CN114458307A - A method for in situ acquisition of rock dynamic parameters - Google Patents

Abstract

The invention belongs to the technical field of mine blasting, and discloses a method for in-situ acquisition of rock dynamic parameters, comprising the following steps: dividing layers of rock layers in a blasting work area according to drilling rig parameters, and acquiring rock physical mechanics parameters of each layer; Carry out micro-logging test in the blasting work area; according to the rock physical and mechanical parameters and micro-logging test data of each layer; carry out the test shot excitation test in the blasting work area; establish the initial finite element model; obtain the optimal finite element model ; Obtain the rock dynamic parameters of each horizon based on the optimal finite element model. The invention solves the problems existing in the prior art that the steps are complicated, the accuracy and real-time performance are low, the time cost is too large, and the continuity of the rock mass in the work area is destroyed.

Description

A method for in situ acquisition of rock dynamic parameters

technical field

The invention belongs to the technical field of mine blasting, and particularly relates to an in-situ acquisition method of rock dynamic parameters.

Background technique

In conventional blasting operations, the rock mass samples are obtained by coring, and the mechanical properties of the rock mass samples are tested in the laboratory to obtain rock mechanical parameters. This method has complex steps, accuracy and real-time performance in engineering applications low, and the time cost is too high. At present, the automatic identification methods of blasting rock dynamic parameters include methods based on cluster analysis and artificial intelligence, both of which are based on sample databases, and determine rock dynamic parameters by constructing the functional relationship between independent variables and dependent variables. This involves the accuracy of the rock dynamic parameters predicted based on the sample database. The rock dynamic parameters are the inherent physical and mechanical characteristics of the rock, and the specific properties exhibited in the dynamic process can be taken into the rock samples after sampling. Testing in the laboratory, and verification of the accuracy of mechanical parameters after mechanical testing, this process destroys the continuity of the rock mass in the work area, and is time-consuming, labor-intensive, and labor-intensive. And with the development of fine blasting concept and electronic detonator, the requirements for blasting design and fine control of blasting process are getting higher and higher. Mine rock dynamic parameters are the basis of fine blasting design. Identify the lithology, analyze the lithology data and then feed back the drilling rig to optimize the drilling rig parameters. This cycle, acquisition-calculation-feedback-adjustment-acquisition, makes blasting more reasonable and economical. The development of 5G information technology and sensors while drilling has made real-time acquisition of drilling rig data a reality during blasting and drilling operations in open-pit mines. How to obtain the rock dynamic parameters in real time during the drilling process of the drilling rig and to be able to quickly verify the accuracy of the rock dynamic parameters is of great significance to the blasting quality control and blasting economy.

SUMMARY OF THE INVENTION

In order to solve the problems of complex steps, low accuracy and real-time performance, excessive time cost and damage to the continuity of the rock mass in the work area in the prior art, the present invention aims to provide an in-situ acquisition method of rock dynamic parameters.

The technical scheme adopted in the present invention is:

A method for in-situ acquisition of rock dynamic parameters, comprising the following steps:

According to the drilling rig parameters, the rock layered layers in the blasting area are divided, and the rock physical and mechanical parameters of each layer are obtained;

Carry out micro-logging test in the blasting area, and obtain the micro-logging test data of each first monitoring point in each layer;

According to the petrophysical and mechanical parameters of each layer and the micro-logging test data, the elastic-plastic parameters of each layer are obtained;

Carry out the test shot excitation test in the blasting work area, dynamically set the second monitoring point and record the corresponding monitoring vibration data;

According to the blast source parameters of the test shot excitation test, the position data of the second monitoring point, the layers of rock layers and the elastic-plastic parameters of each layer, the initial finite element model is established;

Use the initial finite element model to obtain the calculated vibration data of each second monitoring point, compare and analyze the calculated vibration data with the corresponding monitoring vibration data, and optimize the initial finite element model according to the comparative analysis results to obtain the optimal finite element model;

The rock dynamic parameters of each horizon are obtained based on the optimal finite element model.

Further, according to the drilling rig parameters, the layers of the rock layers in the blasting work area are divided, and the rock physical and mechanical parameters of each layer are obtained, including the following steps:

Get the rig parameters of the drill bit at different depths;

According to the obtained drilling rig parameters, the rock layers in the blasting area are divided;

The rock physical and mechanical parameters of each horizon are calculated according to the drilling rig parameters.

Further, the drilling rig parameters include the rotational speed of the drill bit, the drilling speed, the rotary pressure difference, the wind pressure, the end resistance and the frictional resistance ratio.

Further, the rock physical and mechanical parameters include the density, shear modulus and yield strength of the rock.

Further, obtaining the micro-logging test data of each first monitoring point in each layer includes the following steps:

According to the requirements of micro-logging test, set detonators in micro-logging at different depths;

Set up several monitoring points around the micro-logging;

The detonators are activated in sequence, and the micro-logging test data of each first monitoring point is recorded.

Further, obtaining the elastic-plastic parameters of each horizon includes the following steps:

The corresponding seismic wave transit time data is obtained according to the micro-logging test data of each first monitoring point, and the propagation wave velocity of the seismic wave in each horizon is obtained according to the seismic wave transit time data;

According to the propagating wave velocity of seismic waves in each horizon, the rock layered layers in the blasting area are optimized, and the optimized rock layered layers are obtained;

According to the rock physical and mechanical parameters of each optimized horizon and the corresponding micro-logging test data, the elastic-plastic parameters of each optimized horizon are obtained.

Further, the elastic-plastic parameters include attenuation coefficient and elastic modulus.

Further, dynamically setting the second monitoring point and recording the corresponding monitoring vibration data includes the following steps:

Keep the dose constant, carry out the test shot excitation test at each optimized horizon, and record the first test shot excitation data of each second monitoring point;

Keep the optimized horizon unchanged, use different doses to conduct the test shot excitation test, and record the second test shot excitation data of each second monitoring point;

According to the excitation data of the first and second test shots and the optimized horizon of rock stratification, the second monitoring point is dynamically set and the corresponding monitoring vibration data is recorded.

Further, establishing an initial finite element model includes the following steps:

According to the optimized horizon of rock stratification, establish rock mechanics calculation model;

Based on the rock mechanics calculation model, the elastic-plastic parameters of each optimized horizon are taken as the medium mechanics parameters, and the initial finite element model is established according to the blast source parameters of the test shot excitation test and the position data of each second monitoring point.

Further, obtaining the optimal finite element model includes the following steps:

Use the initial finite element model to obtain the calculated vibration data of the current second monitoring point at the currently optimized horizon, and compare and analyze the calculated vibration data with the corresponding monitored vibration data;

If the result of the comparative analysis is that the error is greater than the threshold, adjust the elastic-plastic parameters of the currently optimized horizon, re-acquire the calculated vibration data of the second monitoring point and perform the comparative analysis again, otherwise, change to the next second monitoring point for comparison analyze;

If all the second monitoring points of the current optimized horizon are analyzed and compared, the elastic-plastic parameters of the current optimized horizon will be used as the media mechanics parameters of the next optimized horizon, and the analysis will be performed at the next optimized horizon. Compare;

If all the second monitoring points of all the optimized horizons are analyzed and compared, the optimal finite element model will be obtained.

The beneficial effects of the present invention are:

The present invention provides an in-situ acquisition method of rock dynamic parameters without changing the distribution status of existing rock formations in blasting work areas, and a real-time acquisition method combining drilling rig data and rock formation seismic data in drilling operations, which simplifies the analysis of rock dynamic parameters. The acquisition step improves the accuracy and real-time performance, ensures the continuity of the rock mass in the work area, and is suitable for situations where laboratory tests cannot be used, such as it is difficult to obtain a complete sample, which highlights the superiority of in-situ acquisition of rock dynamic parameters.

Other beneficial effects of the present invention will be further described in the specific embodiments.

Description of drawings

Fig. 1 is a method flow chart of the method for in-situ acquisition of rock dynamic parameters in the present invention.

Detailed ways

The present invention will be further explained below with reference to the accompanying drawings and specific embodiments.

Example 1:

As shown in FIG. 1 , this embodiment provides an in-situ acquisition method for rock dynamic parameters, including the following steps:

Divide the layers of rock layers in the blasting area according to the drilling rig parameters, and obtain the rock physical and mechanical parameters of each layer, including the following steps:

Obtain the drilling rig parameters of the drill bit at different depths. The drilling rig parameters include the rotational speed of the drill bit, the drilling speed, the rotary pressure difference, the wind pressure, the end resistance and the friction resistance ratio. In this example, the drilling speed, the rotary speed, and the rotary pressure are used. difference, pressurized pressure and wind pressure;

According to the obtained drilling rig parameters, the rock layers of the 30-meter deep rock layer in the blasting work area are divided;

The multiple regression method is used to divide the layers of rock layers, and the division formula is:

C=-3.2v ₁ -0.72v ₂ +0.12p ₁ +37.56p ₂ +500p ₃ +6.257

In the formula, C is the Platts coefficient of rock strength; v ₁ is the drilling speed, in m/s; v ₂ is the rotation speed, in r/s; p ₁ is the rotary pressure difference, in kPa; p ₂ is Pressurized pressure, the unit is kPa; p ₃ is the wind pressure, the unit is kPa;

According to the layers of rock layers obtained by the regression of drilling rig parameters, the Platts strength coefficient is generally used to characterize the distribution of rock layers. For example, the Platts coefficient of coal seam rocks is generally between 2 and 5, and sandstone is generally between 4 and 10. The coefficient difference divides the rock into 3 layers;

Calculate the rock physical and mechanical parameters of each layer according to the drilling rig parameters. The rock physical and mechanical parameters include the density, shear modulus and yield strength of the rock;

Carry out a micro-logging test in the blasting work area to obtain the micro-logging test data of each first monitoring point in each layer, including the following steps:

According to the requirements of the micro-logging test, the micro-logging is divided into three areas from deep to shallow, and different detonator intervals are set from deep to shallow. The detonator interval is 0.5 meters;

The first monitoring point distributed in a cross shape is set around the micro-logging, and 10 sensors are set on one side, and the sensor installation interval is 5 meters. The sensors are used to record vibration data and seismic wave elapsed time;

Excite the detonators sequentially from bottom to top, and record the micro-logging test data of each first monitoring point;

According to the rock physical and mechanical parameters and micro-logging test data of each layer, the elastic-plastic parameters of each layer are obtained, including the following steps:

The corresponding seismic wave transit time data is obtained according to the micro-logging test data of each first monitoring point, and the average seismic wave propagation speed between the first monitoring points is obtained according to the seismic wave transit time data, that is, the seismic wave propagation speed in each horizon, the formula for:

v=l/τ

In the formula, v is the average velocity of seismic wave propagation at the two first monitoring points; l is the distance between the two first monitoring points; τ is the time interval of the seismic waves passing through the two first monitoring points;

According to the propagating wave velocity of seismic waves in each horizon, the rock layered layers in the blasting area are optimized, and the optimized rock layered layers are obtained;

The formula for obtaining the horizon height of each rock layer is:

In the formula, hi is the height of the _ith horizon; vi and v _{i +1} are the propagating wave speeds of the ith and i+1 horizons; τ _i is the time interval of the seismic wave passing through the ith horizon;

According to the rock physical and mechanical parameters of each optimized horizon and the corresponding micro-logging test data, the elastic-plastic parameters of each optimized horizon are obtained. The elastic-plastic parameters include attenuation coefficient and elastic modulus. The calculation formula of elastic modulus is:

In the formula, θ is the elastic modulus; C is the Platts coefficient of rock strength; ρ is the root of rock density;

Carry out the test shot excitation test in the blasting work area, dynamically set the second monitoring point and record the corresponding monitoring vibration data, including the following steps:

Keep the TNT explosive with the dosage of 2kg unchanged, carry out the test shot excitation test at each optimized horizon, and record the first test shot excitation data of each second monitoring point;

Keep the optimized horizon unchanged, use different doses of TNT explosives of 1kg, 2kg, and 3kg to carry out the test shot excitation test, and record the second test shot excitation data of each second monitoring point;

According to the excitation data of the first and second test shots and the optimized horizon of the rock stratification, the second monitoring point is dynamically set and the corresponding monitoring vibration data is recorded. The number of the second monitoring point is greater than the total number of horizons plus 2;

According to the blast source parameters of the test shot excitation test, the position data of the second monitoring point, the layers of rock layers and the elastic-plastic parameters of each layer, an initial finite element model is established, including the following steps:

According to the optimized horizon of rock stratification, establish rock mechanics calculation model;

Based on the rock mechanics calculation model, the elastic-plastic parameters of each optimized horizon are taken as the medium mechanics parameters, and the initial finite element model is established according to the blast source parameters of the test shot excitation test and the position data of each second monitoring point;

Use the initial finite element model to obtain the calculated vibration data of each second monitoring point, compare and analyze the calculated vibration data with the corresponding monitoring vibration data, and optimize the initial finite element model according to the results of the comparative analysis to obtain the optimal finite element model, It includes the following steps:

Use the initial finite element model to obtain the calculated vibration data of the current second monitoring point at the currently optimized horizon, and compare and analyze the calculated vibration data with the corresponding monitored vibration data;

If the result of the comparative analysis is that the error is greater than the threshold value of 3%, adjust the elastic-plastic parameters of the currently optimized horizon, re-acquire the calculated vibration data of the second monitoring point and perform the comparative analysis again, otherwise, change to the next second monitoring point carry out comparative analysis;

If all the second monitoring points of the current optimized horizon are analyzed and compared, the elastic-plastic parameters of the current optimized horizon will be used as the media mechanics parameters of the next optimized horizon, and the analysis will be performed at the next optimized horizon. Compare;

If all the second monitoring points of all the optimized horizons are analyzed and compared, the optimal finite element model will be obtained;

The rock dynamic parameters of each horizon are obtained based on the optimal finite element model.

The present invention provides an in-situ acquisition method of rock dynamic parameters without changing the distribution status of existing rock formations in blasting work areas, and a real-time acquisition method combining drilling rig data and rock formation seismic data in drilling operations, which simplifies the analysis of rock dynamic parameters. The acquisition step improves the accuracy and real-time performance, ensures the continuity of the rock mass in the work area, and is suitable for situations where laboratory tests cannot be used, such as it is difficult to obtain a complete sample, which highlights the superiority of in-situ acquisition of rock dynamic parameters.

The present invention is not limited to the above-mentioned optional embodiments, and anyone can derive other various forms of products under the inspiration of the present invention. The above specific embodiments should not be construed as limiting the protection scope of the present invention, which should be defined in the claims, and the description can be used to interpret the claims.

Claims (10)

1. An in-situ acquisition method of rock kinetic parameters is characterized by comprising the following steps: the method comprises the following steps:

dividing the positions of rock layering in a blasting work area according to the parameters of the drilling machine, and acquiring the physical and mechanical parameters of rocks at each position;

carrying out a micro-logging test in the blasting work area to obtain micro-logging test data of each first monitoring point of each layer;

acquiring elastoplasticity parameters of each layer according to the rock physical mechanical parameters and the micro-logging test data of each layer;

carrying out a test-blasting excitation test in a blasting work area, dynamically setting a second monitoring point and recording corresponding monitoring vibration data;

establishing an initial finite element model according to the explosion source parameters of the test gun excitation test, the position data of the second monitoring point, the layer position of the rock layering and the elastoplasticity parameters of each layer position;

obtaining the calculated vibration data of each second monitoring point by using the initial finite element model, comparing and analyzing the calculated vibration data with the corresponding monitored vibration data, and optimizing the initial finite element model according to the comparison and analysis result to obtain an optimal finite element model;

and acquiring rock dynamics parameters of each layer based on the optimal finite element model.

2. The in-situ acquisition method of rock kinetic parameters according to claim 1, characterized in that: dividing the positions of rock layering in a blasting work area according to the parameters of a drilling machine, and acquiring the physical and mechanical parameters of rocks of all the positions, wherein the method comprises the following steps:

acquiring drilling machine parameters of a drill bit at different depths;

dividing the rock layering layer in the blasting work area according to the obtained drilling machine parameters;

and calculating the rock physical mechanical parameters of each layer according to the drilling machine parameters.

3. The in-situ acquisition method of rock kinetic parameters according to claim 2, characterized in that: the parameters of the drilling machine comprise the rotating speed, the drilling speed, the rotary pressure difference, the wind pressure, the end resistance and the friction-resistance ratio of the drill bit.

4. The in-situ acquisition method of rock kinetic parameters according to claim 3, characterized in that: the rock physical mechanical parameters comprise the density, the shear modulus and the yield strength of the rock.

5. The in-situ acquisition method of rock kinetic parameters according to claim 4, characterized in that: obtaining micro-logging test data of each first monitoring point of each layer, comprising the following steps:

arranging detonators in micro-logging wells at different depths according to the requirements of the micro-logging test;

arranging a plurality of monitoring points around the micro-logging;

and sequentially exciting the detonators and recording the micro-logging test data of each first monitoring point.

6. The in-situ acquisition method of rock kinetic parameters according to claim 5, characterized in that: obtaining elastic-plastic parameters of each layer, comprising the following steps:

acquiring corresponding seismic wave passing time data according to the micro-logging test data of each first monitoring point, and acquiring the propagation wave velocity of the seismic waves at each layer according to the seismic wave passing time data;

optimizing the layer position of the rock layering in the blasting work area according to the propagation wave velocity of the seismic waves at each layer position to obtain an optimized layer position of the rock layering;

and acquiring the elastoplasticity parameters of the optimized layers according to the rock physical and mechanical parameters of the optimized layers and the corresponding micro-logging test data.

7. The in-situ acquisition method of rock kinetic parameters of claim 6, characterized by comprising: the elastic-plastic parameters comprise attenuation coefficient and elastic modulus.

8. The in-situ acquisition method of rock kinetic parameters of claim 7, characterized by: dynamically setting a second monitoring point and recording corresponding monitoring vibration data, comprising the following steps:

keeping the dosage unchanged, performing a test firing excitation test on each optimized layer, and recording first test firing excitation data of each second monitoring point;

keeping the optimized layer constant, performing a test-gun excitation test by using different doses, and recording second test-gun excitation data of each second monitoring point;

and dynamically setting a second monitoring point and recording corresponding monitoring vibration data according to the first and second pilot gun excitation data and the optimized layer position of the rock layering.

9. The in-situ acquisition method of rock kinetic parameters of claim 8, characterized by: establishing an initial finite element model, comprising the following steps:

establishing a rock mechanics calculation model according to the optimized horizon of the rock layering;

and based on a rock mechanics calculation model, taking the elastoplasticity parameters of each optimized layer as medium mechanics parameters, and establishing an initial finite element model according to the explosion source parameters of the test gun excitation test and the position data of each second monitoring point.

10. The in-situ acquisition method of rock kinetic parameters of claim 9, characterized in that: obtaining an optimal finite element model, comprising the following steps:

using an initial finite element model to obtain the calculated vibration data of the current second monitoring point at the current optimized position, and comparing and analyzing the calculated vibration data with the corresponding monitored vibration data;

if the comparison analysis result is that the error is larger than the threshold value, adjusting the elastic-plastic parameters of the current optimized layer, re-acquiring the calculated vibration data of the second monitoring point and performing comparison analysis again, otherwise, replacing the second monitoring point with the next second monitoring point for comparison analysis;

if all the second monitoring points of the current optimized layer are analyzed and compared, the elastic-plastic parameters of the current optimized layer are used as the medium mechanical parameters of the next optimized layer, and the next optimized layer is replaced for analysis and comparison;

and if all the second monitoring points of all the optimized layers are analyzed and compared, obtaining the optimal finite element model.

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