| 基于群体搜索的串行蒙特卡罗反演方法的并行算法(英文) |
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| 引用本文： | 魏超,李小凡,郑晓东.基于群体搜索的串行蒙特卡罗反演方法的并行算法(英文)[J].应用地球物理,2010,7(2):127-134. |
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| 作者姓名： | 魏超 李小凡 郑晓东 |
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| 作者单位： | |
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| 基金项目： | supported by National Key S&T Special Projects of Marine Carbonate(No.2008ZX05000-004);CNPC Projects(No.2008E-0610-10) |
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| 摘 要： | 随着并行计算技术的发展,非线性反演计算效率在不断提高,但对于基于单点搜索的非线性反演方法,其并行算法的实现则是一个难题。本文将群体搜索的思想引入到基于单点搜索的非线性反演方法,构建了并行算法,以量子蒙特卡罗方法为例进行了二维地震波速度反演及实际资料波阻抗反演,并测试了使用不同节点数进行计算的效率。计算结果表明:该并行算法在理论和实际资料反演中是可行的和有效的,具有很好的通用性;算法计算效率随着使用节点数的增加而提高,但算法计算效率的提高幅度随着使用节点数的增加逐渐减小。
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| 关 键 词： | 非线性反演 单点搜索 群体搜索 并行计算 |
The group search-based parallel algorithm for the serial Monte Carlo inversion method |
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| Chao?Wei,Xiao-Fan?Li,Xiao-Dong?Zheng.The group search-based parallel algorithm for the serial Monte Carlo inversion method[J].Applied Geophysics,2010,7(2):127-134. |
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| Authors: | Chao Wei Xiao-Fan Li Xiao-Dong Zheng |
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| Institution: | 1.Research Institute of Petroleum Exploration and Development,PetroChina,Beijing,100083. 2.Institute of Geology and Geophysics,CAS,Beijing,100029. |
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| Abstract: | With the development of parallel computing technology, non-linear inversion calculation efficiency has been improving. However,
for single-point search-based non-linear inversion methods, the implementation of parallel algorithms is a difficult issue.
We introduce the idea of group search to the single-point search-based non-linear inversion algorithm, taking the quantum
Monte Carlo method as an example for two-dimensional seismic wave velocity inversion and practical impedance inversion and
test the calculation efficiency of using different node numbers. The results show the parallel algorithm in theoretical and
practical data inversion is feasible and effective. The parallel algorithm has good versatility. The algorithm efficiency
increases with increasing node numbers but the algorithm efficiency rate of increase gradually decreases as the node numbers
increase. |
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| Keywords: | non-linear inversion single-point search group search parallel computation |
| 本文献已被 CNKI 维普 万方数据 SpringerLink 等数据库收录！ |
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