A genetic meta-algorithm-assisted inversion approach: hydrogeological study for the determination of volumetric rock properties and matrix and fluid parameters in unsaturated formations

Journal Article · Sat Sep 15 04:00:00 EDT 2018 · Hydrogeology Journal

DOI:https://doi.org/10.1007/S10040-018-1749-7· OSTI ID:22780851

An evolutionary inversion approach is suggested for the interpretation of nuclear and resistivity logs measured by direct-push tools in shallow unsaturated sediments. The efficiency of formation evaluation is improved by estimating simultaneously (1) the petrophysical properties that vary rapidly along a drill hole with depth and (2) the zone parameters that can be treated as constant, in one inversion procedure. In the workflow, the fractional volumes of water, air, matrix and clay are estimated in adjacent depths by linearized inversion, whereas the clay and matrix properties are updated using a float-encoded genetic meta-algorithm. The proposed inversion method provides an objective estimate of the zone parameters that appear in the tool response equations applied to solve the forward problem, which can significantly increase the reliability of the petrophysical model as opposed to setting these parameters arbitrarily. The global optimization meta-algorithm not only assures the best fit between the measured and calculated data but also gives a reliable solution, practically independent of the initial model, as laboratory data are unnecessary in the inversion procedure. The feasibility test uses engineering geophysical sounding logs observed in an unsaturated loessy-sandy formation in Hungary. The multi-borehole extension of the inversion technique is developed to determine the petrophysical properties and their estimation errors along a profile of drill holes. The genetic meta-algorithmic inversion method is recommended for hydrogeophysical logging applications of various kinds to automatically extract the volumetric ratios of rock and fluid constituents as well as the most important zone parameters in a reliable inversion procedure.

• OSTI ID: 22780851
• Journal Information: Hydrogeology Journal, Journal Name: Hydrogeology Journal Journal Issue: 6 Vol. 26; ISSN 1431-2174
• Country of Publication: United States
• Language: English

Related Subjects

58 GEOSCIENCES
AIR
BOREHOLES
CLAYS
DEPTH
GENETIC ALGORITHMS
GEOPHYSICS
HUNGARY
HYDROLOGY
MATHEMATICAL SOLUTIONS
OPTIMIZATION
RELIABILITY
ROCKS
SEDIMENTS
WATER