Comprehensive Sediment Horizon Picking From Subbottom Profile Data

Abstract

Manual horizon picking and semiautomatic horizon picking are the traditional methods for data processing of subbottom profiles (SBPs). However, the former is time consuming and laborsome, whereas the latter requires frequent manual intervention and easily suffers from low accuracy and discontinuous picking due to noises. A comprehensive and automatic horizon picking method is proposed by combining the given gray mutation, horizon tracking and filtering, and horizon growth algorithms in this paper. Based on the peaks and valleys corresponding to the strong and weak impedance contrasts in an echo sequence, the gray mutation is used to prepick horizons from a SBP image. According to sediment layer continuity and horizontal resolution, the horizon tracking and filtering are applied to construct discrete horizon segments and remove outliers. In consideration of the correlation of adjacent ping sequences and the horizon orientation, the horizon growth based on the horizon orientation constraints is utilized to connect the discrete horizon segments. Experiments validated the proposed method. The automatic horizon picking results were compared with the bore-hole data and the manual horizon picking results as well, and good consistencies were achieved. The determinations of parameters and the performance of the proposed method are discussed based on the theoretical study and experiments, and some conclusions are drawn.