Analysis of acquisition parameters and geometry quality
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High-quality seismic geometry is the key to obtain high-quality seismic data, and can affect the accuracy of data processing and imaging. Based on the analysis of the relationship between the quality of the geometry and the four acquisition parameters (the number of traces, shot line spacing, and the space and number of receiver lines), a quality evaluation method of the geometry based on comprehensive quality factor (CQF) is proposed, and the relationship between the geometry quality and the four parameters is given. We use field data collected in an oil field in Western China with complex geology: First we use a wide azimuth geometry. Then, we calculate the relationship curve between geometry and data quality by varying each parameter while keeping the rest fixed. and the analysis results are given by using the CQF evaluation method. The results show that the shot-line spacing has the greatest effect on the quality of the geometry, and the increase of the receiver line spacing can appropriately improve the quality of the geometry, and the increase of the number of receiving traces can improve the geometry quality. The different acquisition parameters have different effects on the imaging quality of shallow and deep events. The model forward and prestack depth migration are used to generate prestack depth migration profiles with different acquisition parameters. The imaging results are consistent with the above calculated results. According to the depth of the target layer, the quality factor evaluation method is applied to guide the design of the geometry and optimize the acquisition parameters to improve the imaging accuracy of seismic data.
KeywordsSeismic acquisition geometry quality factor acquisition parameters
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- Kumar, A., Blacquière, G., and Morten, W., Pedersen, A. G., 2016, Full–wavefield marine survey design using all multiples: Geophysics, 81(3), 1–12.Google Scholar
- Coles, D., Prange, M., and Djikpesse, H., 2015, Optimal survey design for big data: Geophysics, 80(3), 11–22.Google Scholar
- Vermeer, G. J., 2010, 3D symmetric sampling of sparse acquisition geometries: Geophysics, 75(6), WB3–WB14.Google Scholar
- Su, J., Fu, L. Y., Wei, W., et al., 2017, On vertical resolution of seismic acquisition geometries in complex 3D media: Geophysics, 82(6), 75–87.Google Scholar
- Zhao, H., Yin, C., He, G. M., et al., 2015, Research of CRP–based irregular 2D seismic acquisition: Applied Geophysics, 12(1), 73–78.Google Scholar
- Zhao, H., Yin, C., Wu, M. S., et al., 2012, Research on seismic survey design for doubly complex areas: Applied Geophysics, 9(3), 279–285.Google Scholar
- Zhao, H., Yin, C., Hou, P. J., et al., 2013, An automatical infill shot method for uniform imaging of target layer: Applied Geophysics, 10(2), 222–228.Google Scholar
- Zhao, H., Wu, S. H., Yang, J., et al., 2017, Designing optimal number of receiving traces based on simulation model: Applied Geophysics, 14(1), 49–55.Google Scholar
- Zhao, H., Yin, C., Wei, F. J., et al., 2015, Research of goemetry comprehensive quality factor: Oil Geophysical Prospecting (in Chinese), 50(6), 1037–1041.Google Scholar
- Zhang, H., and Chen, X. H., 2013, Seismic data reconstruction based on jittered sampling and curvelet transform: Chinese J. Geophys (in Chinese), 56(5), 1637–1649.Google Scholar
- Zhang, H., Chen, X. H., and Li, H. X., 2015, 3D seismic data reconstruction based on complex–valued curvelet transform in frequency domain: Journal of Applied Geophysics, 113(2), 64–73.Google Scholar