Discrete element stratigraphic model mesoscopic parameter calibration method, system, medium and equipment

Abstract

The invention relates to a discrete element stratigraphic model mesoscopic parameter calibration method and system, a medium and equipment, and the method comprises the following steps: employing an intrinsic specific energy calculation method to calculate an average cutting force, and obtaining first data; calculating an average cutting force by adopting a discrete element simulation method to obtain second data; performing error calculation based on the first data and the second data to obtain an error result; and according to an error result, adjusting the initial value of each mesoscopic parameter until an error range is met, and completing parameter calibration. According to the method, the stratum mesoscopic parameters required by the discrete element rock breaking model can be efficiently deduced and obtained according to the cutting force, accurate stratum parameters are provided for subsequent influence factor analysis, tooth profile optimization and other simulation, and the model accuracy is guaranteed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of drilling exploration, and more particularly to a discrete element formation model mesoscopic parameter calibration method, system, medium and equipment. BACKGROUND

[0002] The conventional drill bit is seriously worn in the drilling process, the single drill bit footage is short, and the average mechanical drilling speed is low. The use of special-shaped tooth drill bit can effectively improve the rock breaking efficiency and reduce the drill bit wear, and good application effect has been achieved in the field. However, the special-shaped tooth rock breaking mechanism is not clear, and the discrete element method is used to carry out drill bit rock breaking simulation test to explore the interaction mechanism of drill bit or drill bit and formation, which has important significance for prompting the special-shaped tooth drill bit rock breaking mechanism.

[0003] The related research results can provide guidance basis for deep hard formation drill bit selection. The first step of the discrete element rock breaking simulation test is to establish a formation model and complete the mesoscopic parameter correction. The conventional method is to carry out single triaxial compression test and Brazilian splitting test based on core data to measure rock elastic modulus, Poisson's ratio, compressive strength, cohesion, internal friction angle and tensile strength and other parameters. Based on this, the mesoscopic parameters of the formation model are calibrated. However, in the case of difficulty in taking core in the field, the necessary rock mechanics parameters cannot be obtained through core data, and the conventional method cannot complete the calibration of the mesoscopic parameters of the discrete element formation model. SUMMARY

[0004] The technical problem to be solved by the present application is to provide a discrete element formation model mesoscopic parameter calibration method, system, medium and equipment in view of the problems in the prior art.

[0005] The technical scheme adopted by the present application to solve the technical problem is that a discrete element formation model mesoscopic parameter calibration method is constructed, comprising the following steps:

[0006] The average cutting force is calculated by using the specific energy calculation method to obtain first data;

[0007] The average cutting force is calculated by using the discrete element simulation method to obtain second data;

[0008] Error calculation is carried out based on the first data and the second data to obtain error results;

[0009] The initial values of each mesoscopic parameter are adjusted according to the error results until the error range is met, and the parameter calibration is completed.

[0010] In the discrete element formation model mesoscopic parameter calibration method, the average cutting force is calculated by using the specific energy calculation method to obtain first data, which comprises:

[0011] Collecting logging data, and constructing a basic database based on the logging data;

[0012] Determining a drill bit cutting depth based on the logging data;

[0013] Calculating according to the cutting depth and drill bit parameters to obtain an average value of horizontal cutting force; the average value of horizontal cutting force is the first data.

[0014] In the discrete element stratum model micro parameter calibration method, the logging data includes a penetration rate, a rotation speed, a drilling pressure, a drill bit model and the drill bit parameters;

[0015] The determining of the drill bit cutting depth based on the logging data includes:

[0016] Calculating according to the penetration rate and the rotation speed to obtain the drill bit cutting depth.

[0017] In the discrete element stratum model micro parameter calibration method, the drill bit parameters include a tooth shape, a drill bit radius and a back rake angle;

[0018] The calculating according to the cutting depth and drill bit parameters to obtain an average value of horizontal cutting force includes:

[0019] Calculating according to the back rake angle, the drilling pressure, the drill bit radius and the cutting depth to obtain a rock intrinsic specific energy;

[0020] Calculating an average value of drill bit cutting depths of multiple groups of data and an average value of rock intrinsic specific energies of multiple groups of data;

[0021] Calculating according to the average value of drill bit cutting depths, the average value of rock intrinsic specific energies and a width of a drill bit cutting cross section to obtain the average value of horizontal cutting force.

[0022] In the discrete element stratum model micro parameter calibration method, the calculating of the average cutting force by using the discrete element simulation method to obtain second data includes:

[0023] Establishing a discrete element rock breaking model based on a preset discrete element method, and assigning initial values of each micro parameter of the discrete element rock breaking model;

[0024] Setting the cutting depth and the cutting speed in the discrete element rock breaking model to obtain average values of tangential cutting forces under different conditions; the average values of tangential cutting forces under different conditions are the second data.

[0025] In the method for calibrating micro parameters of a discrete element formation model, the error calculation based on the first data and the second data comprises:

[0026] The error calculation is performed on the average horizontal cutting force in the first data and the average tangential cutting force in the second data to obtain the error result.

[0027] In the method for calibrating micro parameters of a discrete element formation model, the adjustment of the initial values of the micro parameters according to the error result until the error range is satisfied to complete the parameter calibration comprises:

[0028] determining whether the value of the error result is less than a set value;

[0029] if yes, determining that the error range is satisfied;

[0030] if no, determining that the error range is not satisfied, and adjusting the initial values of the micro parameters until the error range is satisfied.

[0031] The application further provides a system for calibrating micro parameters of a discrete element formation model, comprising:

[0032] a intrinsic calculation unit configured to calculate the average cutting force by using an intrinsic specific energy calculation method to obtain first data;

[0033] a discrete simulation unit configured to calculate the average cutting force by using a discrete element simulation method to obtain second data;

[0034] an error calculation unit configured to perform error calculation based on the first data and the second data to obtain an error result;

[0035] a parameter adjustment unit configured to adjust the initial values of the micro parameters according to the error result until the error range is satisfied to complete the parameter calibration.

[0036] The application further provides a storage medium storing a computer program, wherein the computer program is adapted to be loaded by a processor to execute the steps of the method for calibrating micro parameters of a discrete element formation model.

[0037] The application further provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the steps of the method for calibrating micro parameters of a discrete element formation model by calling the computer program stored in the memory.

[0038] The discrete element stratum model mesoscopic parameter calibration method, system, medium and equipment implementing the present application have the following beneficial effects: comprising the following steps: calculating the average cutting force by using the intrinsic specific energy calculation method to obtain first data; calculating the average cutting force by using the discrete element simulation method to obtain second data; performing error calculation based on the first data and the second data to obtain error results; and adjusting the initial values of each mesoscopic parameter according to the error results until the error range is met, and the parameter calibration is completed. The present application can efficiently obtain the stratum mesoscopic parameters required by the discrete element rock breaking model according to the cutting force, provides accurate stratum parameters for subsequent simulation of influence factor analysis and tooth shape optimization, and guarantees the model accuracy. BRIEF DESCRIPTION OF DRAWINGS

[0039] The present application will be further described below in combination with the drawings and embodiments, wherein:

[0040] Figure 1 FIG. 1 is a flowchart of the discrete element stratum model mesoscopic parameter calibration method provided by the embodiment of the present application;

[0041] Figure 2 FIG. 2 is a logic block diagram of the discrete element stratum model mesoscopic parameter calibration system provided by the embodiment of the present application;

[0042] Figure 3 FIG. 3 is a schematic diagram of the interaction mechanism between the drill tooth and the stratum rock provided by the embodiment of the present application;

[0043] Figure 4 FIG. 4 is a schematic diagram of the rock intrinsic specific energy calculation process provided by the embodiment of the present application;

[0044] Figure 5 FIG. 5 is a rock breaking model based on PDFC3D provided by the embodiment of the present application;

[0045] Figure 6 FIG. 6 is a result comparison diagram provided by the embodiment of the present application. DETAILED DESCRIPTION

[0046] The technical solutions in the embodiments of the present application will be clearly and completely described below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative efforts fall within the scope of the present application.

[0047] The present application provides a discrete element stratum model mesoscopic parameter calibration method, which is a discrete element stratum model mesoscopic parameter calibration method based on logging parameters. The purpose is to complete the discrete element stratum modeling and mesoscopic parameter calibration in the case of lacking core data, and provide technical support for deep hard stratum drill bit selection.

[0048] Reference Figure 1 , Figure 1 A preferred embodiment of the method for calibrating micro parameters of a discrete element formation model is shown.

[0049] Specifically, as shown in the figure, the method for calibrating micro parameters of a discrete element formation model comprises the following steps: Figure 1

[0050] Step S100: Calculate the average cutting force by using the intrinsic specific energy calculation method to obtain first data.

[0051] Optionally, in the embodiment of the present application, the method for calculating the average cutting force by using the intrinsic specific energy calculation method to obtain the first data comprises: collecting logging data, and constructing a basic database based on the logging data; determining the cutting depth of the drill bit based on the logging data; calculating the average value of the cutting force in the horizontal direction according to the cutting depth and the drill bit parameters to obtain the first data.

[0052] The logging data includes but is not limited to: rate of penetration, rotation speed, drilling pressure, drill bit model and drill bit parameters. The drill bit parameters include but are not limited to: tooth shape, drill bit radius and back rake angle, etc.

[0053] In the embodiment of the present application, the cutting depth of the drill bit is determined based on the logging data, which comprises: calculating the cutting depth of the drill bit according to the rate of penetration and the rotation speed. Specifically, the calculation formula of the cutting depth of the drill bit is as follows:

[0054]

[0055] (1) In the formula, d represents the depth of the drill bit (i.e. the cutting depth of the drill bit), m; V represents the rate of penetration, m / h; U represents the rotation speed, r / min.

[0056] In the embodiment of the present application, the calculation of the average value of the cutting force in the horizontal direction and the average value of the cutting force in the vertical direction according to the cutting depth and the drill bit parameters comprises: calculating the intrinsic specific energy of rock according to the back rake angle, the drilling pressure, the drill bit radius and the cutting depth; calculating the average value of the cutting depth of the drill bit of multiple groups of data and the average value of the intrinsic specific energy of rock of multiple groups of data; calculating the average value of the cutting force in the horizontal direction according to the average value of the cutting depth of the drill bit, the average value of the intrinsic specific energy of rock and the width of the drill bit cross section.

[0057] In the embodiment of the present application, the calculation formula of the intrinsic specific energy of rock is as follows:

[0058]

[0059] (2) In the formula, ε represents the intrinsic specific energy of rock, Pa; r represents the drill bit radius, m; d represents the cutting depth of the drill bit, m; P represents the drilling pressure, MPa.​b The drill bit radius is represented by W, the drill pressure in tons (t), and the cutting depth in meters (d). The backslope angle of the drill bit is expressed in °.

[0060] It should be noted that in the discrete element rock breaking model, the drill teeth (also called cutting teeth) are considered rigid bodies, and there is no wear during the cutting process. The intrinsic rock energy increases as the drill teeth wear more. Therefore, when calculating the average cutting force, data from the portion where the intrinsic rock energy does not increase significantly should be used. The average cutting depth d (i.e., the average cutting depth of the drill teeth across multiple data sets) and the average intrinsic rock energy ε (i.e., the average intrinsic rock energy across multiple data sets) of this portion of the data should be calculated separately. The calculation formulas are as follows:

[0061]

[0062] (3) In the formula, d ave m represents the average depth of cut (i.e., the average depth of cut of the drill teeth). n represents the number of groups, i represents the i-th group, and d represents the average depth of cut. i This represents the cutting depth calculated based on the i-th set of data according to equation (1).

[0063]

[0064] (4) In the formula, ε ave Pa represents the average intrinsic rock energy (i.e., the average intrinsic rock energy). n represents the group number, i represents the i-th group, and ε represents the mean intrinsic rock energy. i This represents the intrinsic energy of the rock calculated based on the i-th set of data according to equation (2).

[0065] Next, based on the average value of the drill bit cutting depth and the average value of the rock's intrinsic energy, the average value of the horizontal cutting force can be calculated. The calculation formula is as follows:

[0066] F cs =ε ave wd ave (5);

[0067] (5) In the formula, F cs represents the average cutting force in the horizontal direction, in N; w represents the width of the tangential cross-section of the drill tooth, in m.

[0068] Step S200: Calculate the average cutting force using the discrete element method to obtain the second data.

[0069] Optionally, in the embodiment of the present application, the average cutting force is calculated by using the discrete element simulation method, and obtaining the second data comprises: establishing a discrete element rock breaking model based on a preset discrete element method, and assigning initial values of each microscopic parameter of the discrete element rock breaking model; setting a cutting depth and a cutting speed in the discrete element rock breaking model to obtain average values of the tangential cutting force under different conditions; and the average values of the tangential cutting force under different conditions are the second data.

[0070] In the embodiment of the present application, the preset discrete element method is a discrete element method based on PFC3D software, and the discrete element rock breaking model (including a drill bit model and a formation model (as shown in Figure 5 illustrated)) is established by using the PFC3D software. Among them, for the formation model, the cementation between the formation particles adopts a parallel bonding mode, and by using the parallel bonding mode, bidirectional transmission of force and torque at the contact point can be realized, which is more in line with the mechanical behavior of actual rock. After the construction of the discrete element rock breaking model is completed, the initial values of each microscopic parameter of the discrete element rock breaking model are assigned. Among them, each microscopic parameter includes but is not limited to: particle contact module emod, normal shear stiffness ratio krat, parallel key modulus pb_emod, parallel key tensile strength pb_ten, and parallel key cohesion pb_coh. It should be noted that each microscopic parameter refers to each microscopic parameter of the formation model.

[0071] After the assignment of the initial values is completed, the average value of the rotational speed is calculated, and the corresponding linear speed thereof is taken as the cutting speed v s of the model drill bit, m / s, and the calculation formula is as follows:

[0072]

[0073] In formulas (6) and (7), U ave represents the average value of the rotational speed, r / min; v s represents the linear cutting speed of the drill bit, m / s; and Ω represents the rotational speed of the drill bit, rpm.

[0074] Then, the discrete element rock breaking model is started to run, wherein the fixed cutting depth is the average depth of cut d ave , and the cutting speed of the drill bit is v s . The cutting force F x of the drill bit in the x direction is detected, and the average value F is obtained. The calculation formula is as follows:

[0075]

[0076] In formula (8), F represents the average value of the tangential cutting force, N; and F represents the i-th tangential cutting force.

[0077] Step S300: Calculate the error based on the first data and the second data to obtain the error result.

[0078] Optionally, in this embodiment of the invention, the error calculation based on the first data and the second data to obtain the error result includes: calculating the error of the average horizontal cutting force in the first data and the average tangential cutting force in the second data to obtain the error result.

[0079] Specifically, the formula for calculating the error is as follows:

[0080]

[0081] (11) In the formula, γ is the error result, %.

[0082] Step S400: Adjust the initial values ​​of each micro-parameter according to the error results until the error range is met, and complete the parameter calibration.

[0083] Optionally, in this embodiment of the invention, adjusting the initial values ​​of various micro-parameters according to the error result until the error range is met, and completing the parameter calibration includes: determining whether the value of the error result is less than a set value; if yes, then determining that the error range is met; if no, then determining that the error range is not met, and adjusting the initial values ​​of various micro-parameters until the error range is met.

[0084] Specifically, determine whether the calculated γ is less than 5%. If it is less than 5%, the condition is met. If it is greater than 5%, adjust the initial values ​​of each micro-parameter and continue running the model until the calculated error value is less than 5%, at which point the parameter calibration ends.

[0085] Unlike traditional methods, this invention directly corrects the micro-parameters of the discrete element rock breaking model based on the cutting force obtained from logging parameter inversion, without being limited by core data. Traditional discrete element formation calibration relies on formation core sampling and uses rock mechanics parameters obtained from uniaxial core tests and Brazilian fracturing tests for verification and calibration. When core data is unavailable, it is difficult to calibrate the micro-parameters of the formation model. This invention effectively solves the problem of discrete element formation model parameter calibration when core data is missing.

[0086] refer to Figure 2 , Figure 2 This invention provides a micro-parameter calibration system for discrete element stratigraphic models.

[0087] like Figure 2 As shown, the discrete element stratigraphic model micro-parameter calibration system includes:

[0088] Intrinsic calculation unit 201 is used to calculate the average cutting force using the intrinsic specific energy calculation method to obtain the first data.

[0089] A discrete simulation unit 202 is configured to calculate the average cutting force by using a discrete element simulation method to obtain second data.

[0090] An error calculation unit 203 is configured to perform error calculation based on the first data and the second data to obtain an error result.

[0091] A parameter adjustment unit 204 is configured to adjust the initial values of the mesoscopic parameters according to the error result until the error range is satisfied, and complete parameter calibration.

[0092] Specifically, the specific cooperation operation process between the units in the mesoscopic parameter calibration system of the discrete element formation model can refer to the above-mentioned mesoscopic parameter calibration method of the discrete element formation model, which will not be described here.

[0093] The following is described with a specific embodiment. Specifically, the steps of the embodiment are specifically as follows:

[0094] Step a. Collecting field logging data including drilling speed, drilling pressure, rotation speed and bit type, etc. Collecting downhole vibration data including bit rotation speed.

[0095] b. Determining the bit depth of cut according to the mechanical drilling speed and the bit rotation speed.

[0096] c. Calculating the rock specific energy according to the bit size, back rake angle, drilling pressure and cutting depth.

[0097] d. Obtaining the average value of the cutting depth and the rock specific energy.

[0098] e. Calculating the average value of the horizontal and vertical cutting forces according to the average value of the rock specific energy and the cutting depth.

[0099] f. Establishing the bit model and the formation model by using the PFC3D discrete element method, and giving the initial values of the mesoscopic parameters to the parallel bonding of the formation particles.

[0100] g. Setting the cutting depth and the cutting speed in the discrete element rock breaking model to obtain the average values of the tangential and vertical cutting forces under different conditions.

[0101] h. Comparing the average values of the cutting forces calculated from the logging data with the average values of the tangential cutting forces obtained from the discrete element rock breaking model to calculate the error.

[0102] i. Judging whether the error is within the allowable range (less than 5%), if not, adjusting the mesoscopic parameters and repeating f to h until the requirement is met.

[0103] Wherein, Figure 3 The interaction mechanism between the bit and the formation rock is shown, which shows the mechanical mechanism in the bit rock breaking process. Figure 4The calculation process of the intrinsic specific energy of the rock is shown. Figure 5 A discrete element rock breaking model based on PFC3D is shown. Figure 6 The comparison between the test value and the calculated value is given.

[0104] As can be seen from the above examples, in the case that the entity core cannot be obtained on site, the formation micro parameter required by the discrete element rock breaking model can be efficiently obtained according to the cutting force by combining the logging parameters and the drill-bit-formation interaction model, the calibration of the micro parameter of the discrete element formation model is effectively completed, a set of accurate formation parameters is provided for the subsequent simulation of the influence factor analysis and the tooth shape optimization, and the model accuracy is ensured.

[0105] In addition, the electronic device of the present application comprises a memory and a processor; the memory is used for storing a computer program; the processor is used for executing the computer program to realize the micro parameter calibration method of the discrete element formation model according to any one of the above. Specifically, according to the embodiments of the present application, the process described above with reference to the flow chart can be realized as a computer software program. For example, the embodiments of the present application comprise a computer program product comprising a computer program carried on a computer readable medium, and the computer program comprises program codes for executing the method shown in the flow chart. In such embodiments, the computer program can be downloaded and installed by the electronic device and executed to perform the above functions defined in the method of the embodiments of the present application. The electronic device in the present application can be a notebook, a desktop, a tablet computer, a smart phone and the like terminal, and can also be a server.

[0106] In addition, the present application also provides a storage medium storing a computer program, which is executed by a processor to implement the method for calibrating micro parameters of a discrete element stratum model according to any one of the above. Specifically, it should be noted that the storage medium of the present application can be a computer readable signal medium or a computer readable storage medium or any combination of the above two. The computer readable storage medium may, for example, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination of the above. More specific examples of the computer readable storage medium can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device or component. In the present application, the computer readable signal medium can include a data signal carried in a baseband or as a part of a carrier wave, which carries computer readable program code. Such a propagated data signal can take various forms, including but not limited to an electromagnetic signal, an optical signal or any suitable combination of the above. The computer readable signal medium can also be any computer readable medium other than the computer readable storage medium, which can send, propagate or transmit a program for use by or in conjunction with an instruction execution system, device or component. The program code contained in the computer readable medium can be transmitted by any suitable medium, including but not limited to an electrical wire, an optical cable, an RF (radio frequency) or the like, or any suitable combination of the above.

[0107] The above computer readable medium can be contained in the above electronic device or can exist separately and not be assembled into the electronic device.

[0108] The various embodiments in the specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other. For the device disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method part.

[0109] Those skilled in the art will further realize that the mere conception of the examples described herein is not inducing the patentable subject matter recited in each claim. The combinations and / or sequences of various example elements, steps, operations, actions, and / or functions described in each example are not necessarily the only possible combinations and / or sequences for practicing the claimed subject matter. Those skilled in the art will further realize that the mechanisms of the various examples described herein are for implementing the several embodiments and are not meant to be limiting as to the scope of the claimed subject matter. That is, the protection afforded to the claimed subject matter is not limited to the mechanisms of practicing the described examples. Therefore, the claimed subject matter should be understood to encompass a variety of subject matter, and equally obvious to those in the art, including but not limited to the following:

[0110] The steps of a method or algorithm described in connection with the examples disclosed herein can be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module can reside in RAM, flash memory, ROM, electrically programmable ROM (EPROM or EEPROM), registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium can be integral to the processor. The processor and the storage medium can reside in an ASIC.

[0111] The examples described herein are only intended to illustrate the technical concepts and features of the present application, and the purpose is to enable those skilled in the art to understand the content of the present application and to implement it accordingly, and cannot limit the protection scope of the present application. Any equivalent changes and modifications made within the scope of the claims of the present application shall be included in the scope of the claims of the present application.

Claims

1. A method for calibrating mesoscopic parameters of a discrete element formation model, characterized in that, The method comprises the following steps: calculating the average cutting force by using an intrinsic specific energy calculation method to obtain first data; calculating the average cutting force by using a discrete element simulation method to obtain second data; performing error calculation based on the first data and the second data to obtain an error result; adjusting initial values of various mesoscopic parameters according to the error result until an error range is met, and completing parameter calibration.

2. The method of calibrating mesoscopic parameters of a discrete element formation model according to claim 1, characterized in that, The method of calculating the average cutting force by using the intrinsic specific energy calculation method to obtain the first data comprises: collecting logging data and constructing a basic database based on the logging data; determining a drill bit cutting depth based on the logging data; calculating an average value of the horizontal direction cutting force according to the cutting depth and drill bit parameters to obtain the first data.

3. The method of calibrating mesoscopic parameters of a discrete element formation model according to claim 2, characterized in that, The logging data comprises a rate of penetration, a rotation speed, a drilling pressure, a drill bit type and the drill bit parameters. The method of determining the drill bit cutting depth based on the logging data comprises: calculating the drill bit cutting depth according to the rate of penetration and the rotation speed.

4. The method of calibrating mesoscopic parameters of a discrete element formation model according to claim 2, wherein, The drill bit parameters comprise a tooth shape, a drill bit radius and a back rake angle. The method of calculating the average value of the horizontal direction cutting force according to the cutting depth and the drill bit parameters comprises: calculating rock intrinsic specific energy according to the back rake angle, the drilling pressure, the drill bit radius and the cutting depth; calculating an average value of the drill bit cutting depth of multiple groups of data and an average value of the rock intrinsic specific energy of multiple groups of data; calculating the average value of the horizontal direction cutting force according to the average value of the drill bit cutting depth, the average value of the rock intrinsic specific energy and a width of a drill bit cutting cross section.

5. The method of calibrating mesoscopic parameters of a discrete element formation model according to claim 1, wherein, The method of calculating the average cutting force by using the discrete element simulation method to obtain the second data comprises: establishing a discrete element rock breaking model based on a preset discrete element method and assigning initial values of various mesoscopic parameters of the discrete element rock breaking model; setting a cutting depth and a cutting speed in the discrete element rock breaking model to obtain average values of tangential cutting forces under different conditions; the average values of the tangential cutting forces under the different conditions are the second data.

6. The discrete element formation model mesoscopic parameter calibration method according to claim 1, characterized in that, The method of performing error calculation based on the first data and the second data to obtain an error result comprises: performing error calculation on the average value of the horizontal direction cutting force in the first data and the average value of the tangential cutting force in the second data to obtain the error result.

7. The discrete element formation model mesoscopic parameter calibration method according to claim 1, characterized in that, The method of adjusting the initial values of various mesoscopic parameters according to the error result until the error range is met, and completing parameter calibration comprises: determining whether the error result is less than a set value; if yes, determining that the error range is met; if no, determining that the error range is not met, and adjusting the initial values of various mesoscopic parameters until the error range is met.

8. A discrete element formation model mesoscopic parameter calibration system, characterized in that, The method comprises: an intrinsic calculation unit, configured to calculate the average cutting force by using the intrinsic specific energy calculation method to obtain the first data; a discrete simulation unit, configured to calculate the average cutting force by using the discrete element simulation method to obtain the second data; an error calculation unit, configured to perform error calculation based on the first data and the second data to obtain an error result; and an adjustment unit, configured to adjust the initial values of various mesoscopic parameters according to the error result until the error range is met, and complete parameter calibration. A parameter adjusting unit is configured to adjust initial values of each mesoscopic parameter according to the error result until the error range is satisfied, and complete the parameter calibration.

9. A storage medium, characterized by The storage medium stores a computer program, and the computer program is adapted to be loaded by the processor to execute the steps of the method for calibrating mesoscopic parameters of a discrete element formation model according to any one of claims 1 to 7.

10. An electronic device, comprising: The device comprises a memory and a processor, and the memory stores a computer program, and the processor executes the steps of the method for calibrating mesoscopic parameters of a discrete element formation model according to any one of claims 1 to 7 by calling the computer program stored in the memory.

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