Investigation of the Structure and Lithology of Bedrock Concealed by Basin Fill, Using Ground-Based Magnetic-Field-Profile Data Acquired in the San Rafael Basin, Southeastern Arizona

Abstract

Data on the Earth’s total-intensity magnetic field acquired near ground level and at measurement intervals as small as 1 m include information on the spatial distribution of nearsurface magnetic dipoles that in many cases are unique to a specific lithology. Such spatial information is expressed in the texture (physical appearance or characteristics) of the data at scales of hundreds of meters to kilometers. These magnetic textures are characterized by several descriptive statistics, their power spectrum, and their multifractal spectrum. On the basis of a graphical comparison and textural characterization, ground-based magnetic-field profile data can be used to estimate bedrock lithology concealed by as much as 100 m of basin fill in some cases, information that is especially important in assessing and exploring for concealed mineral deposits. I demonstrate that multifractal spectra of ground-based magnetic-field-profile data can be used to differentiate exposed lithologies and that the shape and position of the multifractal spectrum of the ground-based magnetic-field-profile of concealed lithologies can be matched to the upward-continued multifractal spectrum of an exposed lithology to help distinguish the concealed lithology.

In addition, ground-based magnetic-field-profile data also detect minute differences in the magnetic susceptibility of rocks over small horizontal and vertical distances and so can be used for precise modeling of bedrock geometry and structure, even when that bedrock is concealed by 100 m or more of nonmagnetic basin fill. Such data contain valuable geologic information on the bedrock concealed by basin fill that may not be so visible in aeromagnetic data, including areas of hydrothermal alteration, faults, and other bedrock structures. Interpretation of these data in the San Rafael Basin, southeastern Arizona, has yielded results for estimating concealed lithologies, concealed structural geology, and a concealed potential mineral-resource target.

First posted May 17, 2013