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Geophysical‐hydrological identification of field permeabilities through Bayesian updating
Author(s) -
Copty Nadim,
Rubin Yoram,
Mavko Gary
Publication year - 1993
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/93wr00745
Subject(s) - permeability (electromagnetism) , bayesian probability , geology , inversion (geology) , soil science , synthetic data , seismic inversion , seismic to simulation , geophysics , geotechnical engineering , seismology , algorithm , computer science , data assimilation , meteorology , artificial intelligence , biology , genetics , tectonics , physics , membrane
A new Bayesian method is developed to identify the spatial distribution of permeabilities. In addition to sparsely sampled permeability and pressure data, this approach incorporates densely sampled seismic velocity data along with semiempirical relationships between seismic and hydraulic soil properties. The procedure consists first of performing a hydrological inversion based solely on the permeability and pressure data. In light of the available seismic data, the velocity‐permeability‐pressure relationships are then used to update, in a Bayesian sense, the image of the permeability field. To investigate the usefulness of this approach, synthetic case studies are performed. These studies demonstrate that, even when the seismic data are corrupted by a significant level of error, a joint geophysical‐hydrological inversion can produce improved images of permeability. Moreover, this paper derives rigorously the bounds on the error that can be tolerated in seismic velocities such that they are still useful for hydrological purposes.