Automated Amplitude and Phase Attribute-Based Horizon Picking Applied to 3-D Sub-bottom Data

Abstract

The 3-D sub-bottom profiler (SBP) is widely used for observing sub-bottom structures due to its high resolution and spatial coverage. However, traditional picking methods are limited by scattering noise and imbalanced intensity, resulting in poor picking of reflections with weak intensities and overpicking due to scattering noise. This limitation has hindered the development of 3-D SBP processing technologies relative to the widespread applications. In this article, we present a 3-D SBP horizon-picking method that takes into account both amplitude and phase information. First, we apply an amplitude data enhancement filtering algorithm considering the plate-like structure and the nonvertical characteristic to avoid scattering noise interference and highlight plate-like horizon features. Subsequently, a threshold-based algorithm is applied to pick the amplitude horizons, reflecting the main structures of layer interfaces based on the processed amplitude data. Then, the local phase information of the SBP data is derived through the monogenic analysis, and phase horizons are picked, which can describe detailed reflections with weak intensities, although overpicking may occur. To leverage both amplitude and phase horizons, a combination method is proposed to ensure continuous and fine horizon picking containing both main and detailed 3-D SBP horizon structures. The method was validated by comparing automated horizon results with manual results using experimental data. A total of 87% and 86% F-measures were achieved on two data sets, respectively.