Geological fault detection method under hard and soft interbedded geological condition

Abstract

The present invention discloses a geological fault detection method under a hard and soft interbedded geological condition. The method comprises a step of arranging a detector and a trigger point in a roadway side under a hard and soft interbedded geological condition and obtaining detection data, a step of purifying the reflection slot wave in the detection data, carrying out speed extraction on the reflection slot wave to obtain the velocity profile of the reflection slot wave, carrying out offset superimposition on purified reflection slot wave data on the basis of the velocity profile of the reflection slot wave, and thus obtaining a geological profile. According to the method, in the hard and soft interbedded geological condition, through obtaining and processing the slot wave, the slot wave is used to detect a geological fault to carry out geological forecast, compared with the existing complex process of using reflection transverse and longitudinal wave processing, the detection method of the invention has the advantages that the slot wave purification is more simple, the geological construction of each profile in the geological fault is obtained after slot wave offset stacking, the distribution of the fault can be detected, the growth condition of geological hazards of karst, collapse column and the like in a two-dimensional space can be known, a detection result is accurate, and the range is wide.

Description

technical field [0001] The invention relates to the technical field of advanced geological prediction of tunnels (roadways), in particular to a method for detecting geological faults under soft and hard interbedded geological conditions. Background technique [0002] The current research and application fields of advanced geological prediction methods based on seismic waves are concentrated in tunnel engineering in the field of railway, highway and water conservancy construction. [0003] In 2013, Liu Shengdong of China University of Mining and Technology proposed a coal roadway advanced fault detection method based on reflection channel wave signals. This method directly picks up the arrival time of reflection channel waves from the time profile by means of geometric calculations, thereby drawing the six-channel data. The intersection point, that is, the position where the fault develops, has the advantages of convenience and simplicity, but this method can only give the si...

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Problems solved by technology

[0003] In 2013, Liu Shengdong of China University of Mining and Technology proposed a coal roadway advanced fault detection method based on reflection channel wave signals. This method directly picks up the arrival time of reflection channel waves from the time profile by means of geometric calculations, thereby drawing the six-channel data. The intersection point, that is, the position where the fault develops, has the advantages of convenience and simplicity, but this method can only give the single mileage information of the fault, and cannot give the occurrence and lateral scale information (due to the data imaging process without space); and the The method is only effective for faults, and cannot deal with geological diseases such as karst and collapsed columns

[0004] The conventional seismic wave advanced geological prediction method in the engineering field, the processing process is aimed at the reflected longitudinal wave and shear wave, but in the soft and hard interbedded geological conditions, due to the low velocity of the reflected channel wave and the long duration of the envelope (generally 60ms~ 220ms), resulting in the reflected longitudinal waves and shear waves within the conventionally required exploration range are almost completely submerged in the direct channel waves with dominant energy, and the original processing method cannot be used directly

Therefore, the existing data processing methods are not suitable for seismic wave advanced geological prediction technology under this geological condition.

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