Analysis of the use of multi-scale secondary data in geostatistical mapping

Abstract

A number of different techniques are currently used in the estimation of petrophysical properties away from hard data locations using a softer secondary data such as a seismic attribute. There are two problems that affect these techniques; firstly the relationship between the primary and secondary data is often very weak and secondly the measurement scale of the primary and secondary data is significantly different. Seismic data is usually well represented laterally but has a vertical resolution almost an order of magnitude larger than the well log data that is used as the primary data source.Currently the relationship between primary and secondary variable is quantified by a correlation coefficient and possibly a cross-variogram. Neither of these two measures capture the scale variability of the relationship or any location information between the two property fields. This paper investigates the use of the continuous wavelet transform as a way of examining the scale relationship between these two data sources with the aim of improving the understanding of the behaviour of primary data at different scales. The technique appears to indicate that there is also a potential improvement in the correlation between primary and secondary data once an appropriate comparison scale has been identified.This more robust method for determining the scale dependent relationship between primary and secondary data suggests a new estimation workflow that reduces the uncertainty associated with the estimation of primary data using secondary data sources.