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物探与化探  2023, Vol. 47 Issue (4): 1033-1039    DOI: 10.11720/wtyht.2023.0058
  方法研究信息处理仪器研制 本期目录 | 过刊浏览 | 高级检索 |
基于两步变异差分进化算法的激电测深一维反演
丁志军1(), 罗维斌2(), 连伟章1, 张星1, 何海颦2
1.甘肃省有色地质调查院,甘肃 兰州 730000
2.兰州资源环境职业技术大学 地质与珠宝学院,甘肃 兰州 730021
One-dimensional inversion of induced polarization sounding data based on the differential evolution algorithm with two-step mutation
DING Zhi-Jun1(), LUO Wei-Bin2(), LIAN Wei-Zhang1, ZHANG Xing1, HE Hai-Pin2
1. Gansu Nonferrous Geological Survey Institute, Lanzhou 730000, China
2. Lanzhou Resources and Environment Vocational and Technical University, College of Geology and Jewelry, Lanzhou 730021, China
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摘要 

激电测深一维反演是一个多参数非线性优化问题。本文基于改进的两步变异差分进化全局最优化算法实现了激电测深的一维反演。传统的差分进化算法包含变异、交叉和选择操作,变异为单步变异。本文提出的两步变异法分步将最优个体与随机选取的两个个体经变异后产生新个体。加强了最优个体的影响度,提高了全局寻优能力。通过模型试算结果表明,两步变异法比传统方法寻优能力更强。利用等效电阻率法加载极化率参数,通过数字滤波算法可快速正演计算层状模型表面激电测深电阻率曲线,在此基础上应用两步变异差分进化算法不断变异产生新个体,正演计算电阻率与观测值进行拟合,选择适应度值趋近于最大适应度值的个体作为反演结果。本文反演方法操作简便,计算速度快。通过对H型和KH型地电模型进行计算,得出本反演方法有较高的拟合精度。

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丁志军
罗维斌
连伟章
张星
何海颦
关键词 激电测深非线性一维反演两步变异差分进化优化算法电阻率极化率    
Abstract

The one-dimensional inversion of induced polarization (IP) sounding data involves multi-parameter nonlinear optimization. This study achieved the one-dimensional (1D) inversion of IP sounding data based on the improved global optimization algorithm of differential evolution (DE) with two-step mutation. The conventional DE algorithm includes mutation (single-step), crossover, and selection operations. The two-step mutation method proposed in this study can produce new individuals through the mutation of the optimal individual and two randomly selected individuals in steps, thus enhancing the influence of the optimal individual and the global optimization ability. The model test results show that the two-step mutation method has a higher optimization ability than the conventional method. Specifically, the polarizability parameters were loaded using the equivalent resistivity method, and the surface IP sounding resistivity curves of a layered model can be quickly calculated through forward modeling using the digital filtering algorithm. Based on this, the DE algorithm with two-step mutation was employed to produce new individuals through continuous mutation. Then, the resistivity obtained through forward modeling was fitted with the observed values, and the individuals whose fitness approached the maximum fitness were selected as the inversion results. The inversion method proposed in this study features simple operations and fast calculations. As verified through the calculations of H- and KH-type geoelectric models, the inversion method enjoys high fitting accuracy.

Key wordsIP sounding    nonlinear one-dimensional inversion    optimization algorithm of differential evolution with two-step mutation    resistivity    polarizability
收稿日期: 2023-02-15      修回日期: 2023-05-30      出版日期: 2023-08-20
ZTFLH:  P631  
基金资助:甘肃省教育厅产业支撑计划项目(2021CYZC-67);兰州资源环境职业技术大学科技项目(Y2021B-01)
通讯作者: 罗维斌(1972-),男,地球探测与信息技术工学博士学位,正高级工程师,主要从事地球物理电磁法勘探教学和应用研究工作。Email:lwb210521@lzre.edu.cn
作者简介: 丁志军(1987-),男,地球物理学学士学位,工程师,主要从事电磁法勘探应用研究工作。Email:609415517@qq.com
引用本文:   
丁志军, 罗维斌, 连伟章, 张星, 何海颦. 基于两步变异差分进化算法的激电测深一维反演[J]. 物探与化探, 2023, 47(4): 1033-1039.
DING Zhi-Jun, LUO Wei-Bin, LIAN Wei-Zhang, ZHANG Xing, HE Hai-Pin. One-dimensional inversion of induced polarization sounding data based on the differential evolution algorithm with two-step mutation. Geophysical and Geochemical Exploration, 2023, 47(4): 1033-1039.
链接本文:  
https://www.wutanyuhuatan.com/CN/10.11720/wtyht.2023.0058      或      https://www.wutanyuhuatan.com/CN/Y2023/V47/I4/1033
Fig.1  差分进化流程
Fig.2  两步变异法流程
模型参数 真值 取值范围 反演次数 均值 误差/%
1 2 3 4 5
ρ1/(Ω·m) 100 [10,300] 99.72 99.50 99.78 99.50 100.32 99.76 -0.24
ρ2/(Ω·m) 30 [10,150] 31.15 29.93 31.80 30.09 30.31 30.66 2.19
ρ3/(Ω·m) 110 [10,300] 110.56 110.56 107.63 107.27 107.34 108.67 -1.21
d1/m 180 [10,300] 180.00 180.00 180.00 180.00 180.00 180.00 0.00
d2/m 60 [10,300] 59.99 60.01 59.99 60.01 60.00 60.00 0.00
η1/m 0.5 [0.1, 1] 0.78 1.00 0.72 1.00 0.18 0.74 0.24
η2/m 8.5 [3, 11] 4.97 8.72 3.00 8.24 7.56 6.50 -2.00
η3/m 1 [0.5, 3.5] 0.50 0.50 3.13 3.46 3.40 2.20 1.20
Table 1  H型地电模型参数及反演结果
Fig.3  传统单步变异差分进化与两步变异差分进化性能比较
Fig.4  H型模型真实模型和反演结果的电阻率测深结果对比
模型参数 真值 取值范围 反演次数 均值 误差/%
1 2 3 4 5
ρ1/(Ω·m) 120 [10,300] 119.52 120.24 120.39 120.48 120.47 120.22 0.18
ρ2/(Ω·m) 560 [100,800] 557.21 557.26 559.88 559.71 557.59 558.33 -0.30
ρ3/(Ω·m) 25 [10,100] 26.04 26.85 26.10 24.37 24.32 25.53 2.14
ρ4/(Ω·m) 310 [50,500] 310.58 306.77 303.68 304.13 310.54 307.14 -0.92
d1/m 110 [50,300] 110.00 110.00 110.04 110.00 110.00 110.01 0.01
d2/m 120 [50,300] 120.00 119.98 119.20 119.98 120.02 119.83 -0.14
d3/m 150 [50,300] 150.03 150.29 160.59 150.31 149.68 152.18 1.45
η1/m 0.6 [0.2,1] 1.00 0.40 0.28 0.20 0.21 0.42 -0.18
η2/m 0.3 [0.1,0.8] 0.80 0.80 0.65 0.36 0.72 0.67 0.37
η3/m 9.5 [3,12] 5.76 3.00 11.59 11.95 11.80 8.82 -0.68
η4/m 1 [0.8,3.5] 0.81 2.03 3.08 2.88 0.82 1.93 0.93
Table 2  KH型地电模型参数及反演结果
Fig.5  KH型模型真实模型和反演结果的电阻率测深结果对比
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