Abstract
Random noises in adjacent traces sometime exhibit coherence and correlation. The weighted stacking technique based on the conventional correlative function results in false events that are caused by the noises. Based on the theory of wavelets and high-order statistics, a high-order correlative weighted stacking technique is present in this paper. Its essence is to stack common midpoint gathers after the normal moveout correction by weights that are calculated through high-order correlative statistics in the wavelet domain. Synthetic examples demonstrate its advantages in improving the signal to noise ratio and compressing the correlative random noise.
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