The use of wavelet transforms for improved interpretation of airborne transient electromagnetic data

Abstract

The continuous wavelet transform (CWT) is used to create maps of dominant spatial scales in airborne transient electromagnetic (ATEM) data sets to identify cultural noise and topographic features. The introduced approach is applied directly to ATEM data, and does not require the measurements be inverted, though it can easily be applied to an inverted model. For this survey, we apply the CWT spatially to B-field and dB/dt ATEM data collected in the Edmonton-Calgary Corridor of southern Alberta. The average wavelet power is binned over four ranges of spatial scale and converted to 2D maps of normalized power within each bin. The analysis of approximately 2 million soundings that make up the survey can be run on the order of minutes on a 2.4 GHz Intel processor. We perform the same CWT analysis on maps of surface and bedrock topography and also compare ATEM results to maps of infrastructure in the region. We find that linear features identified on power maps that differ significantly between B-field and dB/dt data are well correlated with a high density of infrastructure. Features that are well correlated with topography tend to be consistent in power maps for both types of data. For this data set, use of the CWT reveals that topographic features and cultural noise from high-pressure oil and gas pipelines affect a significant portion of the survey region. The identification of cultural noise and surface features in the raw ATEM data through CWT analysis provides a means of focusing and speeding processing prior to inversion, though the magnitude of this affect on ATEM signals is not assessed.