Yasong Zhao, Hong Cao, Zhifang Yang, Huiqun Xu, Rong Nie, Zefeng Wang, Mengqiong Yang
{"title":"A seismic thin-layer detection factor calculated by integrated S transform with non-negative matrix factorization","authors":"Yasong Zhao, Hong Cao, Zhifang Yang, Huiqun Xu, Rong Nie, Zefeng Wang, Mengqiong Yang","doi":"10.1111/1365-2478.13517","DOIUrl":null,"url":null,"abstract":"<p>Time–frequency analysis is one of the effective methods for seismic thin-layer detection. Conventional time–frequency analysis technology for seismic thin-layer detection is interfered by the energy of adjacent frequency signals, and there is information redundancy in the frequency-domain analysis. Therefore, an <i>S</i> transform with improved window factor, which is based on the constrained non-negative matrix factorization, is constructed to realize seismic thin-layer detection. First, the seismic data is processed by the <i>S</i> transform of the improved window factor, and then we can obtain the frequency-domain information with strong time–frequency focus by changing the adjustment factor and attenuation factor in the window function. Furthermore, the key frequency of the seismic data spectrum, which can also be called the key frequency characteristic factor, can be calculated by the non-negative matrix factorization algorithm. Fortunately, the overthrust model shows a good correspondence between the key frequency characteristic factor and the thin-layer interface. The field data example shows that this approach provides a new approach for thin-layer detection.</p>","PeriodicalId":12793,"journal":{"name":"Geophysical Prospecting","volume":"72 6","pages":"2274-2281"},"PeriodicalIF":1.8000,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geophysical Prospecting","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/1365-2478.13517","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GEOCHEMISTRY & GEOPHYSICS","Score":null,"Total":0}
引用次数: 0
Abstract
Time–frequency analysis is one of the effective methods for seismic thin-layer detection. Conventional time–frequency analysis technology for seismic thin-layer detection is interfered by the energy of adjacent frequency signals, and there is information redundancy in the frequency-domain analysis. Therefore, an S transform with improved window factor, which is based on the constrained non-negative matrix factorization, is constructed to realize seismic thin-layer detection. First, the seismic data is processed by the S transform of the improved window factor, and then we can obtain the frequency-domain information with strong time–frequency focus by changing the adjustment factor and attenuation factor in the window function. Furthermore, the key frequency of the seismic data spectrum, which can also be called the key frequency characteristic factor, can be calculated by the non-negative matrix factorization algorithm. Fortunately, the overthrust model shows a good correspondence between the key frequency characteristic factor and the thin-layer interface. The field data example shows that this approach provides a new approach for thin-layer detection.
时频分析是地震薄层探测的有效方法之一。传统的地震薄层探测时频分析技术会受到相邻频率信号能量的干扰,频域分析存在信息冗余。因此,基于约束非负矩阵因式分解的改进窗因子 S 变换被用来实现地震薄层检测。首先,用改进窗因子的 S 变换对地震数据进行处理,然后通过改变窗函数中的调整因子和衰减因子,获得时频聚焦性强的频域信息。此外,还可以通过非负矩阵因式分解算法计算出地震数据频谱的关键频率,也可称为关键频率特性因子。幸运的是,推覆模型显示了关键频率特性因子与薄层界面之间的良好对应关系。现场数据实例表明,这种方法为薄层检测提供了一种新的方法。
期刊介绍:
Geophysical Prospecting publishes the best in primary research on the science of geophysics as it applies to the exploration, evaluation and extraction of earth resources. Drawing heavily on contributions from researchers in the oil and mineral exploration industries, the journal has a very practical slant. Although the journal provides a valuable forum for communication among workers in these fields, it is also ideally suited to researchers in academic geophysics.