3D interpolation and extrapolation of sparse well data using rock-physics principles: Applications to anisotropic velocity model building

2014 ◽  
Vol 33 (3) ◽  
pp. 248-254 ◽  
Author(s):  
Ran Bachrach ◽  
Konstantin Osypov
2011 ◽  
Author(s):  
Ran Bachrach ◽  
Yangjun (Kevin) Liu ◽  
Marta Woodward ◽  
Olga Zradrova ◽  
Yi Yang ◽  
...  

2018 ◽  
Author(s):  
Huy Le ◽  
Anshuman Pradhan ◽  
Nader C. Dutta ◽  
Biondo Biondi ◽  
Tapan Mukerji ◽  
...  

2013 ◽  
Vol 61 (2) ◽  
pp. 404-415 ◽  
Author(s):  
Ran Bachrach ◽  
Konstantin Osypov ◽  
Dave Nichols ◽  
Yi Yang ◽  
Yangjun Liu ◽  
...  

2019 ◽  
Author(s):  
Jianchun Dai ◽  
Dawn Jantz ◽  
Zengbao Chen ◽  
Claire Jacob ◽  
Daniel Smith ◽  
...  

Geophysics ◽  
2016 ◽  
Vol 81 (5) ◽  
pp. C205-C218 ◽  
Author(s):  
Yunyue Li ◽  
Biondo Biondi ◽  
Robert Clapp ◽  
Dave Nichols

Velocity model building is the first step of seismic inversion and the foundation of the subsequent processing and interpretation workflow. Velocity model building from surface seismic data only becomes severely underdetermined and nonunique when more than one parameter is needed to characterize the velocity anisotropy. The traditional seismic processing workflow sequentially performs seismic velocity model building, structural imaging/interpretation, and lithologic inversion, modifying the subsurface model in each step without verifications against the previously used data. We have developed an integrated model building scheme that uses all available information: seismic data, geologic structural information, well logs, and rock-physics knowledge. We have evaluated the accuracy of the anisotropic model in the image space, in which structural information is estimated. The lithologic inversion results from well logs and the dynamic seismic information (amplitude versus angle) are also fed back to the kinematic seismic inversion via a cross-parameter covariance matrix, which is a multivariate Gaussian approximation to the numerical distribution modeled from stochastic rock-physics modeling. The procedure of building the rock-physics prior information and the improvements using these extra constraints were tested on a Gulf of Mexico data set. The inverted vertical transverse isotropic model not only better focused the seismic image, but it also satisfied the geologic and rock-physics principles.


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