TY - GEN

T1 - Elastic rock properties influencing factors - Mineralogy, porosity and microstructure

AU - Dertnig, F.

AU - Gegenhuber, N.

PY - 2018/1/1

Y1 - 2018/1/1

N2 - We present data from laboratory measurements of elastic properties of different lithologies. Measurements were carried out on plugs with 25 mm diameter and 22 mm length in dry and brine saturated conditions with an ultrasonic device. Thin sections had been used to obtain mineralogy and microstructures of the samples. For model calculations (Schön, 2015) the host materials compressional- and shear modulus were calculated from mineral composition (from thin sections) but also derived from the empirical data by extrapolation for zero porosity. Bound models of Voigt (1910) and Reuss (1929) were used to calculate upper and lower boundary respectively. Further also the generalization of Lichtenecker and Rother (1931) with the exponent α was applied and used to subgroup the data. Analogous we applied exponential approximation curves (using another exponent β) which helped to automatically divide the data into the subgroups similar to the α-values. The α- and the corresponding β-values describe data groups with similar microstructural parameters and changing porosity. Overall we found out that the empirically derived host material parameters worked better for our approach.

AB - We present data from laboratory measurements of elastic properties of different lithologies. Measurements were carried out on plugs with 25 mm diameter and 22 mm length in dry and brine saturated conditions with an ultrasonic device. Thin sections had been used to obtain mineralogy and microstructures of the samples. For model calculations (Schön, 2015) the host materials compressional- and shear modulus were calculated from mineral composition (from thin sections) but also derived from the empirical data by extrapolation for zero porosity. Bound models of Voigt (1910) and Reuss (1929) were used to calculate upper and lower boundary respectively. Further also the generalization of Lichtenecker and Rother (1931) with the exponent α was applied and used to subgroup the data. Analogous we applied exponential approximation curves (using another exponent β) which helped to automatically divide the data into the subgroups similar to the α-values. The α- and the corresponding β-values describe data groups with similar microstructural parameters and changing porosity. Overall we found out that the empirically derived host material parameters worked better for our approach.

UR - http://www.scopus.com/inward/record.url?scp=85067947379&partnerID=8YFLogxK

M3 - Conference contribution

T3 - 80th EAGE Conference and Exhibition 2018: Opportunities Presented by the Energy Transition

BT - 80th EAGE Conference and Exhibition 2018

T2 - 80th EAGE Conference and Exhibition 2018: Opportunities Presented by the Energy Transition

Y2 - 11 June 2018 through 14 June 2018

ER -