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Aquifer structure identification using stochastic inversion
Author(s) -
Harp Dylan R.,
Dai Zhenxue,
Wolfsberg Andrew V.,
Vrugt Jasper A.,
Robinson Bruce A.,
Vesselinov Velimir V.
Publication year - 2008
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2008gl033585
Subject(s) - aquifer , inversion (geology) , inverse problem , probabilistic logic , geology , facies , stochastic simulation , mathematical optimization , computer science , mathematics , geotechnical engineering , groundwater , statistics , artificial intelligence , geomorphology , mathematical analysis , structural basin
This study presents a stochastic inverse method for aquifer structure identification using sparse geophysical and hydraulic response data. The method is based on updating structure parameters from a transition probability model to iteratively modify the aquifer structure and parameter zonation. The method is extended to the adaptive parameterization of facies hydraulic parameters by including these parameters as optimization variables. The stochastic nature of the statistical structure parameters leads to nonconvex objective functions. A multi‐method genetically adaptive evolutionary approach (AMALGAM‐SO) was selected to perform the inversion given its search capabilities. Results are obtained as a probabilistic assessment of facies distribution based on indicator cokriging simulation of the optimized structural parameters. The method is illustrated by estimating the structure and facies hydraulic parameters of a synthetic example with a transient hydraulic response.