Fei Li, Jun-fa Xie, Zong-hui Yao, Mei Li, Yu-lian Zhao, Wei-ming Liu, Juan Chen
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引用次数: 0
摘要
对地表起伏严重的复杂地下结构(即双重复杂区域)进行地震成像具有挑战性,因为很难收集到非常微弱的反射信号。即使采用最先进的多域和多维预叠加去噪技术,也很难增强微弱信号。本文介绍了基于 τ-p 变换的偏移矢量瓦(OVT)域数据时空倾斜分析。通过建立零偏移时空倾角地震属性轨迹,计算给定数据子卷(即内线、横线、时间)的相干值,然后利用这些相干值重新计算数据,所提出的 N 次根斜叠加方法增强了三维 τ-p 域中的信号。经过排序后,新数据为获得 N 次根斜线堆栈的最佳 N 值提供了坚实的基础,N 次根斜线堆栈用于增强微弱信号。所提出的方法被应用于中国西部低信噪比(SNR)数据的去噪。确定了提高深地层信噪比的最佳 N 值,并增强了弱地震信号。结果表明,所提出的方法有效地抑制了低信噪比数据中的噪声。
N-th root slant stack for enhancing weak seismic signals
Seismic imaging of complicated underground structures with severe surface undulation (i.e., double complex areas) is challenging owing to the difficulty of collecting the very weak reflected signal. Enhancing the weak signal is difficult even with state-of-the-art multi-domain and multidimensional prestack denoising techniques. This paper presents a time–space dip analysis of offset vector tile (OVT) domain data based on the τ-p transform. The proposed N-th root slant stack method enhances the signal in a three-dimensional τ-p domain by establishing a zero-offset time-dip seismic attribute trace and calculating the coherence values of a given data sub-volume (i.e., inline, crossline, time), which are then used to recalculate the data. After sorting, the new data provide a solid foundation for obtaining the optimal N value of the N-th root slant stack, which is used to enhance a weak signal. The proposed method was applied to denoising low signal-to-noise ratio (SNR) data from Western China. The optimal N value was determined for improving the SNR in deep strata, and the weak seismic signal was enhanced. The results showed that the proposed method effectively suppressed noise in low-SNR data.
期刊介绍:
The journal is designed to provide an academic realm for a broad blend of academic and industry papers to promote rapid communication and exchange of ideas between Chinese and world-wide geophysicists.
The publication covers the applications of geoscience, geophysics, and related disciplines in the fields of energy, resources, environment, disaster, engineering, information, military, and surveying.