The CROP dataset encompasses nearly 10,000 km of seismic sections. The marine part (8687.15 km) was performed from 1988 to 1995 by the RV OGS-Explora with an 80.4 liter airgun array and a 4500 m long, 180-channel streamer. The basic processing sequence focused on amplitude correction, multiple removal, deconvolution, velocity analysis, stacking, post-stack migration and time-variant filtering. Part of the marine dataset was re-processed to improve multiple attenuation, deep signal-to-noise ratio and imaging of structurally complex sectors. A proprietary Hough-transform-based algorithm was exploited to attenuate multiple events. Computation of instantaneous attributes by means of wavelet transform improved identification of weak signals in noisy background from deep crustal reflectors. Pre-stack imaging exploited the feedback from the interpretation phase to iteratively refine velocity–depth models and obtain optimum focusing of primary events. The latter interaction between processing and interpretation was the basis for the successful implementation and application of an interpretative strategy for deep crustal seismic data reprocessing.
