A Deterministic Evaluation of eismic Fidelity using Velocity Modeling ...

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Chapter 7 Conclusions and Discussion 7.1 Introduction The goal of this study was to improve the spatial fidelity of seismic imaging through a deterministic evaluation of surface seismic data with velocity modeling and attribute analysis. To achieve the goal I modeled sediment velocities using sonic log velocities, a well-based model, and migrated using a Kirchhoff PSDM. I compared the well-based method of velocity modeling to a more traditional method of using residual migration velocities or prestack time migrated velocity model velocities to model sediment velocities for the migration. I evaluated the results through velocity analysis using CIGs, interpretation, and an innovative use of attributes as a QC tool. Using a velocity model derived from sonic logs improved the spatial fidelity of the land 3-D surface seismic data at Vinton Dome Louisiana and that coherence is an attribute for quantifying improvements is a conclusion I reached in this study. 7.2 Evaluation of Methods 7.2.1 Processing Generally, 3-D surface seismic land data have a lower signal-to-noise ratio than 3-D marine surface seismic data because of noise sources and irregular acquisition and 3-D land surface seismic data require a higher degree of processing than do marine data. The lower signal-to-noise ratio is a reason why marine data are generally better candidates for PSDM. The goal of this study was to improve the spatial fidelity of seismic imaging using velocity modeling and attribute analysis. Field data were processed to reduce noise 140
yet there are several issues regarding processing of land data such as the Vinton Dome survey that are acquired in nontraditional patterns that were not addressed in this study. The approach to processing that I took in this study was to pre-migration process the data so that they maintained a broadband and a high signal-to-noise ratio. I was able to increase the signal-to-noise ratio to a high level using a processing flow enhanced using AGC. Improving the data quality through pre-migration processing allowed the focus of the study to be on velocity modeling of the sediment velocities. There are processing issues that were beyond the scope of this study such as finding the least invasive means to remove surface waves. Another significant issue is the need for development of an acquisition specific processing flow. Data acquisition of the 3-D surface seismic data was in a radial pattern at Vinton Dome. Processing is usually for a brick pattern 3-D seismic acquisition. The impact of a processing flow designed for brick pattern acquisition, applied to data acquired in a radial pattern is not fully understood and for the Vinton Dome survey this is an issue that should be addressed. 7.2.2 Velocity Modeling Data migrated with a velocity model derived from sonic logs provided a superior image than PSTM data and PSDM that used a traditional prestack time migrated velocity model. Two issues that factored into this were vertical and horizontal velocities. In the seismic 141
Page 1 and 2:
Chapter 1 Introduction 1.1 Summary
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1.2.1 Geology Vinton Dome is a pier
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layer in land data that in extreme
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logs as being an effective approach
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Chapter 2 Geology of Vinton Dome 2.
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The Gulf of Mexico Basin contains U
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developed from repetitive episodes
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of the upper Frio. Overlying the lo
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structures form by the differential
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Dividing the Gulf of Mexico Basin i
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2.6 Geologic Modeling Historically,
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2.6.1 Vinton Geology Analysis of se
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surface and a number of small subma
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established the Mississippi delta a
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Figure 2. Outline of the extents of
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Figure 6. Salt sediment contacts us
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Figure 10. Fault pattern representa
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Figure 14. Stratigraphic column of
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Top Hackberry Sand Hackberry Base N
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Figure 18. Structure map contoured
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Gyroidina scalata Outer shelf Gyroi
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Upper Frio Sands A Sand base B Sand
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Top Anahuac Middle Shelf Heterosteg
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Miocene sands Figure 27. Spontaneou
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Vinton Dome Figure 30. Late Miocene
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3.1 Introduction Chapter 3 Processi
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3.3 Processing My primary objective
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38-42). For QC I would brute stack
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Another significant issue was to id
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Table 2 Final processing flow Input
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Number of stacked traces 12.5km 12.
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TWT seconds a 12.5km TWT seconds b
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TWT seconds 12.5km Figure 38. Brute
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Chapter 4 Velocity Modeling and Pre
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quality motivated a reassessment of
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The layer-based approach is much mo
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of seismically derived velocities.
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To test differences between seismic
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ased data, indicating higher fideli
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4.5 Conclusions and Discussion I co
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By using sonic logs the velocities
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Figure 50. Velocity cube of the sed
Page 89 and 90: Velocity in ft/sec Figure 52. Prest
Page 91 and 92: Depth in kilo-feet a. b. Figure 56.
Page 93 and 94: Figure 59. Graphic user interface s
Page 95 and 96: Truncation of sediment onto salt a
Page 97 and 98: s 1 s 1 S e C 0 1 O W 34 M M 0 C a
Page 99 and 100: Prestack time migrated velocity mod
Page 101 and 102: Salt on PSTM Prestack time migrated
Page 103 and 104: Time in seconds Bright spot 12.5km
Page 105 and 106: PSTM prestack time well-based migra
Page 107 and 108: attributes also provided me with an
Page 109 and 110: types of coherence. The first type
Page 111 and 112: comparisons, those at the same dept
Page 113 and 114: Identifying reduced fidelity in the
Page 115 and 116: Faults Channel Figure 72. PSTM cohe
Page 117 and 118: Depth slice of coherence cube from
Page 119 and 120: Compartmentalized faults 5895 feet
Page 121 and 122: Well-based PSDM - faults traced fro
Page 123 and 124: Channel Radial faults 3985 feet a C
Page 125 and 126: Well-based PSDM Prestack time migra
Page 127 and 128: Well-based PSDM Faults imaged with
Page 129 and 130: structure and they must complement
Page 131 and 132: Imaged poorly was a fault identifie
Page 133 and 134: interpretation of the high angle gr
Page 135 and 136: Inline 1391 well-based PSDM Inline
Page 137 and 138: Figure 83. Interpretation showing t
Page 139: Channel nnen a Channel b Figure 85.
Page 143 and 144: 7.2.3 Attributes I used attributes
Page 145 and 146: seismic data provided a more detail
Page 147 and 148: educed the noise in the field data
Page 149 and 150: PSDM data to evaluate velocity mode
Page 151 and 152: 10, Society of Exploration Geophysi
Page 153 and 154: Marfurt, K. J., Kirlin, R. L., Farm
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