抗噪、抗假频叠前地震数据插值方法研究

项目名称： 抗噪、抗假频叠前地震数据插值方法研究

项目编号： No.41604096

项目类型： 青年科学基金项目

立项/批准年度： 2017

项目学科： 天文学、地球科学

项目作者： 王本锋

作者单位： 清华大学

项目金额： 15万元

中文摘要： 地震数据插值可为自由表面多次波去除、AVO分析、偏移和反演等提供完整数据体，可提高其处理精度，为精细油气藏描述服务，是地震数据处理的重要课题。由于障碍物、禁采区的存在，采集的数据在空间方向不规则，降低了地震数据横向连续性；另外，随机噪声、空间假频的存在将会降低插值重建的精度，继而影响后续多道处理的效果，最终影响精细油气藏描述，因此有必要开展抗噪、抗假频叠前地震数据插值方法研究。本项目基于压缩感知理论，研究噪声（不规则性）和信号在稀疏变换域中的异同，提出插值去噪一体化方法；在含有空间假频时，分析信号在变换域中的形态，建立蒙板矩阵约束能量分布，实现抗噪、抗假频插值重建。本项目研究可以为自由表面多次波的去除、偏移和反演提供高信噪比的完整数据体，继而提高精细油气藏描述的精度，具有重要的理论意义和实际应用价值。

中文关键词： 稀疏性；地震数据；信息技术；理论与方法；Curvelet变换

英文摘要： Seismic data interpolation can provide complete seismic data for surface related multiple elimination (SRME), AVO analysis, migration and inversion to improve the processing accuracy, and is useful for fine reservoir description, which makes itself a significant issue of seismic data processing. Because of the existence of the obstacles and forbidden areas, the acquired seismic data is irregular along spatial direction, which decreases the horizontal continuity. Besides, the existence of random noise, spatial aliasing can decrease the interpolation accuracy, then affect the performance of the subsequent multichannel processing and the fine description of the reservoir, therefore it is necessary to study prestack seismic data interpolation with anti-noise and anti-aliasing property. This study is based on compressive sensing theory to study the similarity and difference of the random noise, irregularity and signal in sparse transform domain, and proposes a simultaneous interpolation and denoising method. When spatial aliasing exists, the property of the signal in sparse transform domain is analyzed and the mask matrix is designed to constrain the energy distribution, then the anti-noise and anti-aliasing interpolation is achieved using the designed mask matrix. This research can provide complete data with high SNR for SRME, migration and inversion, then improve the accuracy of fine reservoir description, which has a significant theoretical meaning and a high value of practical applications.

英文关键词： Sparsity;Seismic data;Information technology;Theory and method;Curvelet transform