In the exploration of a fractured reservoir, it is very important for reservoir engineers to get information about fracture sizes, because macro-scale fractures are more significant to the control of reservoir storability and fluid flow even though both micro-scale cracks and macro-scale fractures contribute to the dominant anisotropy. Recently, a poroelastic equivalent medium model was proposed by Chapman, which describes the frequency-dependent anisotropy effect with the fracture size being one of the key parameters. Based on this model, geophysicists have done work to measure fracture sizes from seismic data. However, it is necessary to extract frequency-dependent anisotropy before inverting for fracture size. In this paper, a new algorithm is developed for extracting frequency-dependent anisotropic parameters from surface multi-component seismic data, especially from a common-receiver-gather. Compared with the conventional method of extracting the splitting parameters only for different frequency bands, it is possible to extract splitting parameters for each frequency with the new algorithm. To check the reliability of the algorithm, a common-receiver-all-azimuth-gather is synthesized by the vector convolution method, involving the splitting parameters dependent on frequency. Test results show that the frequency-dependent splitting parameters will be extracted accurately with a general level of noise (the signal to noise ratio, SNR for shot, equals 3). More importantly, under the joint constraints of multi-azimuth data, a satisfactory result will be obtained even if the noise is significant (SNR equals 1). The good performance of the algorithm in a model test indicates its potential for field applications.
| Publication name | JOURNAL OF GEOPHYSICS AND ENGINEERING Volume: 10 Issue: 5 Article Number: 055005 Published: OCT 2013 |
| Author(s) | Zhang, Jian-li; Wang, Yun; Lu, Jun |
| Corresponding author | ZHANG Jianli
Chinese Acad Sci, Multiwave & Multicomponent MWMC Grp, Inst Geol & Geophys, Beijing 100029, Peoples R China. |
| Author(s) from IGCAS | WANG Yun |
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