Fractional S-transform?part 2: Application to reservoir prediction and fluid identification
Du Zheng-Cong1,2, Xu De-Ping1,3, and Zhang Jin-Ming4
1. State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Chengdu University of Technology, Chengdu 610059, China.
2. Panzhihua University, Panzhihua 617000, China.
3. Geomathematics Key Laboratory of Sichuan Province of Chengdu University of Technology, Chengdu 610059, China.
4. Geophysical college of Chengdu University of Technology, Chengdu 610059, China.
Abstract The fractional S-transform (FRST) has good time–frequency focusing ability. The FRST can identify geological features by rotating the fractional Fourier transform frequency (FRFTfr) axis. Different seismic signals have different optimal fractional parameters which is not conducive to multichannel seismic data processing. Thus, we first decompose the common-frequency sections by the FRST and then we analyze the low-frequency shadow. Second, the combination of the FRST and blind-source separation is used to obtain the independent spectra of the various geological features. The seismic data interpretation improves without requiring to estimating the optimal fractional parameters. The top and bottom of a limestone reservoir can be clearly recognized on the common-frequency section, thus enhancing the vertical resolution of the analysis of the low-frequency shadows compared with traditional ST. Simulations suggest that the proposed method separates the independent frequency information in the time–fractional-frequency domain. We used field seismic and well data to verify the proposed method.
This work was supported by the Open Fund of State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Chengdu University of Technology (No. PLC201402) and National Nature Science Foundation of China (No. U1562111).
Cite this article:
. Fractional S-transform?part 2: Application to reservoir prediction and fluid identification[J]. APPLIED GEOPHYSICS, 2016, 13(2): 343-352.
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2016, Vol. 13 
