Semi-automatic mapping for identifying complex geobodies in seismic images

Abstract

Seismic images are composed of positive and negative seismic wave traces with different amplitudes (Robein 2010 Seismic Imaging: A Review of the Techniques, their Principles, Merits and Limitations (Houten: EAGE)). The association of these amplitudes together with a color palette forms complex visual patterns. The color intensity of such patterns is directly related to impedance contrasts: the higher the contrast, the higher the color intensity. Generally speaking, low impedance contrasts are depicted with low tone colors, creating zones with different patterns whose features are not evident for a 3D automated mapping option available on commercial software. In this work, a workflow for a semi-automatic mapping of seismic images focused on those areas with low-intensity colored zones that may be associated with geobodies of petroleum interest is proposed. The CIE L∗A∗B∗ color space was used to perform the seismic image processing, which helped find small but significant differences between pixel tones. This process generated binary masks that bound color regions to low-intensity colors. The three-dimensional-mask projection allowed the construction of 3D structures for such zones (geobodies). The proposed method was applied to a set of digital images from a seismic cube and tested on four representative study cases. The obtained results are encouraging because interesting geobodies are obtained with a minimum of information.