高密度电法反演数据预处理方法研究

Research on the Data Preprocessing Method of High Density Resistivity Inversion

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1000 cm,电阻率为35Ω·m。对构建模型进行正演计算后,获得视电阻率数据,分别对添加白噪声与工频噪声的视电阻率数据和预处理后的视电阻率数据进行2.50D电法反演计算,反演电阻率相对误差降低10%,异常区域半径相对误差降低30%,反演时间缩短30%。结果表明,对存在噪声的视电阻率数据进行自适应滤波处理能够明显改善反演结果,并能够缩短反演时间。

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.