一种动态匹配特征子波拾取地震同相轴的技术

在传统的地震资料解释或速度分析等过程中，通常都是依靠人工识别与拾取，不但工作量大，而且效率非常低。因此，工业界开始使用各种算法来进行地震同相轴的自动识别与拾取，但是这些算法存在较多的缺陷，精度不高。地震剖面可视为由地震子波与反射系数褶积构成，子波以及噪音的存在对剖面的自动拾取带来一定困难。通过对地震子波进行特征抽取，并将地震剖面进行稀疏化表达，降低子波以及噪音对自动拾取的影响，同时减少数据采样点数，提高计算效率。通过引入矢量距离，并结合动态波形匹配算法计算特征化矢量数据的最小距离，从而实现同相轴的自动追踪。理论资料测试证明方法的正确性和抗噪能力，东部某探区实际资料自动拾取证明了论文方法的有效性。

A Dynamic Matching Feature Wavelet Picking Seismic Event Technology

Traditional seismic data interpretation or velocity analysis usually depends on manual identification and picking up,which not only has heavy workload,but also has very low efficiency.Therefore,the industry began to use a variety of algorithms are used in production to automatically identify and pick up seismic events,but these algorithms have many defects and low accuracy.Seismic profiles can be regarded as the convolution of seismic wavelet and reflection coefficient.The existence of wavelet and noise makes it difficult to pick up profiles automatically.Through feature extraction of seismic wavelet and sparse expression of seismic profiles,the influence of wavelet and noise on automatic pickup is reduced,and the number of data sampling points is reduced to improve the calculation efficiency.By introducing vector distance and combining with dynamic waveform matching algorithm to calculate the minimum distance of characteristic vector data,the automatic tracking of events.The validity and anti-noise ability of the method proved by the test of theoretical data and the validity of the method in this paper have been proved by the automatic pickup of the actual data in an eastern exploration area.