Drilling tool posture modeling method for directional drilling of fractured and soft coal seam tunnel

Abstract

The invention relates to the field of underground coal mine drilling engineering, and discloses a drilling tool posture modeling method for directional drilling of a broken and soft coal seam tunnel. Based on the coal mine underground single-bend screw drill directional drilling technology, according to the geometrical relationship between the tool face angle and the drill posture, a drill posture model related to the build-up rate is obtained; in order to solve the problem that the actual build-up rate of a drilling tool is changed due to fracture and softness of a coal seam, on the basis of fracture and softness coal seam drilling engineering data, a mutual information method is utilized to carry out drilling tool attitude influence factor analysis, environment and engineering characteristic parameters highly related to the drilling tool attitude are determined, and a drilling tool build-up rate model based on sigmoid and a polynomial function is established; and by combining actual data, related unknown parameters of a build-up rate model are identified by using a nonlinear least square method, and an accurate drilling tool attitude model is obtained. Compared with a drilling tool posture model not considering the uncertainty of the build-up rate, the drilling tool posture model has the advantages that the accuracy of the drilling tool posture model in the directional drilling of the fractured and soft coal seam tunnel is obviously improved, and a basis can be provided for the drilling tool posture, drilling track prediction, track tracking control and the like of the directional drilling of the fractured and soft coal seam tunnel.

Description

Technical Field

[0001] The invention relates to the field of coal mine tunnel drilling engineering, and in particular to a drill tool posture modeling method for directional drilling of broken soft coal seam tunnels. Background Art

[0002] Directional drilling technology in underground coal mines is an artificially inclined drilling method that uses a single-bend screw drill to drill to the predetermined target according to the design requirements. It mainly includes two modes: sliding directional drilling and compound drilling. By switching the drilling mode, the trajectory deviation can be controlled and the drilling efficiency can be improved to achieve efficient hole formation. Sliding directional drilling is an adjustment strategy adopted for the situation where the drilling trajectory deviates from the design allowable range. In this mode, the drill in the borehole only slides and does not rotate. The position, inclination and azimuth of the drill are controlled by adjusting the tool face angle of the single-bend screw drill, so that the borehole can extend in a predetermined direction. This method is suitable for situations where the trajectory needs to be corrected quickly, and can effectively adjust the target trajectory. Compound drilling is more used to keep the drilling trajectory smooth and improve the slag removal capacity, which is conducive to safe drilling construction. By switching the working modes of deflection and stable inclination, the preset trajectory can be continuously tracked and controlled.

[0003] The geological conditions of coal mines in my country are complex, among which the coal structure of broken and soft coal seams is broken and drilling construction is difficult. At present, the setting of the facing angle of directional drilling construction tools is mainly based on the screw drill tool deflection law summarized by manual experience, which has problems such as low degree of automation and inaccurate control of directional drilling trajectory. The influence of broken and soft coal seams on the drilling trajectory is studied, and a drill tool posture model suitable for broken and soft coal seams is given, which can provide a basis for the prediction of drilling tool posture drilling trajectory and trajectory tracking control in directional drilling tunnels in broken and soft coal seams. Summary of the invention

[0004] In order to solve the problem of changes in the actual inclination rate of drill tools caused by crushed and soft coal seams, the present invention provides a drill tool posture modeling method for directional drilling in crushed and soft coal seam tunnels. The method is based on the directional drilling technology of single-bend screw inclination drill tools in coal mines, and obtains a drill tool posture model related to the inclination rate according to the geometric relationship of the drill tool posture; then, the mutual information method is used to analyze and determine the drill tool inclination rate model based on sigmoid and polynomial functions, and the nonlinear least squares method is used to identify the unknown parameters related to the inclination rate model, so as to obtain an accurate drill tool posture model, which can accurately predict the drill tool posture in a crushed and soft coal seam environment.

[0005] The method mainly includes the following steps:

[0006] S1: Based on the directional drilling technology of single-bend screw deflection drilling tool in coal mines, the drilling tool posture model related to the deflection rate is obtained according to the geometric relationship of the drilling tool posture;

[0007] S2: Aiming at the problem that the actual drilling tool deflection rate changes due to the soft coal seam, the mutual information method is used to analyze the factors affecting the drilling tool posture based on the engineering data of soft coal seam drilling, determine the environmental and engineering characteristic parameters with high correlation with the drilling tool posture, and establish a drilling tool deflection rate model based on sigmoid and polynomial functions;

[0008] S3: Based on the drill tool attitude model related to the build-up rate and combined with actual data, the nonlinear least squares method is used to identify the unknown parameters related to the drill tool build-up rate model to obtain an accurate drill tool attitude model.

[0009] A computer device comprises a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above method.

[0010] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above method.

[0011] A computer program product comprises a computer program or instructions, and when the program or instructions are executed by a processor, the steps of the above method are implemented.

[0012] The technical solution provided by the present invention has the following beneficial effects: first, according to the geometric relationship in the drill tool posture, the present invention establishes a drill tool posture model related to the build-up rate. Then, in view of the problem that the actual build-up rate of the drill tool changes due to the soft coal seam, the mutual information method is used to analyze the factors affecting the drill tool posture based on the engineering data of drilling in the soft coal seam, and the environmental and engineering characteristic parameters with high correlation with the drill tool posture are determined, and a drill tool build-up rate model based on sigmoid and polynomial functions is established. Finally, on the basis of the drill tool posture model related to the build-up rate, the nonlinear least squares method is used to identify the unknown parameters related to the build-up rate model in combination with the actual data, and the accurate drill tool posture model obtained can accurately predict the drill tool posture in the soft coal seam environment. Combined with the actual situation of the directional drilling process of the soft coal seam tunnel, the present invention fully considers the influence of the soft coal seam on the directional drilling, and proposes a drill tool posture modeling method for directional drilling of the soft coal seam tunnel, which improves the prediction accuracy of the model for the drill tool posture, and can provide a basis for the directional drilling of the soft coal seam tunnel, the drilling trajectory prediction, and the trajectory tracking control. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The present invention will be further described below with reference to the accompanying drawings and embodiments, in which:

[0014] Figure 1 The present invention is a flowchart of a method for modeling the drill tool posture for directional drilling in a broken soft coal seam tunnel.

[0015] Figure 2It is a parameter dependency heat map matrix after mutual information analysis is performed on each drilling engineering data in an embodiment of the present invention.

[0016] Figure 3 This is the prediction effect of the nominal drill tool posture model in the embodiment of the present invention in a broken soft coal seam environment.

[0017] Figure 4 This is the prediction effect of the drill tool posture model considering the uncertainty of the build-up rate in a broken soft coal seam environment in an embodiment of the present invention. DETAILED DESCRIPTION

[0018] In order to have a clearer understanding of the technical features, purposes and effects of the present invention, specific embodiments of the present invention are now described in detail with reference to the accompanying drawings.

[0019] Example 1

[0020] Please refer to Figure 1 , Figure 1 It is a flow chart of a method for modeling a drill tool posture for directional drilling in a broken soft coal seam tunnel according to an embodiment of the present invention, which specifically includes:

[0021] S1: Based on the directional drilling technology of single-bend screw inclination drilling tool in coal mine, according to the geometric relationship between tool face angle and drill tool posture, the drill tool posture model related to the inclination rate is obtained; for the directional drilling in coal mine using single-bend screw drilling tool, the geometric relationship between tool face angle and drill tool posture is analyzed, and the spatial coordinate transformation is used to establish the drill tool posture model related to the inclination rate as shown in (1) and (2):

[0022]

[0023]

[0024] Among them, θ inc is the drilling tool inclination angle, θ azi is the drilling tool azimuth, K dls1 , K dls2 are the inclination and azimuth build rates, U inc is the tilt angle control value, U azi is the azimuth control quantity.

[0025] S2: Based on the engineering data of drilling in broken soft coal seams, the mutual information method is used to analyze the factors affecting the drilling tool posture, determine the environmental and engineering characteristic parameters with high correlation with the drilling tool posture, and establish a drilling tool slope rate model based on sigmoid and polynomial functions; mutual information I (X; Y) is defined as the difference between the joint distribution of variables X and Y and their respective marginal distributions, reflecting the additional information that one variable can provide when another variable is known. Specifically, the mutual information can be calculated by the following formula:

[0026]

[0027] Where p(x,y) is the joint probability distribution of X and Y, and p(x) and p(y) are the marginal probability distributions of X and Y respectively.

[0028] In order to analyze the relationship between hole depth, feed pressure, extraction pressure, wind pressure, air volume, coal seam hardness and inclination and azimuth, the mutual information method is used to analyze the dependence between the variables in the actual drilling data of four holes 15#, 17#, 29# and 30# in a coal mine in Hancheng, Shaanxi. The parameters with a dependence higher than 0.5 are selected as characteristic parameters. The experimental results are as follows Figure 2 As shown, Figure 2 (a) is the mutual information dependence heat map of 15# parameters, (b) is the mutual information dependence heat map of 17# parameters, (c) is the mutual information dependence heat map of 19# parameters, (d) is the mutual information dependence heat map of 30# parameters, and (e) is the parameter average dependence heat map matrix.

[0029] The drilling tool inclination rate K during drilling dls1 , K dls2 It will change under the influence of coal seam environment. Combining the above correlation analysis and drilling process characteristics, we consider adding hole depth, feed pressure, wind pressure, air volume, and coal seam hardness as uncertain slope factor K. dls1 The characteristic parameters in the correlation model of the relationship between the hole depth, feed pressure, wind pressure and air volume are added as the uncertain slope factor K dls2 The characteristic parameters in the association relationship model.

[0030] For formula (1), the uncertain slope rate K dls1 The association relationship model is:

[0031] K dls1 (H,P,Q,F,C)=(a 1 F 2 +a 2 F+a 3 H)+σ(a 4 (a 5 P+a 6 Q+a 7 H+a 8 ))+a 9 Q+a 10 (4)

[0032] For formula (2), according to the mutual information analysis results, the azimuth is less affected by the hardness of the coal seam, so the slope rate K is uncertain. dls2 The association relationship model is:

[0033] K dls2H,P,Q,F,C)=(β 1 F 2 +β 2 F+β 3 H)+σ(β 4 (β 5 P+β 6 Q+β 7 H+β 8 ))+β 9 Q(5)

[0034] Among them, H is the hole depth, P is the wind pressure, Q is the air volume, F is the feed pressure, C is the coal seam hardness, and σ is the sigmoid function. 1 ,…,a 10 ,β 1 ,…,β 9 are unknown parameters, which play the role of adjusting the amplitude and rate of change of the function.

[0035] For equations (4) and (5), during the drilling process, as the hole depth increases, the contact friction between the drill pipe and the hole wall will also increase. At the same time, there is a similar linear law for the air volume and air pressure. Therefore, the influence of hole depth on the deflection rate can be given in the form of a general linear function. For feed pressure, the deflection rate of the drill tool will increase with the increase of feed pressure, but when the feed pressure increases to a certain value, the deflection rate will begin to decrease with the continued increase of feed pressure. This is mainly because the ratio of the initial support reaction force of the structural bend to the drilling pressure becomes smaller under high drilling pressure, which weakens The inclination ability of the drill bit; the influence of wind pressure and air volume on the inclination rate is mainly reflected through the slag removal effect. During the drilling process, if the air volume and air pressure reach a certain value, there will be less sediment in the hole, and the inclination rate will be greatly affected by the deadweight. If it is lower than a certain value, there will be more sediment in the hole, and the inclination rate will be greatly affected by the sediment. Therefore, the influence of wind pressure and air volume on the inclination rate can be given in the form of an approximate sigmoid function; for coal seam hardness, the influence on the inclination rate is relatively simple. Different coal seams correspond to different inclination rates, which can be given in the form of a general linear function.

[0036] S3: Based on the drill tool attitude model related to the build-up rate, combined with actual data, the nonlinear least squares method is used to identify the unknown parameters related to the drill tool build-up rate model, the root mean square error between the model predicted attitude and the actual attitude is calculated, the model performance is evaluated, and then an accurate drill tool attitude model is obtained.

[0037] Table 1. Results of fitting the polynomial coefficients of the nonlinear least squares method of formula (4)

[0038]

[0039] Table 2 Nonlinear least squares polynomial coefficient fitting results of formula (5)

[0040]

[0041] According to equations (4) and (5), in order to determine the parameters at each position in the expression, the nonlinear least squares method is used to perform fitting experiments between input and output using actual drilling data. Starting from the initial parameter estimation value, the parameters are gradually adjusted through an iterative optimization process until the parameter value that minimizes the sum of squared errors is found. In each iteration, the algorithm calculates the residual between the model prediction value and the actual observation value, and then updates the parameter estimation value based on the residual and the Jacobian matrix of the model. The parameter identification results are shown in Tables 1 and 2. Figure 3 The model fitting effect of the drilling tool attitude without considering the uncertainty of the build-up rate is shown. Figure 3 (a) is a comparison of the model-calculated inclination angle and the actual inclination angle without considering the uncertainty of the slope rate. Figure 3 (b) is a comparison between the model-calculated azimuth and the actual azimuth without considering the uncertainty of the slope rate. Figure 4 The fitting results of the drilling tool posture model under this method are shown. Figure 4 (a) shows the comparison between the calculated inclination angle of the model proposed in the present invention and the actual inclination angle. Figure 4 (b) shows the comparison between the azimuth angle calculated by the model proposed in the present invention and the actual azimuth angle. The results show that under the same actual drilling data, the root mean square error of the inclination angle output by the model proposed in the present invention is reduced from 15.68 to 1.02, and the root mean square error of the azimuth angle is reduced from 2.74 to 1.50, which significantly improves the prediction accuracy of the model.

[0042] Example 2

[0043] A computer device comprises a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above method.

[0044] Example 3

[0045] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above method.

[0046] Example 4

[0047] A computer program product comprises a computer program or instructions, and when the program or instructions are executed by a processor, the steps of the above method are implemented.

[0048] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A drilling tool posture modeling method for directional drilling in broken soft coal seam tunnels, characterized in that: include: S1: Based on the directional drilling technology of single-bend screw deflection drilling tool in coal mines, the drilling tool posture model related to the deflection rate is obtained according to the geometric relationship of the drilling tool posture; S2: Aiming at the problem that the actual drilling tool deflection rate changes due to the soft coal seam, the mutual information method is used to analyze the factors affecting the drilling tool posture based on the engineering data of soft coal seam drilling, determine the environmental and engineering characteristic parameters with high correlation with the drilling tool posture, and establish a drilling tool deflection rate model based on sigmoid and polynomial functions; S3: Based on the drill tool attitude model related to the build-up rate and combined with actual data, the nonlinear least squares method is used to identify the unknown parameters related to the drill tool build-up rate model to obtain an accurate drill tool attitude model.

2. The method for drilling tool posture modeling for directional drilling in broken soft coal seam tunnels according to claim 1, characterized in that: In S1, for directional drilling in coal mines using single-bend screw drills, the geometric relationship between the tool face angle and the drill posture is analyzed, and the drill posture model related to the build-up rate is established using spatial coordinate transformation as shown in (1) and (2): Among them, θ inc is the drilling tool inclination angle, θ azi is the drilling tool azimuth, K dls1 , K dls2 are the inclination and azimuth build rates, U inc is the tilt angle control quantity, U azi is the azimuth control quantity.

3. The method for drilling tool posture modeling for directional drilling in broken soft coal seam tunnels according to claim 2, characterized in that: In S2, the engineering data of drilling in the broken soft coal seam include hole depth, wind pressure, air volume, pulling pressure, feed pressure, coal seam hardness, inclination and azimuth. The mutual information method is used to analyze the factors affecting the drilling tool posture to obtain the degree of dependence between each parameter and the inclination and azimuth; According to the results of mutual information analysis, characteristic parameters with high correlation with drill tool posture are extracted as characteristic parameters affecting the uncertain inclination rate of the drill tool posture model. The correlation between the characteristic parameters of hole depth, feed pressure, wind pressure, air volume and coal seam hardness and the drill tool inclination rate is clarified, and a drill tool inclination rate model based on sigmoid and polynomial functions is established. High correlation means that the dependence degree of characteristic parameters on drill tool posture is higher than 0.

5.

4. The method for drilling tool posture modeling for directional drilling in a broken soft coal seam tunnel according to claim 3, characterized in that: In S2, the mutual information is calculated by the following formula: Where p(x,y) is the joint probability distribution of variables X and Y, and p(x) and p(y) are the marginal probability distributions of variables X and Y, respectively.

5. The method for drilling tool posture modeling for directional drilling in broken soft coal seam tunnels according to claim 4, characterized in that: For formula (1), the uncertain slope rate K dls1 The association relationship model is: K dls1 (H,P,Q,F,C)=(a1F 2 +a2F+a3H)+σ(a4(a5P+a6Q+a7H+a8))+a9Q+a 10 (4) For formula (2), according to the mutual information analysis results, the uncertain slope rate K dls2 The association relationship model is: K dls2 H,P,Q,F,C)=(β1F 2 +β2F+β3H)+σ(β4(β5P+β6Q+β7H+β8))+β9Q(5) Among them, H is the hole depth, P is the wind pressure, Q is the air volume, F is the feed pressure, C is the coal seam hardness, σ is the sigmoid function, a1,…,a 10 ,β1,…,β9 are unknown parameters used to adjust the function amplitude and rate of change.

6. A computer device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of establishing a drill tool posture model for directional drilling in a broken soft coal seam tunnel as described in any one of claims 1-6.

7. A computer-readable storage medium, characterized in that: A computer program is stored, and when the program is executed by a processor, the steps of establishing a drill tool posture model for directional drilling in a broken soft coal seam tunnel as described in any one of claims 1 to 6 are implemented.

8. A computer program product, characterized in that It includes a computer program or instruction, which, when executed by a processor, implements the steps of establishing a drill tool posture model for directional drilling in a broken soft coal seam tunnel as described in any one of claims 1 to 6.

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