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Monitoring overburden layer changes and fault movements from time‐lapse seismic data on the Valhall Field
Author(s) -
Røste Thomas,
Landrø Martin,
Hatchell Paul
Publication year - 2007
Publication title -
geophysical journal international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.302
H-Index - 168
eISSN - 1365-246X
pISSN - 0956-540X
DOI - 10.1111/j.1365-246x.2007.03369.x
Subject(s) - geology , overburden , geodesy , seismology , geomechanics , seabed , geophysics , geotechnical engineering , oceanography
SUMMARY A method developed by Røste et al. , which discriminates between layer thickness and velocity changes, is tested on pre‐stack time‐lapse seismic ocean bottom cable (OBC) data from the Valhall Field. A key parameter in this discrimination process is the dilation factor, α, which is the relative velocity change divided by the relative thickness change within a given layer. The high quality and good repeatability of the OBC data enables us to estimate α with a reasonable accuracy for α‐values between 0 and −5. For α‐values below −5, complementary information, like for instance geomechanics is required. For the top reservoir horizon we estimate a maximum subsidence of 0.50 m ± 0.29 m and a corresponding velocity decrease for the sequence from the seabed to the top reservoir of 2.0 m s −1 ± 0.40 m s −1 . Time‐lapse distortion patterns with characteristic time‐shift versus offset signatures are observed. The positions and vertical extents of the distortion zones are determined from ray path considerations and modelling. The distortion zones correlate with buried faults, indicating that a (time‐lapse) distortion zone might be produced by a localized slip in a fault zone. We present an extended method which allows for vertical (in addition to lateral) variations in the relative thickness and velocity changes. This method can be viewed as a simplified version of time‐lapse tomography, but involving fewer unknown parameters, giving more stability to the estimated changes in thickness and velocity. Using this technique, we are able to estimate α for positions with localized time‐lapse distortions.

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