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Research On The Resistivity Cross-hole CT Methods And Its Application For The Engineering Field

Posted on:2015-02-19Degree:MasterType:Thesis
Country:ChinaCandidate:Z Y LiuFull Text:PDF
GTID:2250330431454984Subject:Architecture and civil engineering
Abstract/Summary:PDF Full Text Request
Recent years, with the increasingly complex terrain and geological conditions and environmental monitoring faced in detection, the requirements of imaging accuracy and interpret results for geophysical detection are increasingly high. For the requirements above, as the advantages of resistivity crosshole CT method in terms of detection accuracy and resolution, advanced solution of DC resistivity crosshole CT detection method was proposed, which was improved in this paper in terms of observation mode, inversion imaging method, etc. The main contents are as follows:1) Crosshole CT inversion quick sectional imaging detection based on2dimensional resistivity. A kind of partial derivative parallel parsing algorithm was proposed to solve the inversion problem of inefficiency in partial derivative matrix calculation, parsing algorithm was used to ensure the accuracy of the inversion, and parallel algorithm was used to improve inversion solution speed; a kind of combined observation mode was proposed, fitting crosshole CT detection based on2dimendional resistivity, and it also has the advantage of a variety of observation modes, the ability of detect and identify anomalous body was improved by this mode; through a great number of inversion cases, the impact of parameters setting on crosshole CT detection inversion imaging results based on2dimensional resistivity was discussed, like drill hole spacing, the electrode spacing, etc, imaging characteristics and response law of different kinds of abnormal bodies was summarized. Feasibility and effectiveness of this method used in anomaly detection were verified by physical model experiments.2) Crosshole CT detection whole space inversion imaging method based on3dimensional resistivity. The whole space arrangement and detection mode was established for crosshole CT measuring electrode based on3dimensional resistivity. Impact on three-dimensional electric field was studied, when the low-resistivity body, impedance body existed separately; inequality constrained inversion imaging method was proposed to bring inequality constraints representing range of resistivity changes as priori information into crosshole CT inversion equation based on3dimensional resistivity; observation mode applying to crosshole CT based on3dimensional resistivity was proposed, compared with the traditional electrical detection imaging and crosshole CT detection imaging based on2dimensional resistivity, the unique advantage of crosshole CT detection method based on3dimensional resistivity was revealed, such as abnormal body positioning and precise identification of3dimensional space; through a large number of inversion cases, the impact of parameters setting on crosshole CT detection inversion imaging results based on3dimensional resistivity was studied, like drill hole spacing, the electrode spacing, etc, imaging characteristics and response law of different kinds of abnormal bodies was summarized. Feasibility and effectiveness of this method used in anomaly detection were verified by physical model experiments.3) Time lapse-uniformization inversion imaging method based on3dimensional resistivity crosshole CT. Time lapse-uniformization inversion imaging theory used in geological disaster change process monitoring was proposed to give the apparent resistivity data collected from background field and the subsequent time steps uniformly same ratio process in the whole monitoring process, with eliminating interference flanking, more effective resistivity change information is extracted; and good results have been achieved in the monitoring test of tunnel water inrush impacting on the underground water environment.
Keywords/Search Tags:crosshole resistivity CT, detecting inversion imaging, 3D reisitivitycrosshole CT, time-lapse inversion imaging, dynamic monitoring, sophisticateddetection
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