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sep:research:theses:sep159 [2015/08/27 09:30]
yang |
sep:research:theses:sep159 [2015/08/27 10:53]
yang |
| // by Yang Zhang // | // by Yang Zhang // |
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| Full thesis [[http://sepwww.stanford.edu/data/media/public/docs/sep159/sep159.pdf|PDF]] | **Downloads** |
| | * Thesis + Computation recipe [[http://sepwww.stanford.edu/data/media/public/docs/sep159/sep159.tar.gz|tar.gz]] |
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| | * Thesis [[http://sepwww.stanford.edu/data/media/public/docs/sep159/sep159.pdf|pdf]] |
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| **Table of contents** | **Table of contents** |
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| * Chapter 1: [[http://sepwww.stanford.edu/data/media/public/docs/sep159/chap1.pdf|Introduction]] | * Chapter 1: Introduction |
| * Chapter 2: [[http://sepwww.stanford.edu/data/media/public/docs/sep159/chap2.pdf|2-D RMO-based WEMVA]] | * Chapter 2: 2-D RMO-based WEMVA |
| * Chapter 3: [[http://sepwww.stanford.edu/data/media/public/docs/sep159/chap3.pdf|3-D extension of RMO-based WEMVA]] | * Chapter 3: 3-D extension of RMO-based WEMVA |
| * Chapter 4: [[http://sepwww.stanford.edu/data/media/public/docs/sep159/chap4.pdf|3-D field data test —- a target-oriented approach]] | * Chapter 4: 3-D field data test —- a target-oriented approach |
| * [[http://sepwww.stanford.edu/data/media/public/docs/sep159/bibli.pdf|Bibliography]]\\ | * Bibliography\\ |
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| **Abstract**\\ | **Abstract**\\ |
| Furthermore, I extend the RMO-based WEMVA method to the 3-D case. To deal with multiple azimuths 3-D ADCIG, I augment my method’s formulation by assign- ing independent moveout parameters to each azimuth. A simple synthetic example verifies that the 3-D extension of the RMO-based WEMVA is able to invert simulta- neously velocity information from multiple azimuths. Finally, I apply my RMO-based WEMVA to a 3-D WATS (Wide Azimuth Towed Streamers) field dataset from GOM (Gulf of Mexico). To make applying WEMVA methods to this large industrial scale dataset computationally affordable on the academic computing resources I have in the school of Earth, Energy and Environmental Sciences, I adopt a target-oriented in- version approach that concentrates on a relatively small target area of interest inside the full physical domain of the dataset. The target-oriented RMO-based WEMVA inversion of this field dataset yields geophysically more consistent models. The inver- sion results show convincing imaging improvements and enhancements in the flatness of the 3-D ADCIG universally across the target domain and all azimuths. | Furthermore, I extend the RMO-based WEMVA method to the 3-D case. To deal with multiple azimuths 3-D ADCIG, I augment my method’s formulation by assign- ing independent moveout parameters to each azimuth. A simple synthetic example verifies that the 3-D extension of the RMO-based WEMVA is able to invert simulta- neously velocity information from multiple azimuths. Finally, I apply my RMO-based WEMVA to a 3-D WATS (Wide Azimuth Towed Streamers) field dataset from GOM (Gulf of Mexico). To make applying WEMVA methods to this large industrial scale dataset computationally affordable on the academic computing resources I have in the school of Earth, Energy and Environmental Sciences, I adopt a target-oriented in- version approach that concentrates on a relatively small target area of interest inside the full physical domain of the dataset. The target-oriented RMO-based WEMVA inversion of this field dataset yields geophysically more consistent models. The inver- sion results show convincing imaging improvements and enhancements in the flatness of the 3-D ADCIG universally across the target domain and all azimuths. |
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| ### For SEP theses index page | |
| | **__Report__ ** | **__Title__ ** | **__Author__ ** | | |
| | **[[http://sepwww.stanford.edu/doku.php?id=sep:research:theses:sep159|SEP-159]]**\\ (2015)\\ [[http://sepwww.stanford.edu/data/media/public/docs/sep159/sep159.pdf|PDF]] | //__ Velocity model building using residual moveout-based wave-equation migration velocity analysis __// | ** Yang Zhang ** | | |
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