薄储层高分辨率阻抗反演
[Abstract]:Seismic wave impedance inversion is an important aspect of seismic reservoir prediction. Because of its high resolution and low model dependence, compression perception has become a hot research field in the field of seismic signal processing. The applications of compression sensing in seismic wave impedance inversion mainly include base tracing impedance inversion and matching tracing impedance inversion. The basis tracking method is to realize information reconstruction by minimizing the first norm. The matching tracking method uses greedy local matching optimization dictionary to realize signal reconstruction. In this paper, we first study the principle of matching tracking and base tracking in compressed sensing. The advantages of compression sensing over traditional digital signal processing methods such as Fourier transform and wavelet transform are analyzed. Compression sensing is different from the traditional digital signal processing technology. It uses a small number of observations to represent the original sparse signal by constructing the corresponding dictionary. How to apply the base tracking and matching tracking methods of compression sensing to seismic impedance inversion is analyzed. The key factors of the application of base tracking and matching tracing in compression sensing in seismic impedance inversion are also studied. Secondly, the realization method of matching tracing in seismic wave impedance inversion is studied. The inversion is based on single-layer (monopole) matching tracing impedance inversion, two-layer tuning (bipolar) matching tracing impedance inversion, and four-layer tuning (quadrupole) matching tracing impedance inversion. According to the instability of matching tracing in the decomposition of actual seismic records, it is proposed that the wavelet phase and the main frequency range should be determined in the construction of atomic library. The matching tracing decomposition strategy takes into account the error between the original seismic signal and the matching synthetic seismic signal on the basis of the original seismic signal projected to the maximum value of the atomic library. Thirdly, the realization of base tracing in seismic wave impedance inversion is studied, which is based on unipolar and bipolar basis tracing impedance inversion. In order to further improve the inversion resolution of multilayer tuning, a quadrupole subbase tracing impedance inversion method is established. Finally, the global consistency advantage of base tracking and the local optimization advantage of matching tracking are established. The problems of matching tracing impedance inversion and base tracing impedance inversion are analyzed. By synthesizing the respective advantages of the two inversion methods, firstly, the best matching seismic wavelet of each reflection layer is obtained by matching tracing, and then the base tracking uses matching tracing to construct the decomposed atomic library. The seismic information is decomposed by using the method of tracing impedance inversion based on quadrupole basis, and the relative reflection coefficient sequence of each reflection layer with higher resolution is obtained, and the wave impedance of each layer is obtained.
【学位授予单位】:成都理工大学
【学位级别】:硕士
【学位授予年份】:2017
【分类号】:P618.13;P631.4
【参考文献】
相关期刊论文 前10条
1 印兴耀;刘晓晶;吴国忱;宗兆云;;模型约束基追踪反演方法[J];石油物探;2016年01期
2 刘晓晶;印兴耀;吴国忱;宗兆云;;基于基追踪弹性阻抗反演的深部储层流体识别方法[J];地球物理学报;2016年01期
3 郝亚炬;文晓涛;李忠;李世凯;李天;;基于基追踪分解算法的薄层波阻抗反演[J];科学技术与工程;2015年33期
4 杨昊;郑晓东;李劲松;马淑芳;;基于匹配追踪的薄层自动解释方法[J];石油地球物理勘探;2013年03期
5 黄捍东;郭飞;汪佳蓓;任敦占;;高精度地震时频谱分解方法及应用[J];石油地球物理勘探;2012年05期
6 李雪英;陈树民;王建民;裴江云;王元波;;薄层时频特征的正演模拟[J];地球物理学报;2012年10期
7 武国宁;曹思远;孙娜;;基于复数道地震记录的匹配追踪算法及其在储层预测中的应用[J];地球物理学报;2012年06期
8 张繁昌;李传辉;印兴耀;;三角洲砂岩尖灭线的地震匹配追踪瞬时谱识别方法[J];石油地球物理勘探;2012年01期
9 张繁昌;李传辉;;基于正交时频原子的地震信号快速匹配追踪[J];地球物理学报;2012年01期
10 赵嵩;马荣华;薛朝改;李恒建;;基于树型冗余字典正交匹配追踪的信号稀疏分解[J];扬州大学学报(自然科学版);2011年04期
相关硕士学位论文 前7条
1 屈冉;压缩感知算法及其应用研究[D];南京邮电大学;2013年
2 文首先;压缩感知匹配追踪算法的研究[D];安徽大学;2013年
3 任晓馨;压缩感知贪婪匹配追踪类重建算法研究[D];北京交通大学;2012年
4 王方非;基于树形结构回溯正交匹配追踪的稀疏恢复算法研究[D];北京交通大学;2012年
5 胡军;基于压缩传感稀疏重构方法的研究[D];湖南大学;2012年
6 李亚文;遗传匹配追踪算法的研究与改进[D];江南大学;2011年
7 赵玉娟;基于子空间匹配追踪的信号稀疏逼近[D];西安电子科技大学;2005年
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