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高密度电法反演数据预处理方法研究
引用本文:尚新磊,于悦,王天宇,王浩宇,王晓光. 高密度电法反演数据预处理方法研究[J]. 工程地球物理学报, 2021, 18(2): 199-204
作者姓名:尚新磊  于悦  王天宇  王浩宇  王晓光
作者单位:吉林大学仪器科学与电气工程学院,吉林长春130012;吉林大学公共计算机教学与研究中心,吉林长春130012
摘    要:高密度电法探测获得的视电阻率数据中存在的不确定噪声,会使反演结果不精确且反演时间增加.为了减小不确定性噪声带来的影响,采用自适应滤波方法对视电阻率曲线进行预处理后,再进行反演计算.本文通过仿真对比验证该方法的有效性.首先构建球体异常区域,半径为1 000 cm,电阻率为35 Ω·m.对构建模型进行正演计算后,获得视电阻...

关 键 词:视电阻率曲线  自适应滤波方法  2.5D电法反演

Research on the Data Preprocessing Method of High Density Resistivity Inversion
Shang Xinlei,Yu Yue,Wang Tianyu,Wang Haoyu,Wang Xiaoguang. Research on the Data Preprocessing Method of High Density Resistivity Inversion[J]. Chinese Journal of Engineering Geophysics, 2021, 18(2): 199-204
Authors:Shang Xinlei  Yu Yue  Wang Tianyu  Wang Haoyu  Wang Xiaoguang
Affiliation:(College of Instrument Science and Electrical Engineering, Jilin University, Changchun Jilin 130012, China;Public Computer Education and Research Center, Jilin University, Changchun Jilin 130012, China)
Abstract:The uncertain noise in the apparent resistivity curve obtained by high density electric method tends to cause the inaccuracy of inversion result and slow down the inversion velocity.In order to reduce the negative influence of uncertain noise,the adaptive filtering method is used to preprocess the apparent resistivity curve and then carry out inversion calculation.The effectiveness of the proposed method is verified by simulation.Firstly,the anomalous region of the sphere with radius of 1000 m and conductivity of 35Ω·m is constructed.The apparent resistivity data with white noise and power frequency noise and the preprocessed apparent resistivity data are then used for 2.5D electrical inversion calculation.The relative error of the inversion resistivity is reduced by 10%,the relative error of abnormal area radiusis reduced by 30%,and the inversion time is shortened by 30%.It can be seen that self-adaptive filtering of apparent resistivity data with noise can significantly improve the inversion results and shorten the inversion time.
Keywords:apparent resistivity curve  self-adaptive filtering method  2.5D inversion
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