Study on the Velocity Analysis Method of Low SNR Seismic Data

Jianbo He,Mingdong Zhang,Zhenyu Wang

doi:10.5539/eer.v11n1p78

Abstract

When the signal to noise ratio of seismic data is very low, velocity spectrum focusing will be poor., the velocity model obtained by conventional velocity analysis methods is not accurate enough, which results in inaccurate migration. For the low signal noise ratio (SNR) data, this paper proposes to use partial Common Reflection Surface (CRS) stack to build CRS gathers, making full use of all of the reflection information of the first Fresnel zone, and improves the signal to noise ratio of pre-stack gathers by increasing the number of folds. In consideration of the CRS parameters of the zero-offset rays emitted angle and normal wave front curvature radius are searched on zero offset profile, we use ellipse evolving stacking to improve the zero offset section quality, in order to improve the reliability of CRS parameters. After CRS gathers are obtained, we use principal component analysis (PCA) approach to do velocity analysis, which improves the noise immunity of velocity analysis. Models and actual data results demonstrate the effectiveness of this method.

Highlights

At present, the focus of seismic exploration has shifted to the areas with strong interference, such as complicated topography areas
The signal-to-noise ratio of seismic data obtained in these areas is very low, the reflection phase axis on the common center point (CMP) gather can not be distinguished completely, the focusing of velocity spectrum is poor, the error of the extracted stacking velocity is quite large, and it is difficult to establish an accurate velocity model, which leads to the poor effect of subsequent migration imaging
Traditional Common Reflection Surface (CRS) stack only improves the quality of post stack time profile. and the partial CRS stack method studied in this paper inherits many advantages of CRS stack. as the partial CRS stack method utilizes the information about the local inclination and curvature of each reflection unit to stack the gathers that contribute to the reflection unit, making full use of the potential of multiple coverage data, which can improve the quality of prestack data and is more conducive to our subsequent processing, such as velocity analysis, stack and migration imaging

Summary

Introduction

The focus of seismic exploration has shifted to the areas with strong interference, such as complicated topography areas. As the partial CRS stack method utilizes the information about the local inclination and curvature of each reflection unit to stack the gathers that contribute to the reflection unit, making full use of the potential of multiple coverage data, which can improve the quality of prestack data and is more conducive to our subsequent processing, such as velocity analysis, stack and migration imaging. Compared with the conventional CMP stack method, the ellipse expansion CRP method abandons the traditional idea of common center of CMP, and stack in the original shot domain directly Since this method makes full use of all kinds of effective information (strong or weak reflection information and diffraction information) to realize interference stack. It can be seen that only the strongest common phase axis is visible in CMP gathers (Fig. 2 (a)) But in CRS gathers, the reflection layer is clearly visible and the signal-to-noise ratio is significantly improved (Fig. 2 (b))

Ellipse Evolving CRP Method

Model Test

Findings

Conclusions