Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.637610
Title: Analysis of PS-converted wave seismic data in the presence of azimuthal anisotropy
Author: Liu, Weining
ISNI:       0000 0004 5360 8490
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2014
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Abstract:
Shear-wave splitting and azimuthal variations of seismic attributes are two major anisotropic effects induced by vertically-aligned fractures. They both have influences on seismic data processing and interpretation, and provide information on fracture properties. Azimuthal variations in P-wave data have been intensively studied to improve imaging and obtain fracture parameters. However, azimuthal variations in PS-converted wave seismic data, particularly the velocity variation in PS-converted wave data, have not been well studied. Shear-wave splitting has been frequently used to estimate fracture directions and densities. However, its influence on the azimuthal variations of PS-converted wave data has also lacked a proper analysis. In this thesis, I analyse the anisotropic behaviour of PS-converted wave seismic data in the presence of azimuthal anisotropy, which includes the azimuthal variation of the PSconverted wave and PS-converted wave splitting. First, I demonstrate the robustness of PS-converted wave splitting for fracture characterisation. PS-converted wave seismic data is also influenced by the splitting effect due to its upgoing shear-wave leg. This important feature enables the application of shear-wave splitting analysis to PS-converted wave seismic data. I use synthetic data to show the necessity for separation of the split PS-converted waves. Then I apply the PS-converted wave splitting analysis to Sanhu 3D3C land seismic data. By separation of the fast and slow PS-converted waves and compensation for the time delays, the imaging quality has been improved. Dominant fracture properties obtained from the splitting analysis show a good correlation with the stress-field data. However, this work is accomplished by assuming only one set of vertical fractures in processing a given time window. In future work a specific layer-stripping algorithm could be constructed and applied. . Second, I study azimuthal variations of velocities in PS-converted wave seismic data. It involves two major parts: analysing azimuthal variations of NMO velocities to improve imaging, and examining the sensitivity of azimuthal variations to different fluid saturations. For a layer with HTI anisotropy induced by a set of vertical fractures, seismologists usually analyse the azimuthal behaviour exhibited on the radial and transverse components, on which PS-converted wave data are recorded. However, PS-converted waves also undergo shear-wave splitting, which complicates the azimuthal variations of PS-converted wave data. I demonstrate that it is essential to separate the fast P-SV1 wave from the slow P-SV2 wave, before applying any azimuthal analysis. I derive an equation describing the azimuthal variation in PSconverted wave NMO velocities, which shows the variation can be approximated into an ellipse. Based on this theory, I build a workflow to analyse the azimuthal variations of velocities in PS-converted wave data and apply this workflow to synthetic data. The imaging quality can be improved by using this workflow. Different fluid saturations in fractures have different influences on the azimuthal variations of both P-wave and PS-converted wave data. I perform a numerical study to understand how dry or water-saturated fractures control the azimuthal variations. Through theoretical and synthetic studies, I find that the azimuthal variation of velocities in PS-converted wave data is sensitive to different fluid saturations. By analysing the azimuthal variation, the fracture properties can also be estimated, but results are not as robust as those from PS-converted wave splitting analysis. I find that azimuthal variations of fast P-SV1 and slow P-SV2 waves show in-phase characteristics in dry fractures, but exhibit out-of-phase characteristics in water-saturated fractures. This important feature could open a new application for using PS-converted wave seismic data to distinguish oil-filled fractures from gas-filled fractures. In cases where multiple HTI layers are involved, I have developed a specific layer-stripping method to analyse both azimuthal variations and splitting effects of PS-converted waves. By applying this method to synthetic data, the fracture properties of each HTI layer can be estimated. The analysis of azimuthal variations in PS-converted wave velocities is applied to Daqing 3D3C land data. By using azimuthal velocity models in the PS-converted wave seismic data processing, the imaging quality is improved, especially in the anticline area where intensive fractures are likely to be developed. Furthermore, all fracture information obtained from analysis of azimuthal variations and splitting effects is compared with the stress-field data. The results from splitting analysis show a better correlation with the stress-field study. Finally, it is important to conclude that the analysis of PS-converted wave splitting is a robust method to estimate fracture directions and densities. However, it is not sensitive to different fluid saturations, which limits its application to fractured reservoir characterisation. Azimuthal variations of PS-converted wave seismic data can be analysed to improve imaging quality. Moreover their sensitivity to fluid saturations may provide a new way to discriminate between oil-filled and gas-filled fractures. However, the analysis of azimuthal variations is not as robust as the analysis of splitting effects, and it may require appropriate calibration with other fracture characterisation methods.
Supervisor: Li, Xiang; Curtis, Andrew Sponsor: Natural Environment Research Council (NERC)
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.637610  DOI: Not available
Keywords: Azimuthal variations ; PS-converted wave seismic data ; azimuthal anisotropy ; PS-converted wave splitting
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