Summary
We describe the successful application of a new prestack stochastic
inversion algorithm to the spatial delineation of thin reservoir units
otherwise poorly defined with deterministic inversion procedures. The inversion
algorithm effectively combines the high vertical resolution of wireline logs
with the relatively dense horizontal coverage of 3D prestack seismic amplitude
data. Multiple partial-angle stacks of seismic amplitude data provide the
degrees of freedom necessary to estimate spatial distributions of lithotype and
compressional-wave (P-wave) and shear-wave (S-wave) velocities in
a high-resolution stratigraphic/sedimentary grid. In turn, the estimated
volumes of P- and S-wave velocity permit the statistical
cosimulation of lithotype-dependent spatial distributions of porosity and
permeability.
The new stochastic inversion algorithm maximizes a Bayesian selection
criterion to populate values of lithotype and P- and S-wave
velocities in the 3D simulation grid between wells. Property values are
accepted by the Bayesian selection criterion only when they increase the
statistical correlation between the simulated and recorded seismic amplitudes
of all partial-angle stacks. Furthermore, inversion results are conditioned by
the predefined measures of spatial correlation (variograms) of the unknown
properties, their statistical cross correlation, and the assumed global
lithotype proportions.
Using field data acquired in a fluvial-deltaic sedimentary-rock sequence, we
show that deterministic prestack seismic-inversion techniques fail to delineate
thin reservoir units (10–15 m) penetrated by wells because of insufficient
vertical resolution and low contrast of elastic properties. By comparison, the
new stochastic inversion yields spatial distributions of lithotype and elastic
properties with a vertical resolution between 10-15m that accurately describe
spatial trends of clinoform sedimentary sequences and their associated
reservoir units.
Blind-well tests and cross validation of inversion results confirm the
reliability of the estimated distributions of lithotype and P- and
S-wave velocities. Inversion results provide new insight to the spatial
and petrophysical character of existing flow units and enable the efficient
planning of primary and secondary hydrocarbon recovery operations.
© 2009. Society of Petroleum Engineers
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History
- Original manuscript received:
30 June 2006
- Meeting paper published:
24 September 2006
- Revised manuscript received:
9 January 2009
- Manuscript approved:
29 July 2009
- Published online:
17 December 2009
- Version of record:
20 April 2010
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