Seismic attributes not magic
A lot of geoscientist represent seismic attributes like magic wand that can solve all complex seismic interpretation problems, seismic attributes need very good workflows and should have good and known physical meaning, some geoscientist build fault interpretation workflow depend on curvature attributes and applying this attributes without any preconditioning and without know the direction of faults or understanding different between strike or dip curvature, negative or positive curvature ,Curvature attributes are excellent attributes but it is the most sensitive attributes for noise effect .
Another mistake when geoscientist use window attributes between horizons or along time slice usually when attributes used for channels they used window attributes and forget the contamination from noise or from unimportant geological features, there are a lot of window attribute like RMS, AVERAGE ENERGY, ENVELOPE, NEGATIVE, POSITIVE,… etc. seismic interpreters should to know of the properties of the interested geobodies .
Many geoscientist use seismic attributes without understanding relation with their targets, they used attributes to detect geobodies or identify reservoir properties and forge seismic attributes can led to wrong direction (misleading), geoscientist told me they used many attributes to detect target but they didn't understand what is physical meaning of them.
One of important development tools in seismic attribute analysis is flying test that can help interpreter to test seismic attributes parameter before applying in all volume this really amazing properties and interactively you can test all parameters of seismic attributes , it is recommend to all geoscientist to test parameter before applying seismic attribute to all volumes.
The famous question what is best seismic attribute for my target , really it is difficult question all my trainees asked this question , the answer is simple start from simple and understandable attributes there are no rule but there are experiences, start from similarity attributes to detect edge of geobodies or structures features, start with envelope and average energy, sweetness for detect hydrocarbon , start from acoustic impedance, envelop, frequency, amplitude for lithology.
