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Data‐driven rock physics analysis of North Sea tertiary reservoir sands
Author(s) -
Avseth Per,
Lehocki Ivan,
Kjøsnes Øyvind,
Sandstad Odd
Publication year - 2021
Publication title -
geophysical prospecting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.735
H-Index - 79
eISSN - 1365-2478
pISSN - 0016-8025
DOI - 10.1111/1365-2478.12986
Subject(s) - facies , geology , predictability , economic geology , structural geology , homogeneous , data set , regional geology , mineralogy , geophysics , geotechnical engineering , hydrogeology , statistical physics , geomorphology , seismology , statistics , mathematics , physics , telmatology , metamorphic petrology , structural basin
We have demonstrated an approach for data‐driven rock physics analysis, where we first do facies classification using elastic well log data from several wells, followed by facies‐constrained regression analysis to establish local rock physics relations for the prediction of V P and V S from geological input parameters. We have applied this approach to a multi‐well log data set (53 wells, 40 of which had reliable/useful data) from the greater Alvheim area. We show how we can derive very robust local empirical rock physics relations for the prediction of P‐wave and S‐wave velocities as well as densities, for given combinations of porosity and clay volume. These locally derived empirical relations are recommended instead of universal rock physics models, even when the latter are locally calibrated. Using elastic facies with geological characteristics (cemented versus unconsolidated; normally compacted versus injectites; homogeneous versus heterogeneous) helps to improve the predictability of the regression models. The local rock physics relations that we obtain can furthermore be used to create training data for AVO classification.