The curvelet domain modelling and inversion method to attenuate “black triangle” noise for vibroseis desert data

Abstract

Summary Vibroseis data acquired in desert areas are typically contaminated by “black triangle” noise. This kind of coherent noise is distributed in a triangular cone in the 3D shot gather and its energy accounts for more than 80% of the vibrator source excitation. Different from scattered surface waves and ground roll, “black triangle” noise has strong energy in the whole frequency band with variable characteristics, which makes it challenging to remove in vibroseis data processing. In this abstract, “black triangle’ noise is firstly predicted and removed from the vibroseis desert data with the curvelet domain modelling and inversion method. This special noise is modelled in the curvelet domain and reconstructed through iterative inversion. By building the objective function, the “black triangle” noise suppression problem is transformed into a sparse inversion problem. The field data test results show that the “black triangle” noise can be significantly attenuated from land seismic data sets with modelling and inversion method. Compared to traditional transform domain filtering, this method can preserve the target signals and improve the signal-to-noise ratio of the results.