Seismic dynamic monitoring in CO2 flooding based on characterization of frequency-dependent velocity factor
Zhang Jun-Hua1,2, Li Jun1,2, Xiao Wen1,2, Tan Ming-You3, Zhang Yun-Ying3, Cui Shi-Ling3, and Qu Zhi-Peng3
1. School of Geosciences, China University of Petroleum, Qingdao 266580, China.
2. Laboratory for Marine Mineral Resources, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266071, China.
3. Geophysical Research Institute of Shengli Oilfield Branch Company, Sinopec, Dongying 257015, China.
Abstract：
The phase velocity of seismic waves varies with the propagation frequency, and thus frequency-dependent phenomena appear when CO2 gas is injected into a reservoir. By dynamically considering these phenomena with reservoir conditions it is thus feasible to extract the frequency-dependent velocity factor with the aim of monitoring changes in the reservoir both before and after CO2 injection. In the paper, we derive a quantitative expression for the frequency-dependent factor based on the Robinson seismic convolution model. In addition, an inversion equation with a frequency-dependent velocity factor is constructed, and a procedure is implemented using the following four processing steps: decomposition of the spectrum by generalized S transform, wavelet extraction of cross-well seismic traces, spectrum equalization processing, and an extraction method for frequency-dependent velocity factor based on the damped least-square algorithm. An attenuation layered model is then established based on changes in the Q value of the viscoelastic medium, and spectra of migration profiles from forward modeling are obtained and analyzed. Frequency-dependent factors are extracted and compared, and the effectiveness of the method is then verified using a synthetic data. The frequency-dependent velocity factor is finally applied to target processing and oil displacement monitoring based on real seismic data obtained before and after CO2 injection in the G89 well block within Shengli oilfield. Profiles and slices of the frequency-dependent factor determine its ability to indicate differences in CO2 flooding, and the predicting results are highly consistent with those of practical investigations within the well block.
. Seismic dynamic monitoring in CO2 flooding based on characterization of frequency-dependent velocity factor[J]. APPLIED GEOPHYSICS, 2016, 13(2): 307-314.
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2016, Vol. 13 
