Elastic parameters derived from seismic data are valuable input for
reservoir characterization because they can be related to lithology
and fluid content of the reservoir through empirical relationships.
The relationship between physical properties of rocks and fluids
and P-wave seismic data is nonunique. This leads to large uncertainties
in reservoir models derived from P-wave seismic data. Because S-
waves do not propagate through fluids, the combined use of P-and
S-wave seismic data might increase our ability to derive fluid and
lithology effects from seismic data, reducing the uncertainty in
reservoir characterization and thereby improving 3D reservoir model-building.We
present a joint inversion method for PP and PS seismic data by solving
approximated linear expressions of PP and PS reflection coefficients
simultaneously using a least-squares estimation algorithm. The resulting
system of equations is solved by singular-value decomposition (SVD).
By combining the two independent measurements (PP and PS seismic
data), we stabilize the system of equations for PP and PS seismic
data separately, leading to more robust parameter estimation. The
method does not require any knowledge of PP and PS wavelets.We tested
the stability of this joint inversion method on a 1D synthetic data
set. We also applied the methodology to North Sea multicomponent
field data to identify sand layers in a shallow formation. The identified
sand layers from our inverted sections are consistent with observations
from nearby well logs.
%0 Journal Article
%1 veire_landro:2006
%A Veire, Helene H.
%A Landrø, Martin
%D 2006
%I SEG
%J Geophysics
%K geophysics seismics
%N 3
%P R1--10
%R 10.1190/1.2194533
%T Simultaneous inversion of PP and PS seismic data
%U http://dx.doi.org/10.1190/1.2194533
%V 71
%X Elastic parameters derived from seismic data are valuable input for
reservoir characterization because they can be related to lithology
and fluid content of the reservoir through empirical relationships.
The relationship between physical properties of rocks and fluids
and P-wave seismic data is nonunique. This leads to large uncertainties
in reservoir models derived from P-wave seismic data. Because S-
waves do not propagate through fluids, the combined use of P-and
S-wave seismic data might increase our ability to derive fluid and
lithology effects from seismic data, reducing the uncertainty in
reservoir characterization and thereby improving 3D reservoir model-building.We
present a joint inversion method for PP and PS seismic data by solving
approximated linear expressions of PP and PS reflection coefficients
simultaneously using a least-squares estimation algorithm. The resulting
system of equations is solved by singular-value decomposition (SVD).
By combining the two independent measurements (PP and PS seismic
data), we stabilize the system of equations for PP and PS seismic
data separately, leading to more robust parameter estimation. The
method does not require any knowledge of PP and PS wavelets.We tested
the stability of this joint inversion method on a 1D synthetic data
set. We also applied the methodology to North Sea multicomponent
field data to identify sand layers in a shallow formation. The identified
sand layers from our inverted sections are consistent with observations
from nearby well logs.
@article{veire_landro:2006,
abstract = {Elastic parameters derived from seismic data are valuable input for
reservoir characterization because they can be related to lithology
and fluid content of the reservoir through empirical relationships.
The relationship between physical properties of rocks and fluids
and P-wave seismic data is nonunique. This leads to large uncertainties
in reservoir models derived from P-wave seismic data. Because S-
waves do not propagate through fluids, the combined use of P-and
S-wave seismic data might increase our ability to derive fluid and
lithology effects from seismic data, reducing the uncertainty in
reservoir characterization and thereby improving 3D reservoir model-building.We
present a joint inversion method for PP and PS seismic data by solving
approximated linear expressions of PP and PS reflection coefficients
simultaneously using a least-squares estimation algorithm. The resulting
system of equations is solved by singular-value decomposition (SVD).
By combining the two independent measurements (PP and PS seismic
data), we stabilize the system of equations for PP and PS seismic
data separately, leading to more robust parameter estimation. The
method does not require any knowledge of PP and PS wavelets.We tested
the stability of this joint inversion method on a 1D synthetic data
set. We also applied the methodology to North Sea multicomponent
field data to identify sand layers in a shallow formation. The identified
sand layers from our inverted sections are consistent with observations
from nearby well logs.},
added-at = {2012-09-01T13:08:21.000+0200},
author = {Veire, Helene H. and Landr{\o}, Martin},
biburl = {https://www.bibsonomy.org/bibtex/2759afe0765e690b4bf898fb18be624bb/nilsma},
day = 1,
doi = {10.1190/1.2194533},
interhash = {51d6156c81fdde7055c4dda8078d3835},
intrahash = {759afe0765e690b4bf898fb18be624bb},
journal = {Geophysics},
keywords = {geophysics seismics},
month = may,
number = 3,
pages = {R1--10},
publisher = {SEG},
timestamp = {2021-02-09T13:27:42.000+0100},
title = {Simultaneous inversion of PP and PS seismic data},
url = {http://dx.doi.org/10.1190/1.2194533},
volume = 71,
year = 2006
}