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GCRelative Acoustic Impedance Defines Thin Reservoir Horizons*
Satinder Chopra1, John P. Castagna2 and Yong Xu1
Search and Discovery Article #40435 (2009)
Posted July 23, 2009
*Adapted from the Geophysical Corner
column, prepared by the authors, in AAPG Explorer, July, 2009, and entitled
“Thin Is In: Here's a Helpful Attribute
”. Editor of Geophysical Corner is Bob
A. Hardage
([email protected]). Managing Editor of AAPG Explorer is Vern Stefanic; Larry Nation is Communications Director.
1Arcis Corp., Calgary, Canada
2University of Houston/Fusion Geo Inc., Houston, TX
And now, the rest of the story … You may recall that a novel poststack inversion method was discussed in the May 2008 Geophysical Corner (http://www.searchanddiscovery.net/documents/2008/jw0808chopra/index.html?q=%2Btext%3Achopra); the output from the method described in that article was a reflectivity series that had a resolution superior to that of the input data used to generate the reflectivity response. Some applications of this inversion method were discussed in the 2008 article. Here we illustrate another application of that 2008 reflectivity calculation that aids in quantifying numerous geological features – with the emphasis here being on thin beds.
Many flow units within reservoirs are thin layers that
are below seismic
resolution, because their thickness is less than one-eighth
of the dominant wavelength of the illuminating wavefield, causing the unit to
not be resolved seismically. Determining the actual thicknesses of such thin
layers is an important task for many geophysicists. We achieve this objective
of quantifying thin-bed thickness by a two-step process:
First, invert
the
seismic
amplitudes into a reflectivity series using spectral inversion (the
topic discussed in the May 2008 article).
Second, transform this reflectivity
series into relative impedance layers. This step is a trace-by-trace
calculation process and can be computed quickly.
Impedance profiles can be represented as either absolute impedances, which have magnitudes equivalent to the magnitudes of log data measured across targeted intervals, or as relative impedances, which have arbitrary amplitudes that show depth-dependent variations equivalent to those exhibited by log data. We emphasize here the option of calculating relative impedances. When interpreting relative impedance profiles, the top and bottom reflection boundaries of a unit are not correlated with well log curves. Instead, the thicknesses of relative impedance layers are correlated with log curve shapes.
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On Figure 1
we
illustrate how a 50-meter thick carbonate reef can be distinguished from the
base platform carbonate unit that it rests on. As indicated on Figure 1a, the frequency bandwidth of the prestack
time-migrated (PSTM)
Figure 2
shows a vertical section through thin-bed impedance data calculated
across a Far East offshore area. This profile follows the trajectory of a
horizontal oil producer labeled Well C, which targeted a seven-meter thick
sand that was previously encountered in wells A and B. This sand thickness is
well below the tuning thickness of the
Our final example shows how relative impedance data helped to distinguish individual sands in a stacked sand sequence. Figure 3 shows sections through:
(a) A prestack depth migrated volume (PSDM), also from a Far East offshore area. (b) An absolute impedance inversion volume. (c) A relative impedance inversion data volume.
The log curve is the gamma-ray response that shows
an upper dirty sand A, a middle clean sand B and a reservoir in the basal
part of sand C. The poor frequency content of the
Relative acoustic impedance calculated from a
thin-bed reflectivity series is a useful
We thank two anonymous companies for permission to publish the examples shown here. The thin-bed reflectivity method mentioned here is commercially referred to as ThinManTM, a trademark owned by FusionGeo, Houston.
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