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Natural fractures are well developed in the Sangtamu carbonate formation which is the primary oil and gas production unit in the Tarim Basin, China. The analysis of converted waves via shear wave splitting (SWS) is an effective tool for predicting natural fractures in carbonate units. Compared with surface seismic data measurements, vertical seismic profiling (VSP) is more advantageous for acquiring and imaging converted waves. At present, there is a lack of robust methods on using 3D three-component (3C) VSP data for fracture prediction. We propose an innovative workflow for predicting the spatial fracture distribution with the first ever application of SWS analysis to a 3D3C VSP dataset. Instead of traditional Cartesian coordinates, we generated image bins based on a polar coordinate system to obtain accurate P-to-S converted waves of different azimuth angles. This was followed by a two-step SWS analysis: first, we conducted a multi-directional SWS analysis to estimate the fracture-induced anisotropy in the upper layers. Then, the wave field of the target layer was corrected using time compensation and coordinate rotation. Finally, we applied SWS analysis again to obtain the azimuth and spatial intensity of the fractures in the target layer. We found that there was an overall good agreement in the fracture densities derived from the VSP waveforms and well-log data. The areas with high fracture development, as indicated by the SWS and ant-tracking analyses, are also consistent. Our study shows that azimuth processing of walkaround 3D3C VSP combined with SWS analysis can serve as a quantitative diagnostic tool for fractures in a carbonate reservoir.
Natural fractures are well developed in the Sangtamu carbonate formation which is the primary oil and gas production unit in the Tarim Basin, China. The analysis of converted waves via shear wave splitting (SWS) is an effective tool for predicting natural fractures in carbonate units. Compared with surface seismic data measurements, vertical seismic profiling (VSP) is more advantageous for acquiring and imaging converted waves. At present, there is a lack of robust methods on using 3D three-component (3C) VSP data for fracture prediction. We propose an innovative workflow for predicting the spatial fracture distribution with the first ever application of SWS analysis to a 3D3C VSP dataset. Instead of traditional Cartesian coordinates, we generated image bins based on a polar coordinate system to obtain accurate P-to-S converted waves of different azimuth angles. This was followed by a two-step SWS analysis: first, we conducted a multi-directional SWS analysis to estimate the fracture-induced anisotropy in the upper layers. Then, the wave field of the target layer was corrected using time compensation and coordinate rotation. Finally, we applied SWS analysis again to obtain the azimuth and spatial intensity of the fractures in the target layer. We found that there was an overall good agreement in the fracture densities derived from the VSP waveforms and well-log data. The areas with high fracture development, as indicated by the SWS and ant-tracking analyses, are also consistent. Our study shows that azimuth processing of walkaround 3D3C VSP combined with SWS analysis can serve as a quantitative diagnostic tool for fractures in a carbonate reservoir.
The development of natural fractures has a significant impact on underground reservoirs and leads to seismic anisotropy. Furthermore, the scale of natural fractures directly affects the oil and gas preservation, hydraulic fracture construction, and production development of shale reservoirs. Shear-wave anisotropy is a frequency dependent parameter and the change in shear-wave anisotropy with frequency is a function of the fracture scale. We propose an innovative method for predicting the fracture scale quantitatively using frequency-dependent shear-wave anisotropy. The quantitative relationship between different fracture scales and the frequency-dependent response of the shear-wave splitting (SWS) anisotropy can be obtained using a dynamic rock physics model. The frequency-dependent shear-wave anisotropy was calculated via SWS analysis in the frequency domain, after which this quantitative relationship and the calculated frequency-dependent response was used to establish an objective function for inversion of fracture scale at different depths using the least-squares algorithm. We synthesized data under ideal conditions, tested the proposed method, applied our method to field data, and found that the quantitative prediction method of the fracture scale yielded reasonable prediction results. The shear-wave anisotropy was calculated based on the SWS analysis from the horizontal components of the upgoing wavefields of the field vertical seismic profile. We compared the fracture scale calculated from logging data using the proposed method, and the results obtained indicated that this method can successfully predict the fracture scale quantitatively.
Natural fractures in oil and gas reservoirs are a crucial factor that cannot be ignored, as they significantly influence the reservoir's petrophysical properties and hydrocarbon development. A horizontal transversely isotropic (HTI) medium composed of a single fracture set in an isotropic background is a typical anisotropic medium. Meanwhile, the shear wave splitting (SWS) is a sensitive response of such anisotropic media, resulting in the generation of fast and slow shear waves. The normal and tangential fracture weaknesses are crucial parameters that characterize the anisotropy of fractured media. We proposed an inversion method for fracture weakness based on three-component vertical seismic profiling (3CVSP) data. Firstly, assuming weak anisotropy and an HTI medium containing single fracture set, we derived a first-order linear approximation of the travel times of the converted fast and slow shear waves (PS1- and PS2-waves) with respect to fracture weakness parameters in the phase velocity domain. By solving for the horizontal projection of the slowness vector, approximate equations of the travel times of the PS1- and PS2-waves were converted from phase velocity domain to the group velocity domain. Furthermore, we devised an inversion workflow consisting of three primary steps: 1. pre-processing the VSP data to derive the travel times and azimuth of the HTI medium; 2. constructing a forward model with undetermined fracture weakness parameters; 3. following the establishment of the objective function, conducting the inversion for the fracture weakness parameters. We demonstrated the reliability of the method through numerical examples and synthetic 3CVSP data. The inversion errors are primarily influenced by the azimuth angle, with minimal influence from the receiver depth. Furthermore, a collective set of inverted results derived from all geophones are more stable and accurate than individual geophones. The application to actual 3CVSP data further confirmed the effectiveness of our approach.
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