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An insightful parametrization for the flatlander's interpretation of time‐lapsed seismic data
Author(s) -
Alvarez Erick,
MacBeth Colin
Publication year - 2014
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 - 10.1111/1365-2478.12071
Subject(s) - geology , saturation (graph theory) , parametrization (atmospheric modeling) , seismic inversion , porosity , interpretation (philosophy) , earth model , inversion (geology) , engineering geology , pore water pressure , clastic rock , mineralogy , seismology , mathematics , geotechnical engineering , geometry , paleontology , physics , sedimentary rock , radiative transfer , computer science , quantum mechanics , combinatorics , azimuth , volcanism , tectonics , programming language
An approximation is developed that allows mapped 4D seismic amplitudes and time‐shifts to be related directly to the weighted linear sum of pore pressure and saturation changes. The weights in this relation are identified as key groups of parameters from a petroelastic model and include the reservoir porosity. This dependence on groups of parameters explains the inherent non‐uniqueness of this problem experienced by previous researchers. The proposed relation is of use in 4D seismic data feasibility studies and inversion and interpretation of the 4D seismic response in terms of pore pressure and water saturation changes. A further result is drawn from analysis of data from the North Sea and West Africa, which reveals that the relative interplay between the effects of pore pressure and saturation changes on the seismic data can be simplified to the control of a single, spatially variant parameter C S /C P . Combining these results with those from published literature, we find that C S /C P = 8 appears to be a generality across a range of clastic reservoirs with a similar mean porosity. Using this C S /C P value, an in situ seismic‐scale constraint for the rock stress sensitivity component of the petroelastic model is constructed considering this component carries the largest uncertainty.