CN102852511B - A kind of intelligent drilling control system and method for oil-well rig - Google Patents

Abstract

The invention discloses an intelligent drilling control system and control method for drilling control of an oil drilling rig. The intelligent drilling control system includes a drilling drive module, a drilling detection module and a drilling control module. The intelligent control method is a fuzzy control algorithm with parameter self-adjusting ability. The algorithm is composed of two control loops, the inner loop is for drilling speed control, and the outer loop is for drilling pressure control. Each control loop includes four parts: fuzzy controller unit, performance evaluation unit, parameter correction unit, and decision-making unit. It can adjust the parameters of the fuzzy controller adaptively, improve the performance of the controller, and realize the drilling pressure and pressure of the oil drilling rig. Intelligent control of drilling speed. The invention can reduce the labor intensity of workers during the drilling process of the drilling rig, and can improve the accuracy of the wellbore trajectory of the drilling, reduce the wear of the drill bit and increase the drilling speed.

Description

An intelligent drilling control system and method for an oil drilling rig

technical field

The invention relates to the field of engineering machinery, in particular to a control system and a control method of an oil drilling rig used for oil and gas drilling.

Background technique

Drilling is one of the main methods of underground oil extraction. At present, the drilling process of drilling mainly adopts the method of manually operating the drilling rig: the driller adjusts the drilling rig parameters according to the thrust and rotation speed of the drill bit recommended in the drilling rig operation manual, and according to the force feeling of the drilling process. When the drilling rig is drilling, there is not only wet friction between the drill bit of the drilling tool and the rock formation, but also dry friction and semi-dry friction. Manual operation can easily lead to uneven lowering of the upper end of the drilling tool, resulting in uneven load on the drill bit; in addition, the difference in operating technology will also cause sharp fluctuations in the drilling pressure. Therefore, the manual operation method will cause the position of the drilling hole to shift: too low propulsion force will lead to slow diffusion of impact energy, which will slow down the advancement rate of the drill bit; the rotational torque of the drill pipe will become smaller; it will lead to the drilling position The deviation is too large, etc. Excessive propulsion will also increase the position deviation of drilling; it will not increase the rate of advancement of the drill bit. In order to obtain good drilling quality, excessively low rotational speeds need to be avoided. Conversely, an excessively high rotational speed can cause damage to the drill bit.

The method of automatic drilling can eliminate the shortcomings of manual drilling rigs: by collecting parameters during the drilling process, such as drilling pressure, drilling speed, torque, mud performance, rock properties, formation pore pressure, wellbore trajectory, wellbore stability It adopts intelligent control method to make the drilling tool adapt to different rock formations, obtain the best rock formation penetration rate, and maintain the ability of drilling collimation. The intelligent drilling control system can not only maintain the accuracy of drilling parameters, but also reduce drill bit wear, thereby improving drilling quality and economic benefits.

The Chinese invention patent with the application number of 201010115470.4 (a rock drilling rig and its control system and control method) discloses a control system for rock drilling rigs: detecting the depth of the drilling bucket and comparing it with a preset depth reference value, Lift up or press down the drilling bucket according to the comparison result; detect the pressure of the drilling bucket and compare it with the preset pressure reference value, and control the drilling bucket to stop entering the rock or continue to enter the rock according to the comparison result; detect the speed of the drilling bucket and compare it with the speed reference value Compare, and control the main winch to reduce or increase the pressurizing pressure according to the comparison result. US Patent US6732052B2 (Method and Apparatus for Prediction Control in Drilling Dynamics Using Neural Networks) discloses a neural network-based predictive control method for the drilling process. The downhole control computer is used to control the downhole drilling tool assembly, and the drilling efficiency is automatically optimized according to the changes of the drilling parameters and the drilling direction. The prediction model of the drilling process is iteratively updated through the neural network and operation guidance is provided for the driller. In the document "Study on Intelligent Drilling Technology of Oil Drilling Rig" ("Petroleum Machinery", Volume 34, No. 12, 2006, Wang Pingping), an automatic drilling technology for oil drilling rigs based on fuzzy intelligent technology is proposed. The industrial control computer is used to automatically control the drilling rig auxiliary motor, and the fuzzy rules are established according to the control experience of the experienced driller to realize the drilling control with constant drilling pressure.

The traditional drilling control method is mainly to realize the control of the drilling tool drilling by establishing the drilling process model and the feedback of the sensor to the drilling parameters. However, because the drilling process is affected by parameters such as geological conditions, bit wear and mud properties, it is difficult to establish an accurate mathematical model. The intelligent drilling control method can realize the control of nonlinear system without precise mathematical model.

Contents of the invention

(1) Technical problems to be solved

In order to overcome the deficiencies in the prior art, the technical problem to be solved by the present invention is to provide an intelligent drilling control system and control method for an oil drilling rig, which can realize the control of the drilling process of the oil drilling rig without establishing an accurate mathematical model. The control parameters include drilling pressure and drilling speed of the oil drilling rig.

(2) Technical solutions

The present invention proposes an intelligent drilling control system for a drilling rig, the drilling rig includes a drill bit for drilling, and the intelligent drilling control system includes a drilling control module, a drilling detection module, and a drilling drive module; The module is used to obtain the parameters during the drilling process of the drilling rig; the drilling control module is used to calculate the expected drilling pressure and expected drilling speed of the drill bit according to the parameters obtained by the drilling detection module; The WOB and the desired drilling speed are used to drive the drilling rig to drill.

According to a specific embodiment of the present invention, the parameters acquired by the drilling detection module include the vibration amount of the drill bit, drilling pressure, torque, drilling speed and drilling fluid parameters, and the drilling detection module includes a vibration detection unit, a drilling Fluid detection unit, weight-on-bit detection unit, torque detection unit, rotational speed detection unit, drilling speed detection unit, wherein: the vibration detection unit is used to detect the vibration of the drill bit in real time; the drilling fluid detection module is used to detect the parameters of the drilling fluid in real time; The pressure detection unit is used to detect the WOB of the drill bit; the torque detection unit is used to detect the torque of the drill bit; the rotation speed detection unit is used to detect the rotation speed of the drill bit; the drilling speed detection unit is used to detect the WOB of the drill bit. , rotational speed and torque to calculate the drilling speed of the drill bit.

According to a specific embodiment of the present invention, the drilling drive module includes a drill tool hoist unit and a drill tool rotation unit, and the drill tool hoist unit is used to suspend the drill bit and control the weight-on-bit; the drill tool rotation unit The unit is used to drive the drill bit to rotate.

According to a specific embodiment of the present invention, the drilling control module includes an inner ring and an outer ring, the inner ring is used to control the drilling tool rotation unit of the drilling rig, and the outer ring is used to control the drilling tool lifting of the drilling rig unit.

According to a specific embodiment of the present invention, the inner loop includes an inner loop fuzzy controller unit, and the inner loop fuzzy controller unit stores an inner loop scaling factor, an inner loop quantization factor, and an expected performance index, and is used for according to The rotational speed input by the drilling speed detection unit and the inner ring scale factor and the inner ring quantization factor are calculated to obtain the drilling speed fuzzy input amount, and fuzzy reasoning is performed on the drilling speed fuzzy input amount to obtain the drilling speed fuzzy control amount, and according to the The drilling speed fuzzy control quantity calculates the drilling speed digital control quantity used to control the drilling tool rotation unit, and outputs it to the drilling tool rotation unit.

According to a specific embodiment of the present invention, the outer loop includes an outer loop fuzzy controller unit, and the outer loop fuzzy controller unit stores an outer loop scaling factor, an outer loop quantization factor, and an expected performance index for The WOB input by the WOB detection unit and the outer ring scale factor and the outer ring quantization factor are calculated to obtain the WOB fuzzy input amount, and fuzzy reasoning is performed on the WOB fuzzy input amount to obtain the WOB fuzzy control amount, And according to the weight-on-bit fuzzy control amount, calculate the weight-on-bit digital control amount used to control the drilling tool hoisting unit, and output it to the drilling tool hoisting unit.

The present invention also proposes an intelligent drilling control method for a drilling rig, the drilling rig includes a drill bit for drilling, and the method includes the following steps: obtaining parameters during the drilling process of the drilling rig; calculating the obtained parameters according to the obtained parameters The expected drilling pressure and expected drilling speed of the drill bit; according to the expected drilling pressure and expected drilling speed, the drilling machine is driven to drill.

(3) Beneficial effects

The intelligent drilling control system and control method proposed by the present invention are beneficial to reduce the labor intensity of the driller during the drilling process of the drilling rig, improve the accuracy of the wellbore trajectory of drilling, and reduce the wear and penetration rate of the drill bit.

Description of drawings

Fig. 1 shows the module connection schematic diagram of intelligent drilling control system of the present invention;

Fig. 2 shows the working principle diagram of the intelligent drilling control system of the present invention;

Fig. 3 shows the working flow diagram of the drilling detection module of the intelligent drilling control system of the present invention;

Fig. 4 shows the control flow diagram of the adaptive control method of the intelligent drilling control system of the present invention;

Fig. 5 shows the algorithm flowchart of the adaptive parameter adjustment of the intelligent control method of the present invention;

FIG. 6 is a flow chart of the parameter adjustment algorithm of the inner-loop fuzzy controller unit of the present invention.

Detailed ways

In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

During the drilling process of oil drilling rigs, due to the diversity of rock mass structures downhole, when the front end of the drill bit touches rocks of different properties, excessive drilling pressure and drilling speed may cause accidents, such as broken drill pipes, drill bits, and drill bits. Damage, etc.; too low drilling pressure, drilling speed and torque make drilling efficiency very low. Therefore, in a certain formation and a certain depth, proper drilling pressure, drilling speed and torque are very beneficial to drilling, which can not only improve drilling efficiency, but also help reduce drill bit wear.

When the oil drilling rig comes into contact with rocks of different properties, if the drilling pressure, drilling speed and torque cannot be adjusted in real time to keep the drill bit in line with the rock conditions, it will cause the unbalanced load of the drill bit and even break the drill pipe. The weight on bit FT can be expressed as:

F _T ＝MG-F ₁ -F ₂ -F _f

Among them, the net weight of the drilling tool is MG, the buoyancy of the drilling tool in the drilling fluid is F ₁ , the pulling force on the wire rope is F ₂ , and the friction between the drill bit and the rock formation is F _f .

The rate of penetration V _T is related to the rotational speed W _T of the drill bit and the weight on bit F _T . The rotational speed W _T of the drill bit is equal to the rotational speed W _P of the rotary table on the drill pipe.

The intelligent drilling control system proposed by the present invention includes a drilling control module 1 , a drilling detection module 2 and a drilling driving module 3 . The drilling detection module 2 obtains the vibration amount of the drill bit, drilling pressure, torque, drilling speed, etc. and drilling fluid parameters during the drilling process of the drilling rig. The drilling control module 1 obtains the parameters calculated by the drilling detection module 2, and calculates the expected pressure on bit and the expected drilling speed through the adaptive control algorithm unit 11 stored in the drilling control module 1 with parameter self-adjustment capability. The drilling drive module 3 drives the drilling rig to drill according to the desired drilling pressure and desired drilling speed.

The drilling detection module includes: a vibration detection unit 21 , a drilling fluid detection unit 22 , a pressure-on-bit detection unit 23 , a torque detection unit 24 , and a drilling speed detection unit 25 . Wherein: the vibration detection unit 21 detects the vibration amount of the drill bit in the downhole in real time, that is, the amplitude and frequency of the axial vibration force of the drill bit and the amplitude and frequency of the longitudinal vibration force of the drill bit; the drilling fluid detection module 22 detects the vibration near the downhole drill bit in real time The physical and chemical properties of the drilling fluid, including the viscosity, pH value, temperature and drilling hydraulic pressure and other parameter information of the drilling fluid; the pressure on bit detection unit 23 measures the contact pressure between the drill bit and the downhole rock formation in real time; the torque detection unit 24 measures the drilling pressure The torque of the drill bit during the process includes measuring the horizontal resistance when the rock is broken and the frictional resistance with the hole wall when the drilling tool rotates; the rotational speed detection unit 25 detects and measures the rotational speed of the drill bit; , Calculate the rock penetration rate to calculate the rock penetration speed when the drilling rig is drilling, that is, the penetration rate.

The drilling drive module 3 includes a drilling tool hoist unit 31 for suspending the drill bit and controlling the weight-on-bit, and a drilling tool rotation unit 32 for driving the drill bit to rotate to break rock formations. The preferred drilling tool hoisting unit 31 may include a winch , auxiliary brakes, etc. to lift the drilling tool and the mechanism for suspending the drill string and controlling the drilling pressure; the drilling rig rotation unit 32 includes a rotary table, a faucet and a drilling tool, etc., which are used to drive the drilling tool to rotate to break the rock formation.

In order to ensure the smoothness of changes in drilling pressure and drilling speed during drilling, it is necessary to adopt an intelligent control system and control method to control the drilling tool lifting unit 31 and the drilling tool rotating unit 32 of the oil drilling rig.

Fig. 1 is a schematic diagram of module connection of the intelligent drilling control system of the present invention. As shown in FIG. 1 , the action objects of the drilling drive module 3 are downhole rock formations and mud. The output end of the drilling detection module 2 is connected to the input end of the drilling control module 1; the output end of the drilling control module 1 is connected to the drilling drive module 3; the drilling detection module 2 detects the status and action objects of the drilling drive module 3 in real time 4 status.

Fig. 2 is a working principle diagram of the intelligent drilling control system of the present invention. According to the drill bit vibration, drilling fluid parameters, drilling pressure, torque, drill bit speed, and drilling speed output by the drilling detection module 2, the drilling control module 1 calculates the expected drilling pressure and expected drilling speed at the next moment. The expected drilling pressure and expected drilling speed are output to the drilling drive module 3 to adjust the drilling tool lifting unit 31 and the drilling tool rotating unit 32 .

FIG. 3 is a schematic structural diagram of the drilling detection module 2 of the intelligent drilling control system of the present invention. The drilling detection module 2 includes a vibration detection unit 21 , a drilling fluid detection unit 22 , a weight-on-bit detection unit 23 , a torque detection unit 24 , a rotational speed detection unit 25 , and a drilling speed detection unit 26 . Wherein: the vibration detection unit 21 detects the vibration law of the drill bit in the downhole in real time, which can be the amplitude of the axial vibration force and the amplitude of the longitudinal vibration force; Parameters such as viscosity, pH value, temperature, and drilling hydraulic pressure; the WOB detection unit 23 measures the WOB between the drill bit and the downhole rock formation in real time; the torque detection unit 24 measures the horizontal resistance when the drill bit breaks rocks during drilling and the rotation time of the drilling tool The friction resistance with the hole wall is used to obtain the torque; the rotational speed detection unit 25 detects the rotational speed of the drill bit, which can be the rotational speed of the turntable; the drilling speed detection unit 26 calculates the drilling speed according to the rotational speed of the drill bit, the pressure on bit and the torque, as shown in the following formula:

$\mathrm{<span\; class="notranslate">\; APR</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; PR</span>}<span\; class="notranslate">\; /</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; PP</span>}<span\; class="notranslate">\; \&times;</span>\sqrt{\mathrm{<span\; class="notranslate">\; RP</span>}}<span\; class="notranslate">\; )</span>$

Among them, APR represents the drilling speed, PR represents the bit speed, PP represents the bit pressure, and RP represents the torque.

Fig. 4 is a schematic control flow diagram of the adaptive control method of the intelligent drilling control system of the present invention. The self-adaptive control method of the present invention adopts a parameter self-adjusting fuzzy control algorithm, and is composed of two control loops, the inner loop is for drilling speed control, and the outer loop is for drill pressure control.

The drilling control module 1 includes an inner ring and an outer ring, the inner ring includes an inner ring fuzzy controller unit 125, an inner ring performance evaluation unit 135, an inner ring parameter correction unit 145, and an inner ring decision-making unit 155; the outer ring includes an outer ring fuzzy control unit The controller unit 126, the outer loop performance evaluation unit 136, the outer loop parameter correction unit 146, and the outer loop decision unit 156. The drilling speed control of the inner ring consists of four parts: the inner ring fuzzy controller unit 125, the inner ring performance evaluation unit 135, the inner ring parameter correction unit 145, and the inner ring decision-making unit 155. The output of the inner ring controls the drilling tool rotation unit of the drilling rig 31. The weight-on-bit control of the outer ring includes four parts: the outer ring fuzzy controller unit 126, the outer ring performance evaluation unit 136, the outer ring parameter correction unit 146, and the outer ring decision-making unit 156. The output of the outer ring controls the lifting of the drilling rig. Unit 32.

The inner-loop fuzzy controller unit 125 stores an inner-loop scale factor, an inner-loop quantization factor and an expected performance index. The inner-loop scale factor and the inner-loop quantization factor have the same adjustable coefficient P.

The inner-loop proportional factor refers to a parameter in the inner-loop fuzzy controller unit that converts the drilling speed fuzzy control quantity into the drilling speed digital control quantity.

In the formula, K _u is the proportional factor of the inner ring, y _u is the numerical control variable of drilling speed, and L is the supremum of the discourse domain of the fuzzy control variable of drilling speed.

The quantization factor of the inner loop refers to the fuzzy input quantity that converts the error variable between the expected output fuzzy control amount of the drilling speed and the actual output of the drilling speed fuzzy control amount into the corresponding drilling speed error in the inner ring fuzzy controller unit a parameter of .

In the formula, K _e is the quantization factor of the inner ring, x _e is the supremum of the basic domain of discourse of the error variable, and n is the supremum of the domain of discourse of the fuzzy subset of the error variable.

The inner loop fuzzy controller unit 125 is used to calculate the fuzzy input amount of the drilling speed according to the rotational speed input by the drilling speed detection unit 26, the inner loop scaling factor, and the inner loop quantization factor, and fuzzy the drilling speed fuzzy input amount. Inference, obtain the drilling speed fuzzy control quantity, calculate the drilling speed digital control quantity for controlling the drilling tool rotation unit 32 according to the drilling speed fuzzy control quantity, and output to the drilling tool rotation unit 32 .

The inner loop performance evaluation unit 135 is used to calculate a performance evaluation function according to the expected performance index stored by the inner loop fuzzy controller unit 125 and the parameters in the actual drilling process detected by the drilling detection module 2 V(x), the performance evaluation function V(x) is used to evaluate the degree of compliance between the detected parameters and the expected performance indicators.

The inner ring parameter correction unit 145 is used to calculate the correction amount ΔP of the adjustable coefficient P according to the digital control amount of the drilling speed.

The inner loop decision-making unit 155 is used to compare the evaluation function of the adjustable coefficient P at P _t , P _t +ΔP, and P _t −ΔP according to the adjustable coefficient P _t at the current moment t and the correction amount ΔP V(x), V ⁺ (x), V- ⁽ x), select the adjustable coefficient corresponding to the maximum value as the adjustable coefficient of the inner ring scale factor and the inner ring quantization factor at the next moment t+1.

The outer-loop fuzzy controller unit 126 stores the outer-loop scale factor, the outer-loop quantization factor and the expected performance index, and the outer-loop scale factor and the outer-loop quantization factor have the same adjustable coefficient P.

The outer loop proportional factor refers to a parameter in the outer loop fuzzy controller unit that converts the fuzzy control amount of the weight on bit into the digital control amount of the bit pressure.

The outer ring quantization factor refers to the fuzzy input amount of the outer ring fuzzy controller unit, which converts the error between the expected output fuzzy control amount of bit pressure and the actual output bit pressure fuzzy control amount into the corresponding bit rate error a parameter of .

The outer ring fuzzy controller unit 125 is used to calculate the weight on bit fuzzy input amount according to the weight on bit input by the weight on bit detection unit 23, the outer ring scaling factor, and the outer ring quantization factor, and perform the fuzzy input amount of the weight on bit Fuzzy inference obtains the weight-on-bit fuzzy control amount, and calculates the digital control amount of the weight-on-bit for controlling the drilling tool hoisting unit 31 according to the bit weight fuzzy control amount, and outputs it to the drilling tool hoisting unit 31 .

The outer loop performance evaluation unit 136 is used to calculate a performance evaluation function V (x) according to the expected performance index stored by the outer ring fuzzy controller unit 126 and the actual parameters detected by the drilling detection module 2, the performance evaluation The function V(x) is used to evaluate the degree of conformity between the actual performance index and the expected performance index.

The outer ring parameter correction unit 146 is used to calculate the correction amount ΔP of the adjustable coefficient P according to the digital control amount of the weight on bit.

The outer loop decision unit 156 is used to compare the evaluation function of the adjustable coefficient P at P _t , P _t +ΔP, and P _t −ΔP according to the adjustable coefficient P _t at the current moment t and the correction amount ΔP V(x), V ⁺ (x), V- ⁽ x), select the adjustable coefficient corresponding to the maximum value as the adjustable coefficient of the outer ring scale factor and the outer ring quantization factor at the next moment t+1.

Fig. 5 is a flow chart of the adaptive control method of the intelligent drilling control system of the present invention. As mentioned above, the method of the present invention is realized by the inner loop and the outer loop of the drilling control module 1. Generally speaking, the present invention first establishes the initial control parameters of the fuzzy controller unit, and then performs the fuzzy controller unit based on the reinforcement learning algorithm. parameter adjustment.

The method of the present invention is described below by taking the parameter adjustment of the inner fuzzy controller unit 125 in the drilling speed control loop as an example, and the steps of parameter adjustment of the outer fuzzy controller unit 126 in the drilling pressure control loop are similar.

Inner loop control methods include:

A1: Initialize the control parameters of the inner loop fuzzy controller unit 125, preferably, the control parameters include the inner loop scaling factor and the inner loop quantization factor.

A2: The inner-ring fuzzy controller unit 125 receives the drilling speed provided by the drilling speed detection unit 26, and according to the initial value of the inner-ring scale factor and the initial value of the inner-ring quantization factor, the input drilling speed becomes an inner ring The drilling speed fuzzy input required by the fuzzy controller unit 125;

A3: The inner-loop fuzzy controller unit 125 performs fuzzy reasoning on the fuzzy input quantity of the drilling speed according to a fuzzy rule base to obtain the fuzzy control quantity of the drilling speed.

A4: The inner-loop fuzzy controller unit 125 transforms the drilling speed fuzzy control quantity obtained by fuzzy inference into the drilling speed digital control quantity actually used to control the drilling tool rotation unit 32 , and then outputs it to the drilling tool rotation unit 32 .

A5: Adjust the inner-loop scale factor and inner-loop quantization factor of the inner-loop fuzzy controller unit 125 .

The adjustment method of the inner ring scale factor and the inner ring quantization factor will be described below.

A6: Return to step A2.

FIG. 6 is a flow chart of the method for adjusting the inner-loop scale factor and the inner-loop quantization factor of the inner-loop fuzzy controller unit 125 of the present invention.

According to the present invention, the inner ring quantization factor and the inner ring scale factor have the same adjustable coefficient P. By adjusting P, the adjusted inner ring scale factor and inner ring quantization factor can be obtained. The specific steps are described as follows:

B1: Set the desired performance index of the inner-loop fuzzy controller unit 125, preferably the rise time, overshoot and amplitude of the step response of the fuzzy controller unit 125 can be set.

B2: the inner loop performance evaluation unit 135 is used to calculate a performance evaluation function V (x) according to the desired performance index of the inner loop fuzzy controller unit 125 and the actual performance index detected by the drilling detection module 2, the The performance evaluation function V(x) is used to evaluate the degree of conformity between the actual performance index and the expected performance index.

Preferably, the calculation formula of the evaluation function V(x) is as follows:

$\mathrm{<span\; class="notranslate">\; V</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; exp</span>}<span\; class="notranslate">\; (</span><span\; class="notranslate">\; -</span>{<span\; class="notranslate">\; (</span>\frac{{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; r</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; r</span>}}^{\mathrm{<span\; class="notranslate">\; d</span>}}}{{\mathrm{<span\; class="notranslate">\; \&beta;</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span>{<span\; class="notranslate">\; (</span>\frac{{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; o</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; o</span>}}^{\mathrm{<span\; class="notranslate">\; d</span>}}}{{\mathrm{<span\; class="notranslate">\; \&beta;</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\frac{{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}^{\mathrm{<span\; class="notranslate">\; d</span>}}}{{\mathrm{<span\; class="notranslate">\; \&beta;</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span>$

Among them, β ₁ , β ₂ , β ₃ are the width of the set evaluation function; x ₀ , x _r , x _a are the actual rise time, overshoot and amplitude of the step response respectively; x ^d _o , x ^d _r , x ^d _r are the expected rise time, overshoot and amplitude respectively; evaluation function V(x)∈[0,1].

B3: The inner loop parameter adjustment unit 145 calculates the correction amount ΔP of the adjustable coefficient P according to the digital control amount of the drilling speed. Preferably, the calculation of the correction amount ΔP is as follows:

$\mathrm{<span\; class="notranslate">\; \&Delta;P</span>}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}}<span\; class="notranslate">\; )</span>\frac{{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}{{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}}$

Among them, ΔP is the correction amount of the coefficient P, α ₀ is the initial learning rate, V _t is the evaluation function value at time t, and P _t is the adjustable coefficient of the fuzzy controller at time t.

B4: The inner loop decision-making unit compares the evaluation function V of the adjustable coefficient P at P _t , P _t +ΔP, and P _t -ΔP according to the adjustable coefficient P _t at the current moment t and the correction amount ΔP (x), V ⁺ (x), V ^- (x), select the adjustable coefficient P corresponding to the maximum value as the adjustable coefficient P of the inner ring scale factor and the inner ring quantization factor at the next moment t+1.

Outer loop control methods include:

C1: Initialize the control parameters of the outer loop fuzzy controller unit 126, preferably, the control parameters include the outer loop scaling factor and the outer loop quantization factor.

C2: The outer ring fuzzy controller unit 126 receives the WOB provided by the WOB detection unit 23, and according to the initial value of the outer ring scale factor and the initial value of the outer ring quantization factor, the input WOB is changed into an outer ring The fuzzy input amount of WOB required by the fuzzy controller unit 126;

C3: The outer ring fuzzy controller unit 126 performs fuzzy reasoning on the fuzzy input quantity of the weight on bit according to a fuzzy rule base to obtain the fuzzy control amount of the bit pressure.

C4: The outer ring fuzzy controller unit 126 converts the weight-on-bit fuzzy control amount obtained by fuzzy reasoning into the digital control amount of the weight-on-bit actually used to control the drilling tool lifting unit 31 , and then outputs it to the weight-on-bit lifting unit 31 .

C5: Adjust the outer loop scale factor and outer loop quantization factor of the outer loop fuzzy controller unit 126 .

The steps of adjusting the scale factor of the outer loop and the quantization factor of the outer loop are similar to the steps of adjusting the scale factor of the inner loop and the quantization factor of the outer loop, and will not be repeated here.

C6: return to step C2.

The specific embodiments described above have further described the purpose, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above descriptions are only specific embodiments of the present invention, and are not intended to limit the present invention. Within the spirit and principles of the present invention, any modifications, equivalent replacements, improvements, etc., shall be included in the protection scope of the present invention.

Claims (4)

1. an intelligent drilling control system of a drilling rig, the drilling rig comprises a drill bit for drilling, it is characterized in that the intelligent drilling control system comprises a drilling control module (1), a drilling detection module (2) , drilling drive module (3); The drilling detection module (2) is used to obtain the parameters in the drilling process of the drilling rig, and the parameters include the vibration amount of the drill bit, the drilling pressure button moment, the drilling speed and the parameters of the drilling fluid. The drilling detection module (2) includes the drilling Speed detection unit (26) and drilling pressure detection module (23), described drilling speed detection unit (26) calculates drilling speed according to following formula: Among them, APR represents the drilling speed, PR represents the speed of the drill bit, PP represents the drilling pressure of the drill bit, and RP represents the torque of the drill bit; The pressure-on-bit detection module (23) is used to measure the contact pressure between the drill bit and the downhole formation in real time; The drilling control module (1) is used to calculate the expected drilling pressure and expected drilling speed of the drill bit according to the parameters obtained by the drilling detection module (2); The drilling driving module (3) drives the drilling rig to drill according to the expected drilling pressure and expected drilling speed, and the drilling driving module (3) includes a drilling tool lifting unit (31) and a drilling tool rotating unit ( 32), the drilling tool lifting unit (31) is used to suspend the drill bit and control the drilling pressure, and the drilling tool rotating unit (32) is used to drive the drill bit to rotate; The drilling control module (1) includes an inner ring and an outer ring, the inner ring is used to control the drilling tool rotation unit (31), and the outer ring is used to control the drilling tool lifting unit (32); The inner loop comprises an inner loop fuzzy controller unit (125), an inner loop performance evaluation unit (135), an inner loop parameter correction unit (145) and an inner loop decision unit (155), and the inner loop fuzzy controller unit ( 125) storing the inner ring scale factor, the inner ring quantization factor and the expected performance index, which are used to calculate the drilling speed according to the drilling speed input by the drilling speed detection unit (26) and the inner ring scaling factor and the inner ring quantization factor Fuzzy input quantity, and carry out fuzzy reasoning on the fuzzy input quantity of the drilling speed, obtain the drilling speed fuzzy control quantity, and calculate the drilling speed digital control quantity for controlling the drilling tool rotation unit (32) according to the drilling speed fuzzy control quantity, and output To the drilling tool rotation unit (32), the inner ring scaling factor and the inner ring quantization factor have the same adjustable coefficient P; the inner ring performance evaluation unit (135) is used to The expected performance index stored by the unit (125) and the parameters detected by the drilling detection module (2) calculate a performance evaluation function V (x), and this performance evaluation function is used to evaluate the detected parameters and expected performance The degree of conformity of the index; the inner ring parameter correction unit (145) is used to calculate the correction amount ΔP of the adjustable coefficient P according to the drilling speed digital control amount; the inner ring decision unit (155) is used to The adjustable coefficient P _t at the current moment _t and the correction amount _ΔP are compared with the performance evaluation functions V( _x ), V ⁺ ( x), V- ⁽ x), select the adjustable coefficient corresponding to the maximum value as the adjustable coefficient of the inner ring scale factor and the inner ring quantization factor at the next moment t+1; The outer loop comprises an outer loop fuzzy controller unit (126), an outer loop performance evaluation unit (136), an inner loop parameter correction unit (146) and an inner loop decision unit (156), and the outer loop fuzzy controller unit ( 126) storing the outer ring scale factor, the outer ring quantization factor and the expected performance index, which are used to calculate the weight on bit according to the weight on bit input by the weight-on-bit detection module (23) and the outer ring scale factor and the outer ring quantization factor fuzzy input amount, and perform fuzzy reasoning on the fuzzy input amount of the weight-on-bit to obtain the fuzzy control amount of the weight-on-bit, and calculate the digital control amount of the weight-on-bit for controlling the drilling tool lifting unit (31) according to the fuzzy control amount of the weight-on-bit, Output to the drilling tool lifting unit (31), the outer ring scale factor and the outer ring quantization factor have the same adjustable coefficient P; the outer ring performance evaluation unit (136) is used to The expected performance index stored by the controller unit (126) and the parameters detected by the drilling detection module (2) calculate a performance evaluation function V (x), which is used to evaluate the detected parameters and The degree of compliance with the expected performance index; the outer ring parameter correction unit (146) is used to calculate the correction amount ΔP of the adjustable coefficient P according to the digital control value of the weight-on-bit; the outer ring decision unit (155) is used to According to the adjustable coefficient P _t at the current moment _t and the correction amount _ΔP , compare the performance evaluation functions V( _x ), V ⁺ (x), V- ⁽ x), select the adjustable coefficient corresponding to the maximum value as the adjustable coefficient of the outer ring scale factor and the outer ring quantization factor at the next moment t+1; The calculation of the correction amount ΔP is as follows: $\mathrm{<span\; class="notranslate">\; \&Delta;</span>}\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}}<span\; class="notranslate">\; )</span>\frac{{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}{{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}}<span\; class="notranslate">\; ,</span>$ Among them, ΔP is the correction amount of coefficient P, α ₀ is the initial learning rate, V _t is the performance evaluation function value at time t, and P _t is the adjustable coefficient of the fuzzy controller at time t; The calculation formula of the performance evaluation function V (x) is as follows: $\mathrm{<span\; class="notranslate">\; V</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; exp</span>}<span\; class="notranslate">\; (</span><span\; class="notranslate">\; -</span>{<span\; class="notranslate">\; (</span>\frac{{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; r</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; r</span>}}^{\mathrm{<span\; class="notranslate">\; d</span>}}}{{\mathrm{<span\; class="notranslate">\; \&beta;</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span>{<span\; class="notranslate">\; (</span>\frac{{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; o</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; o</span>}}^{\mathrm{<span\; class="notranslate">\; d</span>}}}{{\mathrm{<span\; class="notranslate">\; \&beta;</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\frac{{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}^{\mathrm{<span\; class="notranslate">\; d</span>}}}{{\mathrm{<span\; class="notranslate">\; \&beta;</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>$ Among them, β ₁ , β ₂ , β ₃ are the width of the set performance evaluation function; x _o , x _r , x _a are the actual rise time, overshoot and amplitude of the step response respectively, x ^d _o , x ^d _r , x ^d _r are the expected rise time, overshoot and amplitude respectively, and the performance evaluation function V(x)∈[0,1]. 2. The intelligent drilling control system according to claim 1, characterized in that, the drilling detection module (2) also includes a vibration detection unit (21), a drilling fluid detection unit (22) and a torque detection unit (24 ),in: The vibration detection unit (21) is used to detect the vibration amount of the drill bit in real time; The drilling fluid detection module (22) is used to detect the parameters of the drilling fluid in real time; The torque detecting unit (24) is used for detecting the torque of the drill bit. 3. The intelligent drilling control system according to claim 2, wherein the vibration amount of the drill bit includes the amplitude and frequency of the axial vibration force of the drill bit, and the amplitude and frequency of the longitudinal vibration force of the drill bit. 4. The intelligent drilling control system according to claim 2, wherein the parameters of the drilling fluid include viscosity, pH value, temperature and drilling hydraulic pressure of the drilling fluid.