Rescue drilling machine multi-model predictive control method for complex formation drilling

Abstract

The invention discloses a rescue drilling machine multi-model predictive control method for complex stratum drilling. The method comprises the following steps that a bit pressure control system model of a rescue drilling machine with voltage as input and bit pressure as output is established for each stratum based on a finite element method; performing rigid-flexible mode separation on the bit pressure control system model of each stratum based on a frequency domain analysis method, and establishing a reduced-order model of the bit pressure control system model of each stratum; a corresponding feeding damping coefficient is determined under each stratum, the multiple stratums are in one-to-one correspondence with the multiple order reduction models, and each stratum is provided with a controller in advance; and when the stratum condition changes, the corresponding controller is switched to predict and control the bit pressure according to the stratum condition. According to the method, the formation change can be quickly responded, and the bit pressure is adjusted to keep the stability and efficiency of the drilling process, so that the bit pressure can be always stabilized within the safety range of the set value under different formations.

Description

Technical Field

[0001] The invention relates to the technical field of rescue drilling rigs, and in particular to a multi-model predictive control method for a rescue drilling rig for drilling in complex formations. Background Art

[0002] In the past decade, my country has experienced many coal mine accidents, resulting in huge losses of life and property. In order to ensure rapid rescue after a coal mine accident, China is in urgent need of a fast mobile rescue equipment with efficient drilling capabilities as the main force for post-accident rescue. Rescue drills are currently widely used rescue equipment in coal mine accidents, and they must have the ability to stabilize drilling pressure under different formation conditions.

[0003] In the related art, PID control and fuzzy control methods are usually used to control drilling pressure, which have problems such as the need to adjust parameters in a timely manner and steady-state errors. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems in the related art to a certain extent. To this end, the first object of the present invention is to propose a multi-model predictive control method for a rescue drilling rig for drilling in complex formations, which can quickly respond to formation changes and adjust the drilling pressure to maintain the stability and efficiency of the drilling process, so that the drilling pressure can always be stable within the safe range of the set value in different formations.

[0005] To achieve the above-mentioned purpose, the first aspect of the present invention proposes a multi-model predictive control method for a rescue drilling rig for drilling in complex formations, the method comprising the following steps: based on the finite element method, a drilling pressure control system model of the rescue drilling rig with voltage as input and drilling pressure as output is established for each formation, the drilling pressure control system model comprising a proportional relief valve model, a hydraulic cylinder system model, a drill string axial model and a drill bit rock action model; based on the frequency domain analysis method, the drilling pressure control system model of each formation is subjected to rigid-flexible mode separation, and a reduced-order model of the drilling pressure control system model of each formation is established; the corresponding feed damping coefficient is determined under each formation, and multiple formations are matched one by one with multiple reduced-order models, wherein each formation is pre-configured with a controller; when the formation conditions change, the corresponding controller is switched to perform predictive control of the drilling pressure according to the formation conditions.

[0006] According to the multi-model predictive control method for rescue drilling rigs for drilling in complex formations according to the embodiment of the present invention, the characteristics of the drill string system are combined, and the drilling pressure control system model is established by using the finite element method. The rigid mode and the flexible mode of the drilling pressure control system model are first separated based on the frequency domain analysis method, and then the corresponding reduced-order model is approximately designed. A plurality of reduced-order models are established for different formations and predictive controllers are designed respectively. The corresponding model predictive control strategy is selected according to the formation conditions, so that the drilling pressure can be tracked when the formation changes. As a result, the method can quickly respond to formation changes and adjust the drilling pressure to maintain the stability and efficiency of the drilling process, so that the drilling pressure can always be stable within the safe range of the set value under different formations.

[0007] Compared with the prior art, the present invention has the following beneficial effects:

[0008] The present invention considers a rescue drilling rig that provides drilling pressure with a proportional relief valve-hydraulic cylinder system, and designs an adaptive control method for complex formations for the first time. The drilling pressure control system model is established by the finite element method. In order to reduce the complexity, the rigid mode and the flexible mode in the drilling pressure control system model are separated based on the frequency domain analysis method, and the two parts are approximated to obtain a reduced-order model; different reduced-order models are established for different formations, and predictive control methods for different reduced-order models are designed. The optimal model predictive control strategy for the formation is selected according to the difference between the estimated output and the actual output of each model, thereby completing the accurate tracking of the drilling pressure. The prior art usually uses PID control and fuzzy control methods, which have problems such as the need to adjust parameters in a timely manner and steady-state errors. The method mentioned in the present invention breaks through the difficult problem of adaptive control of drilling pressure in variable formations, which is of great significance for a safe and efficient drilling process.

[0009] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 A flowchart of a multi-model predictive control method for a rescue drilling rig for drilling in complex formations according to an embodiment of the present invention;

[0011] Figure 2 is a schematic diagram of a drilling pressure control system model according to an embodiment of the present invention;

[0012] Figure 3 is a structural block diagram of a reduced-order model according to an embodiment of the present invention;

[0013] Figure 4 The figure is a diagram showing the output tracking effect for different formations corresponding to different drilling pressure setting values ​​according to an embodiment of the present invention. DETAILED DESCRIPTION

[0014] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0015] The following describes a multi-model predictive control method for a rescue drilling rig for drilling in complex formations proposed in an embodiment of the present invention with reference to the accompanying drawings.

[0016] Figure 1 The present invention is a flowchart of a multi-model predictive control method for a rescue drilling rig for drilling in complex formations according to an embodiment of the present invention.

[0017] like Figure 1 As shown, the multi-model predictive control method for a rescue drilling rig for drilling in complex formations according to an embodiment of the present invention comprises the following steps:

[0018] S1. Based on the finite element method, a drilling pressure control system model of the rescue drilling rig with voltage as input and drilling pressure as output is established for each formation. The drilling pressure control system model includes a proportional relief valve model, a hydraulic cylinder system model, a drill string axial model and a drill bit rock action model.

[0019] Specifically, the rescue drilling rig provides drilling pressure with a proportional relief valve-hydraulic cylinder system, such as Figure 2 As shown in the figure, a drilling pressure control system model is established based on the process mechanism of hydraulic cylinder connecting drill string to apply drilling pressure. The drilling pressure control system model can be divided into four main parts: proportional relief valve model, hydraulic cylinder system model, drill string axial model and drill bit rock action model. The actual output pressure of the proportional relief valve is p r Affected by its command voltage v and the flow rate q through the relief valve r The oil pressure actually output by the proportional relief valve will be transmitted to the rodless chamber of the hydraulic cylinder, thereby controlling the output pressure of the hydraulic cylinder. The hydraulic cylinder is connected to the power head through a pulley to control the drilling pressure of the drill string system. The drill string system consists of multiple drill tools. According to the finite element method, each drill rod can be regarded as a discrete unit, and their connection points can be regarded as generalized nodes. Assume that the drill string system consists of N drill rods, each drill rod can be numbered 1 to N from top to bottom, and there are N+1 generalized nodes in total. The top of the drill string is rigidly connected to the power head, and the speeds of the two are equal.

[0020] It should be noted that the proportional relief valve model is responsible for adjusting the pressure in the hydraulic system to control the drilling pressure of the drilling rig; the hydraulic cylinder system model simulates the behavior of the hydraulic cylinder, converting hydraulic energy into mechanical energy to generate drilling pressure; the drill string axial model describes the mechanical behavior of the drill string in the axial direction, including its force and deformation; the drill bit rock action model simulates the mechanical process of interaction between the drill bit and the rock, which affects the drilling pressure and drilling efficiency.

[0021] S2, based on the frequency domain analysis method, the drilling pressure control system model of each formation is separated into rigid and flexible modes, and a reduced-order model of the drilling pressure control system model of each formation is established.

[0022] S3, determining a corresponding feed damping coefficient under each stratum, and making a one-to-one correspondence between the multiple strata and the multiple reduced-order models, wherein each stratum is pre-configured with a controller.

[0023] S4, when the formation conditions change, according to the formation conditions, the corresponding controller is switched to perform predictive control on the drilling pressure.

[0024] Specifically, during the drilling process, as the formation changes, the feed damping coefficient will change, causing the model of the controlled object to change, so the reduced-order model with fixed parameters has great limitations. The corresponding feed damping coefficient is determined for each formation, and a reduced-order model with good matching is established, and a controller suitable for the formation is pre-designed. When the system operating conditions change from one formation to another, it is difficult for the previous controller to maintain the original control quality. According to the formation conditions, the controller with the best matching degree with the formation is selected to obtain better control quality.

[0025] Specifically, firstly, the finite element method is used to establish a drilling pressure control system model for each formation. This model takes voltage as input and drilling pressure as output. Then, the frequency domain analysis method is used to separate the rigid and flexible modes of the drilling pressure control system model of each formation to establish a reduced-order model. This can simplify the model and reduce the computational complexity while retaining the key dynamic characteristics of the model for real-time control.

[0026] Furthermore, a corresponding feed damping coefficient is determined under each stratum, and the feed damping coefficient can be determined by experimental determination or empirical estimation of the physical properties of the stratum. Then, multiple strata are matched one by one with multiple reduced-order models, and a controller is pre-configured for each stratum. When the stratum conditions change, the system will switch to the corresponding controller for predictive control according to the stratum conditions monitored in real time, thereby quickly responding to stratum changes and adjusting drilling pressure to maintain the stability and efficiency of the drilling process.

[0027] According to one embodiment of the present invention, a drilling pressure control system model of a rescue drilling rig with voltage as input and drilling pressure as output is established for each stratum based on the finite element method, including: determining the control input, output and state variables of the drilling pressure control system; and establishing a state space model of the drilling pressure control system according to the input, output and state variables of the drilling pressure control system.

[0028] Further, according to one embodiment of the present invention, the control input of the bit pressure control system is expressed by the following expression:

[0029]

[0030] Among them, u is the control input of the drilling pressure control system, v is the command voltage of the proportional relief valve, and q r is the flow through the proportional relief valve;

[0031] The output of the drilling pressure control system is the drilling pressure at the top of the drill string, which is expressed by the following expression:

[0032] y s =F s

[0033] Among them, y s is the output of the drilling pressure control system, F s The drilling pressure at the top of the drill string;

[0034] The state variables of the drilling pressure control system are expressed by the following expression:

[0035]

[0036] Among them, x s is the state variable, R n represents n-dimensional Euclidean space, x n Expressed as the displacement of the nth generalized node, Expressed as the velocity of the nth generalized node;

[0037] The state space model of the drilling pressure control system is established according to the following formula:

[0038]

[0039] in, is the first-order derivative of the state variable, indicating the change of the system state over time; u(t) is the control input of the system, A s is the system matrix, B s is the input matrix, y s (t) is the output of the system, C s is the output matrix;

[0040] Determine the parameter A in the state space model of the drilling pressure control system according to the following formulas , B s , C s :

[0041] A s =A sr +Hk r T

[0042] C s =C1-n1mQA s -n1bQ

[0043]

[0044]

[0045] Among them, k r represents the feed damping coefficient, which indicates the damping of the drill bit at a unit drilling speed and is an uncertain parameter related to the formation strength; the constant n1 is the coefficient of the feed mechanism, which indicates the relationship between the drilling pressure on the well and the output pressure of the hydraulic cylinder and is determined by the pulley structure; b is the viscous damping coefficient, which is obtained from the hydraulic cylinder motion test; m is the total mass of the drill string, O i×j is an i×j dimensional matrix whose elements are all 0;

[0046] The above parameters A, B, C1, D a , E1, H, H1, K t 、M a , T, Q are expressed by the following formula:

[0047]

[0048]

[0049] C1=[n1A a O 1×(2N+4) ]

[0050] D a =αM+βK+n1bE0Q

[0051]

[0052]

[0053]

[0054] K t =KE3

[0055] M a =M+n1mE0Q

[0056] T=[0 0 ... 1]∈R 1×(2N+5)

[0057] Q=[O 1×(N+4) 1 O 1×N ]

[0058] Among them, A a is the effective area of ​​the rodless cavity, K is the global stiffness matrix, M is the global mass matrix, and constants α and β are the model coefficients of the global damping model obtained using the Rayleigh damping model;

[0059] The above parameters A1, A2, A3, B1, B2, B3, E0, E2, E3, W, K, and M are expressed by the following formulas:

[0060]

[0061]

[0062]

[0063]

[0064]

[0065]

[0066] E0=[1 0 ... 0] T ∈R N+1

[0067] E2=[0 0 ... 1] T ∈R N+1

[0068]

[0069]

[0070]

[0071]

[0072] Among them, K cr Represents the equivalent flow pressure coefficient of the proportional relief valve, ω rv Indicates the dominant turning frequency of the main valve motion, ζ ry Indicates the damping ratio of the pilot valve, ω ry Indicates the natural frequency of the pilot valve, K qr represents flow pressure gain, ω rm Indicates the main valve equivalent natural frequency, ζ rm Represents the equivalent damping ratio of the main valve, P∈R N×N is a matrix whose main diagonal and elements above the main diagonal are all 1;

[0073] The global stiffness matrix K and the global mass matrix M are composed of the element mass matrix M of each discrete element i and the element stiffness matrix K i Combined, M i and K i They are:

[0074]

[0075]

[0076] i=1,2,…,N

[0077] Where ρ is the density of each drill rod, S is the cross-sectional area of ​​each drill rod, E is the Young's modulus of each drill rod, and l is the length of each drill rod.

[0078] According to one embodiment of the present invention, the drilling pressure control system model of each formation is separated into rigid and flexible modes based on the frequency domain analysis method, and a reduced-order model of the drilling pressure control system model of each formation is established, including: separating the drilling pressure control system model to obtain low-order rigid modes and high-order flexible modes; using a first-order inertia link to describe the rigid modal transfer function; using a fixed multiplicative uncertainty weighting function to approximately describe the high-order flexible mode, and using a trial and error method to optimize the amplitude of the uncertainty weighting function.

[0079] Further, according to one embodiment of the present invention, the state space equation of the rigid mode transfer function is expressed according to the following formula:

[0080]

[0081] Among them, x l is the system status, y l Output drilling pressure value for the system, B l is the input matrix, and the state transfer matrix ε is equal to the real part of the dominant pole;

[0082] The uncertainty weighting function is expressed according to the following formula:

[0083]

[0084] Among them, ω1, ω2, ζ1, ζ2, and K1 are constants.

[0085] Specifically, the transfer function matrix corresponding to the above-mentioned drilling pressure control system model is defined as G h (s). The first-order inertial link is used to describe the low-order rigid mode, and its transfer function matrix is ​​G l (s), the corresponding state space equation is:

[0086]

[0087] For different strata, you can choose B l is a matrix whose elements are all constants. In order to facilitate the parameter selection of the flexible mode, the input matrix B l It is necessary to make the relative error amplitude response of the entire drilling pressure control system model and the rigid mode under different formations fluctuate within the range of 0 to 60 dB.

[0088] A fixed multiplicative uncertainty weighting function W(s) is used to approximate high-order flexible modes. In order to reduce the conservatism of the model, it is necessary to ensure that W(s) is close enough to the frequency band corresponding to the flexible mode, and it is designed as follows:

[0089]

[0090] In addition, the amplitude of W(s) should be larger than the amplitude of the relative error, and the amplitude of the relative error should be as close as possible to the frequency band where the high-order flexible mode is located. That is, W(s) is obtained by solving the following optimization problem through trial and error:

[0091]

[0092] The structure diagram of the reduced-order model is as follows: Figure 3 shown.

[0093] According to one embodiment of the present invention, when the formation conditions change, the corresponding controller is switched to perform predictive control of the drilling pressure according to the formation conditions, including: determining the model parameters of the drilling pressure control system model of each formation according to the transfer function of the reduced-order model of the drilling pressure control system model of each formation; determining the indicator switching function according to the model parameters of the drilling pressure control system model of each formation and the current error and historical error of the current formation output, and judging the matching degree of the drilling pressure control system model of each formation and the current formation through the indicator switching function; when the matching degree of the drilling pressure control system model and the current formation meets the preset conditions, determining the drilling pressure control system model corresponding to the current moment as the target model; and using the controller corresponding to the target model to perform predictive control of the drilling pressure.

[0094] Specifically, the reduced-order model transfer function is obtained by combining the rigid modal transfer function with the uncertainty weighting function under each formation, which is converted into a state space equation as shown below:

[0095]

[0096] In the formula, A i , B i , C i are the model parameters after reduction, and the model parameters are different in different formations i.

[0097] For the above model, the first-order Euler method is used to convert the continuous time model into a discrete time model:

[0098]

[0099] In the formula, T is the sampling time.

[0100] The model parameters of the drilling pressure control system model of each formation can be obtained through the above steps.

[0101] Further, according to an embodiment of the present invention, the indicator switching function is determined according to the following formula:

[0102]

[0103] e i (k) = y i (k)-y(k)

[0104] Among them, y i (k) is the output value of the drilling pressure control system model of the ith formation, y(k) is the actual output of the drilling pressure control system, e i (k) is the difference between the output value of the drilling pressure control system model and the actual system output value of the i-th formation; λ1 is the weight at the current moment, λ2 is the weight of the error at the historical moment, λ1>0,λ2>0; θ is the forgetting factor, which represents the memory effect of the historical error information, 0<θ<1; h is the length of the historical error.

[0105] At any time, when (δ represents the number of formations), determine the appropriate model parameters to design the predictive control strategy.

[0106] According to one embodiment of the present invention, a controller corresponding to a target model is used to predict and control the drilling pressure, including: obtaining model parameters of the target model, and setting a prediction time domain N of the drilling pressure control system. p , control time domain N c , where N c ≤N p ; and define the predicted output vector Y of the drilling pressure control system k and the predictive control vector U k ; Determine the predicted output vector according to the model parameters of the target model, the prediction time domain, the control time domain, the predicted control vector and the prediction equation; Determine the optimal control law according to the predicted output vector, the predicted control vector and the quadratic objective function; Use the convex optimization toolbox to obtain the future N in the control time domain cThe first result in the control sequence is used as the actual control input to act on the drilling pressure control system to control the drilling pressure control system, and then enters the next cycle and repeats the above process to complete the rolling optimization.

[0107] Furthermore, the model parameters of the target model are:

[0108] The predicted output vector is:

[0109] Y k =[y(k+1 / k) y(k+2 / k) … y(k+N c / k) … y(k+N p / k)] T

[0110] Wherein, u(k+η / k) represents the input value at time k+η determined at time k; y(k+η / k) represents the prediction of the output value at time k+η at time k;

[0111] The predictive control vector is:

[0112] U k = [u(k / k) u(k+1 / k) … u(k+N c -1 / k)] T

[0113] The prediction equation is: k =Φ1x k +Γ1U k

[0114] in,

[0115]

[0116] According to one embodiment of the present invention, the quadratic objective function is:

[0117]

[0118] e(k+η / k)=y(k+η / k)-y d

[0119] Among them, Q is the error weight coefficient, R is the input signal weight coefficient, S is the predicted terminal error weight coefficient, and y d is the desired WOB value;

[0120] The quadratic objective function is calculated by the simultaneous prediction equation:

[0121]

[0122] in,

[0123]

[0124]

[0125] Y d By N p y d The column vector composed of is the Kronecker product.

[0126] In order to simplify the control strategy, the input flow rate q is set to a constant value, and the range of the command voltage v is considered. min ~v max , construct the optimization problem of the model predictive control algorithm:

[0127]

[0128] The convex optimization toolbox is used to obtain the future N in the control time domain. c The first result in the control sequence is used as the actual control input to act on the system, and then enters the next cycle and repeats the above process to complete the rolling optimization.

[0129] The corresponding control algorithm is as follows:

[0130]

[0131]

[0132] A specific embodiment of the present invention is as follows:

[0133] Under three different formations, the following uncertain parameters in the feed damping coefficient and rigid mode are taken, from "soft", "medium" to "hard": ε1=-8.385×10 -2 , ε2=-4.741×10 -2 , ε3=-3.364×10 -2 .

[0134] The parameters used in the model can be taken as A1 = 0.0154m 2 , b = 1000 N / (m·s), ω rm =50rad / s,ζ rm =0.9,ω ry =500rad / s,ζ ry =0.8,ω rv =20rad / s, K qr =2.5Mpa / V,K cr=0.016Mpa / L / min, T=0.1s, n1=2, λ1=0.5, λ2=0.5, h=10, θ=0.75. The parameters used in the controller design are Q=1, S=1, B l =[1100 0.1 0.005 0.00002 0.00000002].

[0135] According to the frequency response characteristics of the model and the aforementioned design requirements, the relevant values ​​of the described weighting function W(s) are ω1=10.49, ω2=8.94, ζ1=625, ζ2=50, and K1=1.375.

[0136] In the present invention, the reference drilling pressure value in the "soft" formation is set to 20000N, the reference drilling pressure value in the "medium" formation is set to 25000N, and the reference drilling pressure value in the "hard" formation is set to 30000N.

[0137] like Figure 4 As shown, the bit pressure tracks drilling from the "soft" formation to the "hard" formation and finally to the "medium" formation.

[0138] From the simulation results, the multi-model predictive control method of the rescue drilling rig for drilling in complex formations can ensure that the drilling pressure can always be stable within the safe range of the set value in different formations.

[0139] According to the multi-model predictive control method for rescue drilling rigs for drilling in complex formations according to the embodiment of the present invention, the characteristics of the drill string system are combined, and the drilling pressure control system model is established by using the finite element method. The rigid mode and the flexible mode of the drilling pressure control system model are first separated based on the frequency domain analysis method, and then the corresponding reduced-order model is approximately designed. A plurality of reduced-order models are established for different formations and predictive controllers are designed respectively. The corresponding model predictive control strategy is selected according to the formation conditions, so that the drilling pressure can be tracked when the formation changes. As a result, the method can quickly respond to formation changes and adjust the drilling pressure to maintain the stability and efficiency of the drilling process, so that the drilling pressure can always be stable within the safe range of the set value under different formations.

[0140] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0141] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0142] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0143] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0144] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements, unless otherwise clearly defined. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0145] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A multi-model predictive control method for a rescue drilling rig for drilling in complex formations, characterized in that: The method comprises the following steps: Based on the finite element method, a drilling pressure control system model of the rescue drilling rig with voltage as input and drilling pressure as output is established for each stratum, wherein the drilling pressure control system model includes a proportional relief valve model, a hydraulic cylinder system model, a drill string axial model and a drill bit rock action model; Based on the frequency domain analysis method, the drilling pressure control system model of each formation is separated into rigid and flexible modes, and a reduced-order model of the drilling pressure control system model of each formation is established; Determine a corresponding feed damping coefficient under each stratum, and correspond the multiple strata to the multiple reduced-order models one by one, wherein each stratum is pre-configured with a controller; When the formation conditions change, the corresponding controller is switched to perform predictive control on the drilling pressure according to the formation conditions.

2. The multi-model predictive control method for rescue drilling rigs for drilling in complex formations according to claim 1 is characterized in that: Based on the finite element method, a drilling pressure control system model of the rescue drilling rig with voltage as input and drilling pressure as output is established for each stratum, including: Determining control inputs, outputs and state variables of the weight-on-bit control system; A state space model of the drilling pressure control system is established according to the input, output and state variables of the drilling pressure control system.

3. The multi-model predictive control method for rescue drilling rigs for drilling in complex formations according to claim 2 is characterized in that: The control input of the drilling pressure control system is expressed by the following expression: Wherein, u is the control input of the drilling pressure control system, v is the command voltage of the proportional relief valve, and q r is the flow rate through the proportional relief valve; The output of the drilling pressure control system is the drilling pressure at the top of the drill string, which is expressed by the following expression: y s =F s Among them, y s is the output of the drilling pressure control system, F s The drilling pressure at the top of the drill string; The state variables of the drilling pressure control system are expressed by the following expression: Among them, x s is the state variable, R n represents n-dimensional Euclidean space, x n Expressed as the displacement of the nth generalized node, Expressed as the velocity of the nth generalized node; The state space model of the drilling pressure control system is established according to the following formula: in, is the first-order derivative of the state variable, indicating the change of the system state over time; u(t) is the control input of the system, A s is the system matrix, B s is the input matrix, y s (t) is the output of the system, C s is the output matrix; The parameter A in the state space model of the drilling pressure control system is determined according to the following formula s , B s , C s : A s =A sr +Hk r T C s =C1-n1mQA s -n1bQ Among them, k r represents the feed damping coefficient, which indicates the damping of the drill bit at a unit drilling speed and is an uncertain parameter related to the formation strength; the constant n1 is the coefficient of the feed mechanism, which indicates the relationship between the drilling pressure on the well and the output pressure of the hydraulic cylinder and is determined by the pulley structure; b is the viscous damping coefficient, which is obtained from the hydraulic cylinder motion test; m is the total mass of the drill string, O i×j is an i×j dimensional matrix whose elements are all 0; The above parameters A, B, C1, D a , E1, H, H1, K t 、M a , T, Q are expressed by the following formula: C1=[n1A a O 1×(2N+4) ] D a =αM+βK+n1bE0Q K t =KE3 M a =M+n1mE0Q T=[00...1]∈R 1×(2N+5) Q=[O 1×(N+4) 1 O 1×N ] Among them, A a is the effective area of ​​the rodless cavity, K is the global stiffness matrix, M is the global mass matrix, and constants α and β are the model coefficients of the global damping model obtained using the Rayleigh damping model; The above parameters A1, A2, A3, B1, B2, B3, E0, E2, E3, W, K, and M are expressed by the following formulas: E0=[10...0] T ∈R N+1 <h2 style=";text-align:left;direction:ltr">E2=[00...1]<h2 style=";text-align:left;direction:ltr"> T <h2 style=";text-align:left;direction:ltr"> ∈R<h2 style=";text-align:left;direction:ltr"> N+1 Among them, K cr Represents the equivalent flow pressure coefficient of the proportional relief valve, ω rv Indicates the dominant turning frequency of the main valve movement, ζ ry Indicates the damping ratio of the pilot valve, ω ry Indicates the natural frequency of the pilot valve, K qr represents flow pressure gain, ω rm Indicates the main valve equivalent natural frequency, ζ rm Represents the equivalent damping ratio of the main valve, P∈R N×N is a matrix whose main diagonal and elements above the main diagonal are all 1; The global stiffness matrix K and the global mass matrix M are composed of the element mass matrix M of each discrete element i and the element stiffness matrix K i Combined, M i and K i They are: i=1,2,…,N Where ρ is the density of each drill rod, S is the cross-sectional area of ​​each drill rod, E is the Young's modulus of each drill rod, and l is the length of each drill rod.

4. The multi-model predictive control method for rescue drilling rigs for drilling in complex formations according to claim 3 is characterized in that: Based on the frequency domain analysis method, the drilling pressure control system model of each formation is separated into rigid and flexible modes, and a reduced-order model of the drilling pressure control system model of each formation is established, including: Separating the weight-on-bit control system model to obtain a low-order rigid mode and a high-order flexible mode; The first-order inertial link is used to describe the rigid modal transfer function; A fixed multiplicative uncertainty weighting function is used to approximately describe the high-order flexible modes, and the amplitude of the uncertainty weighting function is optimized by trial and error.

5. The multi-model predictive control method for rescue drilling rigs for drilling in complex formations according to claim 4 is characterized in that: The state space equation for the rigid modal transfer function is expressed as follows: Among them, x l is the system status, y l Output drilling pressure value for the system, B l is the input matrix, and the state transfer matrix ε is equal to the real part of the dominant pole; The uncertainty weighting function is expressed according to the following formula: Among them, ω1, ω2, ζ1, ζ2, and K1 are constants.

6. The multi-model predictive control method for rescue drilling rigs for drilling in complex formations according to claim 4 is characterized in that: When the formation conditions change, the corresponding controller is switched to perform predictive control on the drilling pressure according to the formation conditions, including: Determining model parameters of the drilling pressure control system model of each formation according to the transfer function of the reduced-order model of the drilling pressure control system model of each formation; Determine an index switching function according to the model parameters of the drilling pressure control system model of each formation and the current error and historical error output by the current formation, and judge the matching degree between the drilling pressure control system model of each formation and the current formation by the index switching function; When the matching degree between the drilling pressure control system model and the current formation meets the preset conditions, the drilling pressure control system model corresponding to the current moment is determined as the target model; The controller corresponding to the target model is used to predict and control the bit weight.

7. The multi-model predictive control method for rescue drilling rigs for drilling in complex formations according to claim 6 is characterized in that: The indicator switching function is determined according to the following formula: and i (k)=y i (k)-y(k) Among them, y i (k) is the output value of the drilling pressure control system model of the i-th formation, y(k) is the real output of the drilling pressure control system, e i (k) is the difference between the output value of the drilling pressure control system model and the actual system output value of the i-th formation; λ1 is the weight at the current moment, λ2 is the weight of the error at the historical moment, λ1>0,λ2>0; θ is the forgetting factor, which represents the memory effect of the historical error information, 0<θ<1; h is the length of the historical error taken.

8. The multi-model predictive control method for rescue drilling rigs for drilling in complex formations according to claim 7 is characterized in that: The controller corresponding to the target model is used to predict and control the drilling pressure, including: Obtain the model parameters of the target model and set the prediction time domain N of the drilling pressure control system p , control time domain N c , where N c ≤N p ; and define the predicted output vector Y of the drilling pressure control system k and the predictive control vector U k ; Determine the predicted output vector according to the model parameters of the target model, the predicted time domain, the control time domain, the predicted control vector and the prediction equation; An optimal control law according to the predicted output vector, the predicted control vector and a quadratic objective function; The convex optimization toolbox is used to obtain the future N in the control time domain. c The first result in the control sequence is used as the actual control input to act on the drilling pressure control system to control the drilling pressure control system, and then enters the next cycle, repeats the above process, and completes the rolling optimization.

9. The multi-model predictive control method for rescue drilling rigs for drilling in complex formations according to claim 8, characterized in that: The model parameters of the target model are: The predicted output vector is: AND k =[y(k+1 / k) y(k+2 / k) … y(k+N c / k) … and (k+N p / k)] T Wherein, u(k+η / k) represents the input value at time k+η determined at time k; y(k+η / k) represents the prediction of the output value at time k+η at time k; The predictive control vector is: YOU k =[u(k / k)u(k+1 / k)…u(k+N c -1 / k)] T The prediction equation is: k =Φ1x k +Γ1U k in, 10. The multi-model predictive control method for rescue drilling rigs for drilling in complex formations according to claim 9, characterized in that: The quadratic objective function is: e(k+η / k)=y(k+η / k)-y d Among them, Q is the error weight coefficient, R is the input signal weight coefficient, S is the predicted terminal error weight coefficient, and y d is the desired WOB value; The quadratic objective function is calculated by combining the prediction equation: in, Y d By N p y d The column vector composed of is the Kronecker product.

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