Summary
Directional steered attributes are often used to delineate features that extend in a certain direction and to minimize the amount of noise captured. We present a new method that applies directional filters to several angles with a small increment on separate cubes. After which, the sum of these individual cubes is used which builds on the principle of superposition. If a feature is present in more than one direction, it will be further highlighted, and features such as noise, which are usually present only in a certain direction at time, are suppressed.
The objective of this study was to create a method that gives a more complete model of the faults networks, and as such, involved a Sobel based edge detection algorithm for delineating amplitude discontinuities. Though, we also included a gradient decent dip estimation to capture the phase changing faults.
When using seismic attributes, the results are very much dependent on the input. This is why we decided to validate our results by correlating them back to the original post stack seismic input. A comparison study was performed between traditional workflows for fault detection and extraction, with our method. The results showed that our method indeed gave a more accurate and precise model of the fault networks, and therefore gave a greater understanding of the structural geology in the region.