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The Adaptive Well Logging Data Interpretation in Gassmann's Fluid Substitution Modeling

Deshenenkov, Ivan S.*1; Kozhevnikov, Dmitry A.1; Kovalenko, Kazimir V.1
(1) Well Logging, Gubkin Russian State University of Oil and Gas, Moscow, Russian Federation.

Seismic data analysis is a key technology for characterizing reservoirs and monitoring subsurface pore fluids. Rock physics is a link between seismic and logging data; it’s applied to predict reservoir parameters, such as lithologies and pore fluids, from seismically derived attributes. This work considers advances in fluid effects on reservoirs elastic properties modeling.

Fluid substitution procedure is the rock physics technique for understanding how seismic velocity and impedance depend on pore fluids. At the heart of the fluid substitution problem are Gassmann's (1951) relations, which predict the rock modulus variation with a change of pore fluids.

For the fluid substitution problem there are two fluid effects that must be considered: the change in rock bulk density, and the change in rock compressibility. For modeling of these effects it is essential to have information about reservoirs components properties and volume contents, which is usually unavailable. Some averaged properties values are used this case that significantly decreases accuracy and reliability of modeling results.

Gassmann's relations, like many rock physics models, are derived assuming a homogeneous mineralogy with monomineralic matrix and cement. This approach doesn’t reflect real rocks mineral composition and goes to additional uncertainties in fluid substitution results as petrophysical characteristics do not remain unchanged in lithological & geochemical processes that involves in secondary minerals transformation while hydrochemical environment changes.

To overcome listed shortcomings we establish a new way of Gassmann's relation application for fluid effect on elastic properties simulation. Elastic modulus are determined by means of the adaptive log data interpretation technology and characteristic parameters dealt with the totality of reservoir components petrophysical characteristics and well measurements technical conditions.

Characteristic parameters are determined with well logging data interpretation (by means of each logs petrophysical parameters pairwise comparison) and core data analysis (with relation between total porosity and residual water saturation). The tuning of characteristic parameters could be performed also with petrophysical zoning.

Modified Gassmann's fluid substitution modeling with adaptive technology provides seismic attributes simulation, which reflects saturation changes more accurately in comparison with conventional Gassmann's relation.


AAPG Search and Discovery Article #90142 © 2012 AAPG Annual Convention and Exhibition, April 22-25, 2012, Long Beach, California