Once a satisfactory Fault Likelihood Volume is created, extraction of fault surfaces is much easier. Instead, planar features within a specified strike and dip range are highlighted. In general, these volumes contain less noise and do not emphasize stratigraphic features. Hale (2013) presents a method to improve on these datasets by creating what is referred to as a Fault Likelihood volume. These products highlight discontinuities, but still need a large amount of human interaction to interpret faults and are plagued by noise and stratigraphic discontinuities. With the improvement of technology, the interpretation of faults can be expedited with the aid of different algorithms that create supplementary seismic attributes, such as semblance and coherency. Automated Fault Interpretation and Extraction using Improved Supplementary Seismic DatasetsÄuring the interpretation of seismic volumes, it is necessary to interpret faults along with horizons of interest.
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