of gas hydrate in complex settings and highlights the potential and value of using OBS refraction in building shallow velocity models. MCS OBS First arrival tomography PSDM BSR Wang, Xiangchun aut Xu, Yunxia aut Wen, Pengfei aut Li, Liqing aut Zhang, Heng aut Enthalten in Marine geophysical research Springer Netherlands, 1970 41(2020), 4 vom: 23. Sept. (DE-627)129987603 (DE-600)414196-9 (DE-576)01554558X 0025-3235 nnns volume:41 year:2020 number:4 day:23 month:09 https://doi.org/10.1007/s11001-020-09414-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OPC-GGO SSG-OPC-GEO AR 41 2020 4 23 09 |
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10.1007/s11001-020-09414-w doi (DE-627)OLC2121497048 (DE-He213)s11001-020-09414-w-p DE-627 ger DE-627 rakwb eng 550 VZ 16,13 ssgn Liu, Bin verfasserin aut A complex gas hydrate system imaged jointly using MCS and OBS data from the northern South China Sea 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Nature B.V. 2020 Abstract Much of our knowledge of gas hydrate in the Dongsha area of the South China Sea has been gained through intensive geophysical surveys and drilling. However, many factors remain unclear, such as the co-existence of shallow gas hydrate and deeper gas hydrate. This lack of clarity is partially due to the lack of a depth-domain velocity model and accurate imagery of the gas hydrate-bearing sediments. In this study, pre-stack depth migration (PSDM) is used to produce subsurface images using a depth-domain velocity model from OBS tomography as the migration velocity. A simple initial velocity model was built using the seafloor depth information derived from multi-channel seismic (MCS) data. This simple model was used to build a more accurate velocity model by using first arrival time tomography from OBS data. Three different approaches were used to assess the reliability of the velocity model. Resolution tests and uncertainties analysis were used to further evaluate the model. The final PSDM image revealed some features more clearly than they were seen on the time migration image. These features help better explain the complex gas hydrate system. The depth of a bottom-simulating reflector (BSR) was picked directly from the PSDM image. This BSR is very consistent with the drilling result. Our work highlights the importance of PSDM in the study of gas hydrate in complex settings and highlights the potential and value of using OBS refraction in building shallow velocity models. MCS OBS First arrival tomography PSDM BSR Wang, Xiangchun aut Xu, Yunxia aut Wen, Pengfei aut Li, Liqing aut Zhang, Heng aut Enthalten in Marine geophysical research Springer Netherlands, 1970 41(2020), 4 vom: 23. Sept. (DE-627)129987603 (DE-600)414196-9 (DE-576)01554558X 0025-3235 nnns volume:41 year:2020 number:4 day:23 month:09 https://doi.org/10.1007/s11001-020-09414-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OPC-GGO SSG-OPC-GEO AR 41 2020 4 23 09 |
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a complex gas hydrate system imaged jointly using mcs and obs data from the northern south china sea |
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A complex gas hydrate system imaged jointly using MCS and OBS data from the northern South China Sea |
| abstract |
Abstract Much of our knowledge of gas hydrate in the Dongsha area of the South China Sea has been gained through intensive geophysical surveys and drilling. However, many factors remain unclear, such as the co-existence of shallow gas hydrate and deeper gas hydrate. This lack of clarity is partially due to the lack of a depth-domain velocity model and accurate imagery of the gas hydrate-bearing sediments. In this study, pre-stack depth migration (PSDM) is used to produce subsurface images using a depth-domain velocity model from OBS tomography as the migration velocity. A simple initial velocity model was built using the seafloor depth information derived from multi-channel seismic (MCS) data. This simple model was used to build a more accurate velocity model by using first arrival time tomography from OBS data. Three different approaches were used to assess the reliability of the velocity model. Resolution tests and uncertainties analysis were used to further evaluate the model. The final PSDM image revealed some features more clearly than they were seen on the time migration image. These features help better explain the complex gas hydrate system. The depth of a bottom-simulating reflector (BSR) was picked directly from the PSDM image. This BSR is very consistent with the drilling result. Our work highlights the importance of PSDM in the study of gas hydrate in complex settings and highlights the potential and value of using OBS refraction in building shallow velocity models. © Springer Nature B.V. 2020 |
| abstractGer |
Abstract Much of our knowledge of gas hydrate in the Dongsha area of the South China Sea has been gained through intensive geophysical surveys and drilling. However, many factors remain unclear, such as the co-existence of shallow gas hydrate and deeper gas hydrate. This lack of clarity is partially due to the lack of a depth-domain velocity model and accurate imagery of the gas hydrate-bearing sediments. In this study, pre-stack depth migration (PSDM) is used to produce subsurface images using a depth-domain velocity model from OBS tomography as the migration velocity. A simple initial velocity model was built using the seafloor depth information derived from multi-channel seismic (MCS) data. This simple model was used to build a more accurate velocity model by using first arrival time tomography from OBS data. Three different approaches were used to assess the reliability of the velocity model. Resolution tests and uncertainties analysis were used to further evaluate the model. The final PSDM image revealed some features more clearly than they were seen on the time migration image. These features help better explain the complex gas hydrate system. The depth of a bottom-simulating reflector (BSR) was picked directly from the PSDM image. This BSR is very consistent with the drilling result. Our work highlights the importance of PSDM in the study of gas hydrate in complex settings and highlights the potential and value of using OBS refraction in building shallow velocity models. © Springer Nature B.V. 2020 |
| abstract_unstemmed |
Abstract Much of our knowledge of gas hydrate in the Dongsha area of the South China Sea has been gained through intensive geophysical surveys and drilling. However, many factors remain unclear, such as the co-existence of shallow gas hydrate and deeper gas hydrate. This lack of clarity is partially due to the lack of a depth-domain velocity model and accurate imagery of the gas hydrate-bearing sediments. In this study, pre-stack depth migration (PSDM) is used to produce subsurface images using a depth-domain velocity model from OBS tomography as the migration velocity. A simple initial velocity model was built using the seafloor depth information derived from multi-channel seismic (MCS) data. This simple model was used to build a more accurate velocity model by using first arrival time tomography from OBS data. Three different approaches were used to assess the reliability of the velocity model. Resolution tests and uncertainties analysis were used to further evaluate the model. The final PSDM image revealed some features more clearly than they were seen on the time migration image. These features help better explain the complex gas hydrate system. The depth of a bottom-simulating reflector (BSR) was picked directly from the PSDM image. This BSR is very consistent with the drilling result. Our work highlights the importance of PSDM in the study of gas hydrate in complex settings and highlights the potential and value of using OBS refraction in building shallow velocity models. © Springer Nature B.V. 2020 |
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| title_short |
A complex gas hydrate system imaged jointly using MCS and OBS data from the northern South China Sea |
| url |
https://doi.org/10.1007/s11001-020-09414-w |
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| author2 |
Wang, Xiangchun Xu, Yunxia Wen, Pengfei Li, Liqing Zhang, Heng |
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Wang, Xiangchun Xu, Yunxia Wen, Pengfei Li, Liqing Zhang, Heng |
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| doi_str |
10.1007/s11001-020-09414-w |
| up_date |
2024-07-04T07:07:26.902Z |
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