Research And Implementation Of A Hybrid Correlation Denoising Algorithm Based On Complex Resistivity

The method of complex resistivity is an important method in geophysical exploration,which is commonly used to study the geological structure,look for useful mineral resources and solve engineering or environment and so on.In field applications,a large number of complex interferences seriously affect the quality of the detected signal of complex resistivity,resulting in decreasing the interpreation accuracy of geological structure and its inner target anomaly.To tackle this problem,noise reduction technology of correlation identification has developed in recent years.However,the relevant technology of recognizing and reducing noise at present mainly adopts the ground injection current,which is not only the reference signal to recognize and reduce the noise,but also the key signal of solving the special parameter of the complex resistivity,it may cause the standard of reducing noise by the own scale,so that when the signal is distorted,it can generate the calculation error.In order to solve this disadvantage,a hybrid correlation denoising algorithm,which combines excitation source signal,relevant theory and complex resistivity method with instrument design,is proposed in this paper.The main research contents are as follows.First,coherent identification technology evaluates robustness of typical pseudo-random excitation source in the anti-jamming ability.The results show that2~n sequence pseudo-random signal has the strong robustness of the anti-jamming ability,which is the reason that it is used as the excitation source in this paper.Second,the basic principle of selecting raw complex resistivity data with high signal-to-noise ratio(SNR)by coherence function method is analyzed.Through simulation analysis of noise reduction effect compared with traditional correlation coefficient method,the ability of selecting raw complex resistivity data with high SNR can be further improved by introducing coherence function method into data preprocessing link.Thirdly,according to the design concept of correlative fusion for noise reduction,three modules of enhanced correlative identification for noise reduction are derived.Then,the anti-noise performance of three modules of enhanced correlative identification for noise reduction is verified by the comparative simulation analysis of the noise reduction effect through conventional noise reduction algorithm.The results show that the de-noising performance of the third module of enhanced correlative identification for noise reduction is particularly prominent.Fourthly,the set of complex resistivity instruments of correlative fusion de-noising algorithm is developed.Based on the analysis of the design requirements,the key hardware technologies to realize the algorithm of correlative fusion for noise reduction is expounded emphatically.Finally,the system test and the model experiment result analysis are carried out on a set of self-developed instrument,which verifies the effectiveness of the whole apparatus and the integrity of the algorithm system of correlative fusion for noise reduction.Field exploration shows that correlation fusion noise reduction algorithm greatly enhances the noise reduction performance of complex resistivity system,and improves its system ability to distinguish abnormal bodies and the accuracy of data interpretation.