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Amplitude variation with incident angle and azimuth inversion for Young's impedance, Poisson's ratio and fracture weaknesses in shale gas reservoirs
Author(s) -
Pan Xinpeng,
Zhang Guangzhi
Publication year - 2019
Publication title -
geophysical prospecting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.735
H-Index - 79
eISSN - 1365-2478
pISSN - 0016-8025
DOI - 10.1111/1365-2478.12783
Subject(s) - transverse isotropy , geology , poisson's ratio , poisson distribution , amplitude , isotropy , fracture (geology) , lithology , azimuth , anisotropy , mechanics , seismology , geometry , mineralogy , geotechnical engineering , optics , physics , petrology , mathematics , statistics
By analogy with P‐ and S‐wave impedances, the product of Young's modulus and density can be termed as Young's impedance, which indicates the rock lithology and brittleness of unconventional hydrocarbon reservoirs. Poisson's ratio is also an effective indicator of rock brittleness and fluid property of unconventional reservoirs, and fracture weaknesses indicate the fracture properties (fracturing intensity and fracture fillings) in fracture‐induced unconventional reservoirs. We aim to simultaneously estimate the Young's impedance, Poisson's ratio and fracture weaknesses from wide‐azimuth surface seismic data in a fracture‐induced shale gas reservoir, and use the horizontal transversely isotropic model to characterize the fractures. First, the linearized PP‐wave reflection coefficient in terms of Young's impedance, Poisson's ratio, density and fracture weaknesses is derived for the case of a weak‐contrast interface separating two weakly horizontal transversely isotropic media. In addition, an orthorhombic anisotropic case is also discussed in this paper. Then a Bayesian amplitude variation with incident angle and azimuth scheme with a model constraint is used to stably estimate Young's impedance, Poisson's ratio and fracture weaknesses with only PP‐wave azimuthal seismic data. The proposed approach is finally demonstrated on both synthetic and real data sets with reasonable results.

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