PATTERN RECOGNITION IN A DIGITAL AGE: A GAMEBOARD APPROACH TO DETERMINING PETROPHYSICAL PARAMETERS

摘要

Graphical pattern recognition interpretive techniques have been part of petrophysics since quantitative interpretation began, as a way to quickly determine properties of interest with a minimum of calculations. When calculators and computers were introduced to petrophysics, the focus of the techniques changed from determining the quantities themselves to determining the parameters needed to calculate those quantities. As an example, Hingle plots (1959) and Pickett plots (1966, 1973), first used to quickly determine water saturation for a few points in a reservoir, can now instead be used to determine the parameters needed in Archie’s (1942) water saturation equation, so that the parameters and associated well log data can be used to calculate water saturation in much more detail and with more precision than before.An extension of those graphical techniques is shown here, where Hingle, Pickett, and Buckles (1965) plots (Morris and Biggs, 1967) are displayed simultaneously. In this “gameboard” display in Excel (©Microsoft), data is displayed on all the plots. The selection and modification of computational parameters is immediately reflected in all plots, leading to a more coherent prediction of those parameters than from the same plots used independently.Pickett plots, with bulk volume water lines added as shown by Greengold (1986), Hingle plots, with bulk volume water lines added as shown by Krygowski and Cluff (2012), and Buckles plots (using both linear and logarithmic scales) can predict in a common environment the following parameters: Matrix parameters to derive porosity from bulk density or sonic slowness, Archie porosity (cementation) exponent (m), saturation exponent (n), and water resistivity (Rw), and irreducible bulk volume water (BVWirr).The display uses those three plots not commonly displayed simultaneously, and has the plots linked so that changes made to the parameters determined from one plot are reflected in the other plots and the computations derived from those plots.By being able to change the values of any of the parameters while seeing how those changes impact the other parameters and the calculated porosity, water saturation, and bulk volume water, the user can quickly try different interpretive scenarios and determine which results best honor all the data at hand. Other information, such as from core measurements, can limit or set the values of some of the parameters while still allowing the values of other parameters to be determined in the context of that other data.