Summary
The exploration target of the pre-salt region from Brazilian offshore basins pose requires extensive use of pre- and post-stack processing and visualization techniques. In the post-stack domain extracting information from seismic data is generally associated with seismic attribute generation. In this research a methodology of seismic interpretation though the ability to examine and compare the response of different attributes combined in blend volumes is presented. Input volumes for blending used in this research were generate from frequency decomposition and structural attributes using RBG (Red-Blue-Green) and CMY (Cyan-Magenta-Yellow) color schemes.
Significant amount of information seen in color blended images relates to geological structures whose geometry cannot be easily extracted by horizons; for example, carbonate build-ups, channels, fan systems, salt bodies, gas chimneys, karsts, injectites, etc. Results from sandstone and carbonate depositional settings are presented.
Introduction
In the new cycle of operation in the basins of the Brazilian east coast Petrobras found the difficulty in seismic characterization of porous carbonate reservoirs and sandstones. Interpreters has since sought improvements for viewing and characterization of exploration targets through seismic processing and post-processing and use of various seismic attributes that show geometric lithological and structural characteristics of reservoirs.
The data used in this work are characterized by low content of high frequencies and the presence of coherent and random noise, translated into low seismic resolution, especially in the pre-salt section. For these reasons the exploration risk factors are high especially where no wells were drilled.
With the advancement in display technologies color blending of seismic attributes workflow have become viable in exploration settings. The process of color blend mixes three volumes associating them with color channels in RGB schemes, CMY or HSV, enabling greater efficiency in the interpretation (Henderson et al, 2008;. Henderson et al., 2007). The volumes of color blend identify the relationships between different attributes.
