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Rock Property Data Volumes from Well Logs*
By
L.R. Denham1 and H. Roice Nelson, Jr. 2
Search and Discovery Article #40266 (2007)
Posted November 3, 2007
*Adapted from extended abstract prepared for poster presentation at AAPG Annual Convention, Long Beach, California, April 1-4, 2007
1Interactive Interpretation & Training, Inc., Houston, TX ([email protected])
2Geokinetics Processing & Interpretation, Houston, TX
Abstract
Geology is sampled densely by wells vertically, but sparsely and irregularly horizontally. A modern seismic survey has sparse samples vertically, but close and uniform sampling horizontally. Seismic data is more useful for regional trends, but does not convey petrophysics, and is difficult to relate to wells. Inverting seismic data to resemble well data is almost impossible. Can we make well data resemble seismic data, not just a single-trace, but a complete volume?
We reduced
well vertical sample interval to 60 m, computing numerous petrophysical
properties. Then we computed vertical arrays of values for each property on a
regular grid, using the samples computed at each well location. Wells within a
specified radius were used
, weighted inversely with distance, and well samples
over a limited depth range, weighted inversely with depth difference from the
sample depth. The computed three-dimensional array was written to disk in SEG Y
format, and loaded into a seismic interpretation system.
In the
initial project we generated data volumes for shale and sand P-wave
velocities
and densities, sand percentage, and pressure (mud weight), for most of the Gulf
of Mexico. These volumes showed regional trends within the basin. The method has
some problems in areas of sparse well information, and does not account for
major structural features.
Petrophysical data volumes generated from well information allow the geologist to integrate information from thousands of wells using standard interpretation systems. So far, the technique seems to be more suited to regional analysis rather than to prospect development.
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Introduction One of
exploration’s perennial problems is relating well-derived geological
information to seismic data. An additional tool for this is now
available: data volumes of rock properties in SEG Y format, generated
from well logs. These volumes are compatible with all standard
seismic-interpretation systems and can be
How The Volumes Are Generated The starting point for the rock-property volumes is the standard suite of well logs. The standard set of rock properties in a dominantly clastic sequence is derived from velocity, density, and resistivity logs. Properties computed using fluid replacement require measurements or assumptions about properties of the fluids, such as oil and gas density, water salinity, and gas-oil ratio. Temperatures are based on measurements made while logging, and formation pressures are estimated from drilling mud weights. A petrophysicist classifies the rocks penetrated by each well, separating intervals into water-filled sand, shale, and all other lithologies (salt, coal, limestone, hydrocarbon-filled sand, etc.). These last intervals are excluded from the analysis. Wells are then divided into uniform depth intervals, using an interval large enough to contain significant quantities of both shale and water-filled sand, but small enough to adequately describe systematic variations. If the chosen interval is too small, many of the intervals will contain only sand, or only shale. If the interval is too large, there may be significant differences in rock properties from top to bottom, due to the difference in compaction, and more depth samples will include rocks with widely varying depositional environments. For the Gulf of Mexico examples described here, the interval chosen is 200 ft (61 m). For
each interval, the averages of the fundamental properties of sand and
shale are computed, along with the amounts of sand and shale within the
interval and the variation of each property within the interval
(recorded as standard deviation). Additional rock properties can be
computed from the fundamental properties using standard procedures such
as the Greenberg-Castagna technique (Greenberg and Castagna, 1992) for
computing shear-
Once the well database is constructed, the SEG Y data volumes can be generated. There are several points to consider carefully:
When these questions are answered, the volume is generated. The process follows these steps for each trace:
As each trace is completed, it is written in 32-bit floating point format to a standard SEG Y format file (Barry et al., 1975) which can be loaded into any seismic-interpretation system. The
generation of these volumes takes time, so we generate graphical
progress reports (updated every 1000 traces), allowing the user to check
that the values
Results The
data volumes are loaded into standard seismic-interpretation systems (in
this example, the Halliburton Landmark SeisWorks application), where
they can be manipulated in the same way as ordinary seismic data. Figure
4a shows the P- Figure 4b shows a section through the same data volume, running from the middle of the Green Canyon area on the left to the Sabine Pass area on the right. The gaps in the bottom of the section mark areas with no deep wells (or no deep logs). The missing data at the top of the section at the left is where velocity logs were not available at depths less than 7500 ft (2290 m) below water bottom (the last 5% of the section depends on a single well). The white line marks the depth of geopressure as interpreted by examination of each well.
Uses for the Volumes These
volumes have great
Suppose, for example, you have identified a The
variability of rock properties is important in estimating the
probability of success for a prospect. Figure 6c shows the standard
deviation of water-filled-sand velocities at 10,000 ft (3050 m) below
the sea floor. This is one indicator of the variability of sand
properties at this depth. Similar volumes can give actual measurements
of the variability of other properties At a simpler level, the interpreter may need to know whether an observed change in amplitude at an apparent fluid contact is compatible with a change from water to oil. This question could be answered by comparing the difference in values from an oil sand reflectivity volume and a wet sand reflectivity model with the change in amplitude observed in the real seismic data in an intercept stack volume. This would be a deterministic solution analogous to the probabilistic solution described by Denham and Johnson (2006). On an even more basic level, a gross overview can be quickly accessed, with mud weight (Figures 3a and 3b), for example, showing regional variations in geopressure at any depth.
Conclusions By
combining two universally-
References Barry, K.M., Cavers, D.A., and Kneale, C.W., 1975, Report on recommended standards for digital tape formats: Geophysics, v. 40, no. 2, p. 344–352. Denham, L.R., and Johnson, D., 2006, Estimating probability of hydrocarbon content from seismic amplitude anomalies: Soc. Explor. Geoph. 76th Annual Meeting, INT3.3. Gassmann, F., 1951, Elastic waves through a packing of spheres: Geophysics, v. 16, no. 4, p. 673–685.
Greenberg, M.L., and Castagna, J.P., 1992, Shear- Hilterman, F., Sherwood, J.W.C., Schellhorn, R., Bankhead, B., and DeVault, B., 1998, Identification of lithology in the Gulf of Mexico: The Leading Edge, v. 17, no. 2, p. 215–222. Hilterman, F., Verm, R., Wilson, M., and Liang, L., 1999, Calibration of rock properties for deepwater seismic: 69th Ann. Internat. Mtg, p. 65–68. Hilterman, F., 1990, Is AVO the seismic signature of lithology? A case history of Ship Shoal-south addition: The Leading Edge, v. 9, no. 6, p. 15–22.
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