Monogenic signal decomposition: A new approach to enhance magnetic data

Abstract

The magnetic method is well-known as one of the most powerful tools used to map concealed geological structures especially those associated with magnetic crystalline basements. Crystalline basements play an important role for oil and gas exploration in sedimentary basins because they influence the geology of the overlying sedimentary rocks and subsequently the formation of their oil and gas plays. Magnetic data from sedimentary structures are in general characterized by their low susceptibility contrast and poor signal-to-noise ratio and it is often challenging to extract subtle geological features from these data. Therefore, image enhancement techniques are very vital for extracting optimum geological and structural information from magnetic data. In this abstract, a new magnetic image enhancement approach is proposed. This approach is based on a recently developed digital processing technique known as monogenic signal decomposition. This new technique is able to decompose 2D magnetic signals into three primary attributes (amplitude, phase and orientation) and two secondary attributes (directional Hilbert and Riesz transforms). Although many magnetic attributes have been utilized to map subtle geologic features, these five particular attributes appear to add more valuable information to magnetic data interpretation. The aim of this study is therefore to explore the monogenic signal decomposition approach as an alternative technique to extract geological and structural information from magnetic data.