Abstract
Many of the geophysical data-analysis problems such as signal-noise separation and data regularization are convenientlyformulatedinatransformdomain,inwhichthesignal appears sparse. Classic transforms such as the Fourier transformorthedigitalwavelettransformDWTfailoccasionally in processing complex seismic wavefields because of the nonstationarityofseismicdataintimeandspacedimensions. Wepresentasparsemultiscaletransformdomainspecifically tailored to seismic reflection data. The new wavelet-like transform — the OC-seislet transform — uses a differential offset-continuation OC operator that predicts prestack reflectiondatainoffset,midpoint,andtimecoordinates.Itprovides a high compression of reflection events. Its compressionpropertiesindicatethepotentialofOCseisletsforapplications such as seismic data regularization or noise attenuation. Results of applying the method to synthetic and field dataexamplesdemonstratethattheOC-seislettransformcan reconstructmissingseismicdataandeliminaterandomnoise eveninstructurallycomplexareas.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
