Fluid identification based on P-wave anisotropy dispersion gradient inversion for fractured reservoirs |
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| Authors: | J W Zhang H D Huang B H Zhu W Liao |
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| Institution: | 1.Unconventional Natural Gas Research Institute, State Key Laboratory of Petroleum Resources and Prospecting,China University of Petroleum,Beijing,China;2.State Key Laboratory of Petroleum Resources and Prospecting, CNPC Key Lab of Geophysical Exploration,China University of Petroleum,Beijing,China;3.Xinjiang Oilfield Branch Company,PetroChina Company Limited,Karamay,China |
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| Abstract: | Fluid identification in fractured reservoirs is a challenging issue and has drawn increasing attentions. As aligned fractures in subsurface formations can induce anisotropy, we must choose parameters independent with azimuths to characterize fractures and fluid effects such as anisotropy parameters for fractured reservoirs. Anisotropy is often frequency dependent due to wave-induced fluid flow between pores and fractures. This property is conducive for identifying fluid type using azimuthal seismic data in fractured reservoirs. Through the numerical simulation based on Chapman model, we choose the P-wave anisotropy parameter dispersion gradient (PADG) as the new fluid factor. PADG is dependent both on average fracture radius and fluid type but independent on azimuths. When the aligned fractures in the reservoir are meter-scaled, gas-bearing layer could be accurately identified using PADG attribute. The reflection coefficient formula for horizontal transverse isotropy media by Rüger is reformulated and simplified according to frequency and the target function for inverting PADG based on frequency-dependent amplitude versus azimuth is derived. A spectral decomposition method combining Orthogonal Matching Pursuit and Wigner–Ville distribution is used to prepare the frequency-division data. Through application to synthetic data and real seismic data, the results suggest that the method is useful for gas identification in reservoirs with meter-scaled fractures using high-qualified seismic data. |
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