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3D AVO crossplotting—An effective visualization technique

Core Laboratories Reservoir Technologies Division, Calgary, Alberta, Canada

Corresponding author: schopra@corelab.ca

The first 20% of the full text of this article appears below.

Crossplots, visual representations of the relationship between two variables, are used to (a) visually identify outliers that may bias a correlation, (b) gain a visual sense for the strength of the correlation between variables, (c) detect if the relationship between variables is linear or nonlinear, (d) identify trends which may indicate multiple populations within the same data set, and (e) detect significant departures from a background trend—in other words to detect anomalies.

Crossplotting is widely used in AVO analysis, because it facilitates the simultaneous and meaningful evaluation of two attributes. Generally, common lithology units and fluid types cluster together in AVO crossplot space, allowing identification of background lithology trends and anomalous off-trend aggregations that could be associated with hydrocarbons.

Initially, AVO crossplotting typically used the intercept and gradient. However, in 1997, Goodway et al. used crossplots of elastic parameters (Lambda-Rho and Mu-Rho) to improve petrophysical discrimination of rock properties. Other attributes have also been used as AVO anomaly indicators (Castagna and Smith, 1994). Crossplotting appropriate pairs of attributes so that common lithologies and fluid types generally cluster together allows for straightforward interpretation. The off-trend aggregations can then be more elaborately evaluated as potential hydrocarbon indicators. This is the essence of successful AVO crossplot analysis and interpretation, all of which is based on the premise that data that are anomalous statistically are interesting geologically.

This article describes attempts to extend crossplotting to three dimensions and assess any advantages that result. Ross and Sparlin (2000) made this extension by using the intercept, gradient, and inlines for a 3D seismic volume as the three dimensions on a 3D crossplot.

Our procedure begins by first visualizing different combinations of the measured well-log parameters (P-velocity, S-velocity, density, porosity, and gamma ray) in two and three dimensions. Next, observed patterns are visualized and compared in the . . . [Full Text of this Article]