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基于傅里叶变换的反泄漏地震数据重建方法

发布时间:2019-01-12 21:00  文章来源:笔耕文化传播
【摘要】:在地震数据处理中,通常受到复杂因素的影响其在空间方向上的采样是不规则的,而这种不规则的采样对后续的地震资料处理影响严重。数据规则化的作用是通过在不规则采样网格中,使用估计空间频率的傅里叶方法进行实现。在一个不规则坐标网格中,傅里叶基函数的非正交性导致“谱泄漏”的问题:能量从一个傅里叶系数泄漏到另一个傅里叶系数中。本文研究了基于傅立叶变换的地震数据规则化的反泄漏算法,通过递归减法的ALFT算法消除了不规则地震数据所引发的频谱泄漏现象,可实现精准分析相对应的傅里叶系数,进而实现不规则网格数据处理和规则重建。本文采用区域加权方案准确估计傅里叶权值;应用频率域过采样技术消除边界吉布斯现象;利用非规则快速傅里叶变换代替传统的非规则离散傅里叶变换降低运算成本;应用分块策略将大数据分块处理提高运行速率;应用分布式并行策略用以存储及处理超大型数据。在本文中,介绍了基于CUDA架构的GPU/CPU并行加速技术,针对较高的轻量计算任务如矩阵乘法部分采用GPU算法进行改进,改进后算法并行度高,处理速度快。在反泄漏傅里叶变换算法中,通过将非规则傅里叶变换运算部分按照傅里叶因子与输入数据的关系拆分成矩阵乘法形式进行表达,并将拆分后的矩阵乘法部分传入GPU端进行处理;在GPU端应用share memory对数据处理进行进一步的加速;应用reduction改进算法在GPU中求取最大值。多种改进以及优化技术应用在反泄漏傅里叶变换方法中,很大程度上提高算法处理效率以及结果模型的精度,通过GPU端相应优化,其算法的加速比可以达到76倍以上。理论模型和实际数据处理结果可以满足工业化的需求,验证了方法的有效性和合理性。
[Abstract]:In seismic data processing, the sampling in spatial direction is irregular under the influence of complex factors, and this kind of irregular sampling has a serious effect on the subsequent seismic data processing. The function of data regularization is realized by using Fourier method to estimate spatial frequency in irregular sampling grid. In an irregular coordinate grid, the nonorthogonality of the Fourier basis function leads to the problem of "spectral leakage": energy leaks from one Fourier coefficient to another. In this paper, a regularized anti-leakage algorithm of seismic data based on Fourier transform is studied. The frequency spectrum leakage caused by irregular seismic data is eliminated by recursive subtraction ALFT algorithm, and the corresponding Fourier coefficients can be accurately analyzed. Furthermore, irregular grid data processing and rule reconstruction are realized. In this paper, the region weighting scheme is used to accurately estimate the Fourier weight, the frequency domain oversampling technique is used to eliminate the boundary Gibbs phenomenon, the irregular fast Fourier transform is used to replace the traditional irregular discrete Fourier transform, and the operation cost is reduced. The block processing of big data is applied to improve the running rate, and the distributed parallel strategy is used to store and process super large data. In this paper, the GPU/CPU parallel acceleration technology based on CUDA architecture is introduced. The GPU algorithm is used to improve the high lightweight computing tasks such as matrix multiplication. The improved algorithm has a high degree of parallelism and a fast processing speed. In the anti-leakage Fourier transform algorithm, the irregular Fourier transform is expressed in matrix multiplication form according to the relation between the Fourier factor and the input data. And the split matrix multiplication part is passed into the GPU terminal for processing; The data processing is further accelerated by using share memory at the GPU end, and the maximum value is obtained by using the improved reduction algorithm in GPU. Many improved and optimized techniques are applied to the anti-leakage Fourier transform method, which greatly improves the processing efficiency of the algorithm and the precision of the result model. The speedup ratio of the algorithm can reach more than 76 times through the corresponding optimization of the GPU terminal. The theoretical model and the actual data processing results can meet the needs of industrialization and verify the validity and rationality of the method.
【学位授予单位】:东北石油大学
【学位级别】:硕士
【学位授予年份】:2017
【分类号】:P631.44

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