摘要
超高密度电法是建立在常规高密度电阻率法基础上的一种新型地球物理探测方法,其继承了高密度电法的诸多优势。首先在数据采集过程中使用多通道数据采集方式,充分利用已经布好的电极,除供电电极以外其他电极均可以进行数据采集,在此过程中缩短了因为进行单一数据采集而消耗的时间,并且增大了数据采集量,从而提高了工作效率;其次,改进型的超高密度电法可以进行多种装置采集所得到的数据联合反演,避免单一数据反演产生的结果畸变,从而提高了探测精度。本文首先介绍了此方法的基本原理、观测方式等;其次通过一个典型模型进行超高密度电法和常规高密度电法的对比分析,确认此方法在实验过程中明显提高了工作效率;此后,在进一步的分析过程中,使用改进型超高密度电法,将若干种装置采集得到的数据分别进行联合反演,还进行了多参数联合反演,取得了良好的应用效果。
The ultra-high density resistivity method is to create the new geophysical method on the basis of the conventional high-density resistivity method,which inherits many advantages of high density electrical method.Firstly,in the data collection process,the multi-channel data acquisition mode is used,which takes full advantage of the arrangement of the electrodes,the other electrodes in addition to the powered electrode can be the data acquisition and shorten the time consumed by a single data acquisition process,and increases the amount of data collected to improve the work efficiency.Secondly,the improved ultra-high density resistivity method can be used for the joint inversion of the data obtained by the acquisition from a variety of devices to avoid the distortion of the results generated by the inversion of a single datum to improve the accuracy.The basic principle and the observation way of this said method are introduced.The contrast analysis on the ultra-high density resistivity method and the conventional high density electrical resistivity method are analyzed through a typical model,and in the course of the experiment it is confirmed that this method can significantly improve the work efficiency.The further analysis on the process is carried out by using the improved ultra-high density resistivity method,and the joint inversion is made by using the data obtained from several kinds of device acquisition.The improved ultra-high density electrical method can be used for multi-parameter joint inversion and can get better results.
出处
《工程勘察》
2013年第9期75-79,共5页
Geotechnical Investigation & Surveying
关键词
超高密度电法
改进型
模型响应
ultra-high density resistivity method
improved type
model response
