Drilling pressure control method and apparatus

Abstract

This invention discloses a drilling pressure control method and apparatus, relating to the field of pressure-controlled drilling technology. The method includes: acquiring drilling site information collected by different sensors; querying a first database based on the drilling site information to determine the drilling conditions corresponding to the drilling site information, wherein the first database stores drilling conditions corresponding to different drilling site information; querying a second database based on the drilling conditions to determine the pressure control strategy corresponding to the drilling conditions, wherein the second database stores pressure control strategies corresponding to different drilling conditions; processing the drilling site information according to the pressure control strategy corresponding to the drilling conditions to obtain a set value for the throttle valve opening; determining a pressure control command based on the set value for the throttle valve opening, and sending the pressure control command to an actuator so that the actuator can perform corresponding operations according to the pressure control command. This can form a multi-condition, multi-strategy pressure control method, reducing drilling costs and improving drilling efficiency.

Description

Technical Field

[0001] This invention relates to the field of controlled-pressure drilling technology, and in particular to a drilling pressure control method and apparatus. Background Technology

[0002] This section is intended to provide background or context for the embodiments of the invention set forth in the claims. The description herein is not an admission that it is prior art simply because it is included in this section.

[0003] As oil and gas resources become increasingly depleted, exploration and development activities in complex formations, deep wells, and ultra-deep wells are gradually increasing. However, drilling in these complex formations often encounters complex problems such as well kicks and lost circulation. Drilling in complex formations significantly increases non-productive time and drilling costs.

[0004] Most pressure control problems are solved using conventional PID control algorithms, which are insufficient to meet the precision requirements of fine-tuned pressure control drilling. Furthermore, this single control strategy cannot simultaneously satisfy control objectives under multiple operating conditions. Managed Pressure Drilling (MPD) technology can address drilling problems in complex formations to some extent. While research into advanced and intelligent control applications in MPD technology has matured, and pressure control strategies for different operating conditions have become increasingly sophisticated, it remains difficult to simultaneously meet control objectives under multiple conditions using a single control strategy. Summary of the Invention

[0005] This invention provides a drilling pressure control method to form a multi-condition, multi-strategy pressure control method, thereby reducing drilling costs and improving drilling efficiency. The method includes:

[0006] Acquire drilling site information collected by different sensors, including drilling site information such as pressure information before and after the choke valve, choke valve opening information, drilling fluid density information, mud pump outlet flow rate information, wellhead back pressure information, and riser pressure information;

[0007] The drilling conditions corresponding to the drilling site information are determined by querying the first database based on the drilling site information. The first database stores drilling conditions corresponding to different drilling site information, including valve position tracking condition, normal drilling condition and gas intrusion condition.

[0008] The second database is queried based on the drilling conditions to determine the pressure control strategy corresponding to the drilling conditions. The second database stores pressure control strategies corresponding to different drilling conditions, including expert control strategies, back pressure fuzzy control strategies, and riser pressure prediction control strategies.

[0009] Based on the pressure control strategy corresponding to the drilling conditions, the drilling site information is processed to obtain the set value of the throttle valve opening.

[0010] The pressure control command is determined based on the set value of the throttle valve opening and sent to the actuator so that the actuator can perform the corresponding operation according to the pressure control command.

[0011] This invention also provides a drilling pressure control device for forming a multi-condition, multi-strategy pressure control method to reduce drilling costs and improve drilling efficiency. The device includes:

[0012] The drilling site information acquisition module is used to acquire drilling site information collected by different sensors. The drilling site information includes pressure information before and after the choke valve, choke valve opening information, drilling fluid density information, mud pump outlet flow rate information, wellhead back pressure information, and riser pressure information.

[0013] The drilling condition determination module is used to query the first database based on the drilling site information to determine the drilling condition corresponding to the drilling site information. The first database stores the drilling conditions corresponding to different drilling site information, including valve position tracking condition, normal drilling condition and gas intrusion condition.

[0014] The pressure control strategy determination module is used to query the second database based on the drilling conditions to determine the pressure control strategy corresponding to the drilling conditions. The second database stores pressure control strategies corresponding to different drilling conditions, including expert control strategies, back pressure fuzzy control strategies, and riser pressure prediction control strategies.

[0015] The drilling site information processing module is used to process drilling site information according to the pressure control strategy corresponding to the drilling conditions, and obtain the set value of the throttle valve opening.

[0016] The pressure control command determination and transmission module is used to determine the pressure control command based on the set value of the throttle valve opening, and send the pressure control command to the actuator so that the actuator can perform the corresponding operation according to the pressure control command.

[0017] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described drilling pressure control method.

[0018] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described drilling pressure control method.

[0019] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described drilling pressure control method.

[0020] In this embodiment of the invention, drilling site information collected by different sensors is acquired; a first database is queried based on the drilling site information to determine the drilling conditions corresponding to the drilling site information. The first database stores drilling conditions corresponding to different drilling site information, including valve position tracking conditions, normal drilling conditions, and gas intrusion conditions; a second database is queried based on the drilling conditions to determine the pressure control strategy corresponding to the drilling conditions. The second database stores pressure control strategies corresponding to different drilling conditions, including expert control strategies, back pressure fuzzy control strategies, and riser pressure prediction control strategies; the drilling site information is processed according to the pressure control strategy corresponding to the drilling conditions to obtain the set value of the throttle valve opening; a pressure control command is determined based on the set value of the throttle valve opening and sent to the actuator so that the actuator can perform the corresponding operation according to the pressure control command. This can form a multi-condition, multi-strategy pressure control method, reducing drilling costs and improving drilling efficiency. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0022] Figure 1 This is a flowchart illustrating the drilling pressure control method in an embodiment of the present invention.

[0023] Figure 2 This is the aperture-Cv value fitting curve in an embodiment of the present invention;

[0024] Figure 3 This is the opening degree-throttling pressure fitting curve in an embodiment of the present invention;

[0025] Figure 4 These are the opening-pressure curves under different flow rates in embodiments of the present invention;

[0026] Figure 5 This is a block diagram of the expert control system in an embodiment of the present invention;

[0027] Figure 6a This is a diagram illustrating the effect of increasing the back pressure from 0 MPa to 3.6 MPa in an embodiment of the present invention.

[0028] Figure 6bThis is a diagram illustrating the effect of increasing the back pressure from 0 MPa to 1.2 MPa in an embodiment of the present invention.

[0029] Figure 6c This is a diagram illustrating the effect of reducing back pressure from 1.2 MPa to 0 MPa in an embodiment of the present invention.

[0030] Figure 7a This is a diagram illustrating the effect of reducing the displacement from 13L / s to 8L / s in an embodiment of the present invention, with a set value of 1.0MPa for variable flow rate.

[0031] Figure 7b This is a diagram illustrating the effect of increasing the displacement from 8L / s to 13L / s in an embodiment of the present invention, with a set value of 0.8MPa.

[0032] Figure 7c This is a diagram illustrating the effect of increasing the displacement from 8L / s to 13L / s in an embodiment of the present invention, with a set value of 3MPa.

[0033] Figure 8 This is a basic schematic diagram of fuzzy PID control in an embodiment of the present invention;

[0034] Figure 9 These are the membership function curves e and ec in the embodiments of the present invention;

[0035] Figure 10 The membership function curve ΔK in this embodiment of the invention. p ΔK i and ΔK d ;

[0036] Figure 11 This is a flowchart of the fuzzy PID control in an embodiment of the present invention;

[0037] Figure 12 This refers to the step signal response of the fuzzy PID controller in this embodiment of the invention.

[0038] Figure 13 The response curves of the fuzzy PID controller overcoming 15%, 30%, and 20% flow disturbances in this embodiment of the invention are shown.

[0039] Figure 14 The sinusoidal response curve of the fuzzy PID controller in this embodiment of the invention;

[0040] Figure 15 This is the structure of the Dynamic Matrix Control (DMC) algorithm in this embodiment of the invention;

[0041] Figure 16 This is a flowchart of the Dynamic Matrix Control (DMC) algorithm in an embodiment of the present invention;

[0042] Figure 17 This is the riser pressure step response curve in an embodiment of the present invention;

[0043] Figure 18a This is a diagram illustrating the control effect of tracking riser pressure setpoint in an embodiment of the present invention.

[0044] Figure 18b This is a graph showing the change in the control value of the riser pressure setpoint in an embodiment of the present invention;

[0045] Figure 19a This is a diagram illustrating the anti-disturbance control effect in an embodiment of the present invention;

[0046] Figure 19b This is a graph showing the variation of anti-disturbance control quantities in an embodiment of the present invention;

[0047] Figure 20a This is a diagram showing the control effect of the tracking setpoint when the model mismatch Ks = 5 in an embodiment of the present invention.

[0048] Figure 20b This is a diagram showing the control effect of the tracking setpoint when the model mismatch Ks = 0.2 in an embodiment of the present invention;

[0049] Figure 21a This is a diagram showing the control effect of the tracking setpoint when the model mismatch Tp = 10 in an embodiment of the present invention.

[0050] Figure 21b This is a diagram showing the control effect of the tracking setpoint when the model mismatch Tp = 50 in an embodiment of the present invention.

[0051] Figure 22a This is a diagram showing the control effect of the tracking setpoint when the model mismatch τ = 2 in an embodiment of the present invention.

[0052] Figure 22b This is a diagram showing the control effect of the tracking setpoint when the model mismatch τ = 15 in an embodiment of the present invention.

[0053] Figure 23 This is a schematic diagram of the drilling pressure control device in an embodiment of the present invention. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0055] The inventors discovered that currently, the adjustment of choke valves, control of wellhead back pressure, and control of riser pressure in the field largely rely on experience and manual operation. Although the application of advanced and intelligent control technologies in MPD (Mastering Dynamics) technology has matured, and research on pressure control strategies under different operating conditions has become increasingly sophisticated, it remains difficult to simultaneously meet the control objectives under multiple operating conditions using a single control strategy. Currently, the adjustment of choke valves, control of wellhead back pressure, and control of riser pressure in the field largely depend on experience and manual operation. However, for general operating conditions (referring to conditions with long cycles, high repeatability, and within the safety zone), intelligent control strategies can be employed to achieve rapid adjustment and precise control. Therefore, the inventors proposed a drilling pressure control method to solve the above problems.

[0056] First, the technical terms used in the embodiments of this invention will be explained:

[0057] Valve position tracking: refers to the throttle valve position changing in accordance with the change of the field back pressure measurement value.

[0058] Normal drilling: refers to the drilling process in the entire drilling process, and there are no abnormal situations (including but not limited to gas intrusion, overflow and leakage, etc.) in this process.

[0059] Gas intrusion: The process by which gas enters the drilling fluid and degrades its performance. Gas intrusion has a certain impact on the drilling fluid column pressure. Furthermore, the density of the drilling fluid in the annulus varies at different depths during gas intrusion. The density of the gas-intruded drilling fluid only becomes very small when it approaches the surface. Therefore, even if the drilling fluid in the annulus near the surface is severely affected by gas intrusion and its density decreases significantly, the reduction in the bottom hole drilling fluid column pressure is not substantial.

[0060] Expert control: Also known as expert-based control system, this term specifically refers to the definition used in the field of control science and engineering. Expert control is an important part of intelligent control. It combines the theories and techniques of expert systems in artificial intelligence with the theories and methods of automatic control, mimicking the intelligence of experts in unknown environments to achieve effective control of the system.

[0061] Backpressure fuzzy control: Backpressure fuzzy control should be divided into two parts. First, backpressure specifically refers to the definition used in the drilling field, namely, wellhead backpressure. Second, fuzzy control specifically refers to the definition used in the field of control science and engineering, namely, fuzzy control is a type of control implemented for objects that are difficult to model precisely, based on fuzzy reasoning and imitating human thinking methods.

[0062] Riser pressure predictive control: Riser pressure predictive control should be divided into two parts. First, riser pressure specifically refers to the definition used in the drilling field. Second, predictive control specifically refers to the definition used in the field of control science and engineering, namely, a control method based on parametric and nonparametric models, employing a local optimization strategy, continuously scrolling the optimization window, and constantly comparing and correcting the actual output with the model output to achieve tracking of reference values.

[0063] Figure 1 This is a flowchart illustrating the drilling pressure control method in an embodiment of the present invention. Figure 1 As shown, the drilling pressure control method in this embodiment of the invention may include:

[0064] Step 101: Obtain drilling site information collected by different sensors, including drilling site information such as pressure information before and after the choke valve, choke valve opening information, drilling fluid density information, mud pump outlet flow rate information, wellhead back pressure information, and riser pressure information.

[0065] Step 102: Query the first database based on the drilling site information to determine the drilling conditions corresponding to the drilling site information. The first database stores drilling conditions corresponding to different drilling site information, including valve position tracking conditions, normal drilling conditions, and gas intrusion conditions.

[0066] Step 103: Query the second database according to the drilling conditions to determine the pressure control strategy corresponding to the drilling conditions. The second database stores pressure control strategies corresponding to different drilling conditions, including expert control strategy, back pressure fuzzy control strategy and riser pressure prediction control strategy.

[0067] Step 104: Based on the pressure control strategy corresponding to the drilling conditions, process the drilling site information to obtain the set value of the throttle valve opening.

[0068] Step 105: Determine the pressure control command based on the set value of the throttle valve opening, and send the pressure control command to the actuator so that the actuator can perform the corresponding operation according to the pressure control command.

[0069] The specific implementation methods of the embodiments of the present invention are described below:

[0070] First, a correspondence between drilling site information and drilling conditions can be established in the first database, and a correspondence between drilling conditions and pressure control strategies can be established in the second database.

[0071] In practice, the correspondence between drilling site information and drilling conditions, as well as the correspondence between drilling conditions and pressure control strategies, can be pre-set based on construction experience, or engineers can make on-site judgments based on actual conditions.

[0072] During the drilling operation, drilling site information collected by different sensors can be obtained, including pressure information before and after the choke valve, choke valve opening information, drilling fluid density information, mud pump outlet flow rate information, wellhead back pressure information, and riser pressure information.

[0073] Then, the drilling conditions corresponding to the drilling site information can be determined by querying the first database. The first database stores the drilling conditions corresponding to different drilling site information, including valve position tracking, normal drilling, and gas intrusion conditions. The second database is then queried based on the drilling conditions to determine the pressure control strategy corresponding to the drilling conditions. The second database stores the pressure control strategies corresponding to different drilling conditions, including expert control strategies, back pressure fuzzy control strategies, and riser pressure prediction control strategies.

[0074] In one embodiment, the pressure control strategy corresponding to the drilling conditions is determined by querying a second database based on the drilling conditions, including:

[0075] When the drilling operation is valve position tracking operation, the second database is queried according to the valve position tracking operation to determine the pressure control strategy corresponding to the valve position tracking operation as the expert control strategy.

[0076] When the drilling condition is normal drilling condition, the second database is queried according to the normal drilling condition to determine the pressure control strategy corresponding to the normal drilling condition as the back pressure fuzzy control strategy.

[0077] When the drilling operation is under gas invasion conditions, the second database is queried based on the gas invasion conditions to determine the pressure control strategy corresponding to the gas invasion conditions as the riser pressure prediction control strategy.

[0078] The reasons and advantages for establishing the aforementioned correspondence between drilling conditions and pressure control strategies are explained below:

[0079] (1) Valve position tracking condition: This condition requires that the control accuracy (deviation between the measured wellhead back pressure and the set value) and the pressure tracking speed (the time from when the controller starts to act until the measured wellhead back pressure is basically stable) meet the requirements. Greater emphasis is placed on a simple and easy-to-implement control strategy. Compared to manual experience operation and traditional PID control strategies, expert control strategies offer both better control performance and ease of implementation.

[0080] (2) Normal drilling conditions: This condition requires higher precision in controlling the wellhead back pressure and faster pressure recovery speed. Manual operation based on experience, traditional PID control strategies, and expert control strategies are insufficient to simultaneously meet these requirements. The fuzzy control strategy is chosen because, theoretically, fuzzy logic provides a systematic reasoning method for experts to construct linguistic information and transform it into control strategies. Based on fuzzy sets, fuzzy linguistic variables, and fuzzy logic reasoning, and using prior knowledge and expert experience as control rules, its main characteristics are: ① The control system design is based on the operator's control experience and operational data, without requiring a precise mathematical model; ② It has strong robustness and can be used to solve problems that traditional control strategies cannot solve; ③ It uses linguistic variables instead of mathematical variables, making it easy to construct; ④ The reasoning process uses "imprecise reasoning," mimicking human thought processes, and can handle complex or even "ill-conditioned" systems; ⑤ Offline calculation yields the control lookup table, improving the real-time performance of the control system. In practice, this patent provides the control effect of the fuzzy control strategy in the invention effect section, which meets the requirements of this condition.

[0081] (3) Gas Invasion Condition: This condition is an abnormal condition and is a common occurrence in complex formations in deep wells (gas invasion: during controlled pressure drilling, when the bottom hole pressure is lower than the formation pressure, the controlled pressure drilling is in an underbalanced state, and formation fluids may invade the wellbore, resulting in a three-phase flow of solid, liquid, and gas within the wellbore annulus). The most effective and accurate way to handle this condition is to adjust the wellhead pressure or riser pressure using a choke valve. The latter (riser pressure) is a more ideal control variable because the density of the drilling fluid in the drill string is stable, and the properties of the fluid in the drill string will not change significantly even if fluid invades the mud at the bottom of the well. Gas takes a certain amount of time to migrate from the formation to the wellhead, which is referred to as lag in the control field. Predictive control has unique advantages in dealing with objects with pure lag, namely, it can naturally take the pure lag into account without adding additional control structures, and its control effect is equivalent to adding an output delay to the control without lag. In short, predictive control strategies have the advantages of simple control structure and simple algorithm implementation compared to other control strategies for gas intrusion conditions, and the control effect can meet the requirements of gas intrusion conditions.

[0082] After determining the pressure control strategy corresponding to the drilling conditions, the drilling site information can be input into the programmable controller (PLC). The PLC then processes the drilling site information according to the pressure control strategy corresponding to the drilling conditions to obtain the set value of the throttle valve opening.

[0083] In one embodiment, processing drilling site information according to a pressure control strategy corresponding to the drilling conditions to obtain a set value for the throttle valve opening may include:

[0084] When the pressure control strategy is an expert control strategy, the throttle valve opening measurement value, mud pump outlet flow value, and drilling fluid density value are determined based on drilling site information.

[0085] The measured values ​​of the throttle valve opening, the mud pump outlet flow rate, and the drilling fluid density are input into the expert PID controller. The influence factors in the expert PID controller are assigned segmented values, and the set value of the throttle valve opening is output. The expert PID controller is designed based on the influence factors and control factors. The influence factors represent the factors that directly or indirectly affect the wellhead pressure, and the control factors represent the control capability of the throttle valve at different opening degrees.

[0086] In practice, when using expert control strategies to solve the problem of controlling wellhead pressure in actual equipment, the influencing factors can be analyzed first, including throttle valve opening Z, outlet flow rate Q, and drilling fluid density D. By analyzing these influencing factors, appropriate state description variables can be selected to form control rules.

[0087] The following section uses a pressure-controlled drilling system as an example to explain the execution steps of the expert control strategy under valve position tracking conditions:

[0088] Based on the characteristic equation of fluid flow in a pipe, the flow rate Q through the throttle valve can be obtained. v The pressure difference ΔP between it and the pressure before and after it v The relationship is:

[0089]

[0090] Where Cv is the throttling coefficient; ΔP v ρ is the pressure difference across the throttle valve; Q is the fluid density; v This represents the flow rate of the throttle valve.

[0091] After specifying the units for each variable, the coefficient Cv depends on the flow cross-sectional area, and is therefore related to the valve type, diameter, and opening degree. According to the principles of fluid mechanics, the relationship between the flow channel area and pressure at a certain displacement can be obtained. However, this relationship deviates significantly from actual pressure changes. In practical applications, it is necessary to conduct experimental tests on the opening degree - Cv value of the throttle valve.

[0092] In a laboratory setting, using clean water for testing, Q v The flow rate is 11 L / s, and the density is 1 g / cm³. 3 Through experimental testing, the relationship between the throttling pressure and the opening degree of the throttling valve was obtained. After processing and calculation, Figure 2 and Figure 3 These are the fitting curves for opening degree-Cv value and opening degree-throttling pressure, respectively.

[0093] In this example, the throttle valve opening is -C. vThe value function relationship is

[0094] Cv = 50.19e m +6.759e b +9.093e c +8.367e d (2)

[0095] Where m, b, c, and d are intermediate temporary parameters, expanded as follows.

[0096]

[0097] At this point, the Gaussian quadrinomial correlation coefficient reached 0.9996, and the sum of squared residuals was 0.0001368, indicating that the fitted curve closely approximates the actual curve, achieving the required fitting accuracy.

[0098] In this example, the opening degree-throttling pressure function relationship is as follows:

[0099] P = 8.971e m +0.2334e b (3) In the formula, P is the throttling pressure, and m and b are intermediate temporary parameters. The specific calculation formula is as follows: The correlation coefficient was 0.9889 and the sum of squared residuals was 0.02, indicating that the fitting result was relatively accurate.

[0100] The flow characteristic fitting curve of the throttle valve shows that when the opening is 50%, the throttling pressure is 0.2 MPa, and when the opening is 79%, the throttling pressure is 0.05 MPa. This indicates that an opening above 50% is close to the dead zone of the throttle valve, which will lead to control failure. When the throttle valve opening changes from 24% to 23%, the throttling pressure changes by 1.08 MPa. This excessively rapid pressure change leads to overly aggressive control, easy overshoot, and difficulty in maintaining accuracy. Therefore, it is essential to operate the throttle valve within a good linear range to ensure both rapid and accurate pressure regulation.

[0101] The Z-Cv curve obtained from the experiment shows that the control capability of the throttle valve on the upstream pressure varies with different opening degrees. This control capability can be represented by the throttle valve flow coefficient, i.e., the Cv value. At the same outlet flow rate, the Cv value is small at a small opening degree, resulting in a large change in upstream pressure and strong control capability when the opening degree is changed by the same amount. Conversely, the Cv value is large at a large opening degree, resulting in a small change in upstream pressure and weak control capability when the opening degree is changed by the same amount. This difference in control capability at different opening degrees significantly impacts the formulation of control strategies. Therefore, the following approach to wellhead pressure control is proposed: using the opening degree as a primary criterion, applying different control actions within different opening degree ranges, while other influencing factors indirectly affect the wellhead pressure through the judgment of the opening degree range.

[0102] The impact of outlet flow rate Q on control is intuitively manifested as follows: at low flow rates, changing the same opening degree results in small pressure changes and weak control capability; at high flow rates, changing the same opening degree results in large pressure changes and strong control capability. In a laboratory environment, outlet flow rates of 8 L / s, 11 L / s, and 13 L / s were used to plot the curves of valve opening Z versus wellhead pressure at different flow rates, as shown in [reference needed]. Figure 4 .from Figure 4 As can be seen, the curve shifts to the right as the flow rate increases, so the flow rate Q can be segmented in the rules.

[0103] Before discussing the impact of drilling fluid density on control, let's try to analyze it:

[0104] As shown in formula (1), the larger the drilling fluid density D is at the same outlet flow rate Q, the greater the pressure change when the throttle valve opening is changed by the same amount, and the greater the impact of the throttle valve opening on the back pressure. Conversely, the smaller the drilling fluid density D is, the smaller the impact of the throttle valve opening on the back pressure. However, the impact of drilling fluid density D on pressure is not as great as that on outlet flow rate Q. Therefore, drilling fluid density D can be segmented like outlet flow rate Q.

[0105] If the error e is too large, that is, when the pressure difference is very large, it will cause the change to be too drastic. Therefore, the error e needs to be limited in the control rules.

[0106] Figure 5 This is a block diagram of an expert control system. Where, D... Factor Q is an influencing factor of drilling fluid density D. Factor Y is the influencing factor of export flow Q. Out Z is the output of the controller, i.e., the throttle valve opening setpoint; C is the current opening feedback value. Factor The control factor is e = SP - PV, where SP is the setpoint (here referring to the wellhead pressure setpoint) and PV is the measured value (here referring to the wellhead pressure measured value). Based on the above analysis of influencing factors, and combined with the experience of field engineers, control rules are formulated, and an expert PID controller is designed accordingly.

[0107] (1) Limit the error e:

[0108]

[0109] (2) Determining Q_Factor: Based on field debugging experience, the general range of Q is 5-30 L / s. Q is divided into segments that vary in 5 L / s increments:

[0110]

[0111] (3) Determining D_Factor: Based on on-site debugging experience, the general range of D is 0.7-2.6 g / cm³.3 In this example, based on the experience gained from on-site commissioning at the test well, the range of D was selected as 0.7-1.5 g / cm³. 3 and D at 0.2g / em 3 Change segmentation:

[0112]

[0113] (4) Z_Sum is the direct judgment condition for the control factor C_Factor. The final opening interval Z_Sum = Z + D - Factor + Q_Factor. Based on on-site commissioning experience and the Z-Cv curve, the opening is divided into 6 segments:

[0114]

[0115] (5) Since the control of the throttle valve is indirectly achieved through the proportional valve, although the opening changes quickly, there is still a certain lag. That is, there is a certain error between the throttle valve opening set value and the current opening value. Therefore, the current opening value Z is used to participate in the control action instead of Y_Out iteration. In this way, the opening changes on the basis of the current opening each time, making the control more stable and less prone to overshoot.

[0116] A_Factor is an additional influencing factor that compensates for the interference of other unconsidered factors on the control. P_Accuracy is the control accuracy, which is the throttle valve opening setpoint, i.e., the controller output is:

[0117]

[0118] To further illustrate the feasibility of the method described in this invention, the results of a field experiment at a certain well are used for explanation.

[0119] The on-site outlet flow rate remained stable at 13 L / s, and the drilling fluid density was 1.2 g / cm³. 3 At that time, the control effect was seen in Figure 6a , Figure 6b , Figure 6c ,as well as Figure 7a , Figure 7b , Figure 7c .

[0120] Figure 6a The voltage can be increased from 0 to 3.6 MPa with a settling time of 25 seconds and an overshoot of 0.1 MPa.

[0121] Figure 6b The voltage is increased from 0 to 1.2 MPa, the settling time is 20 seconds, and the steady-state error is 0.1 MPa.

[0122] Figure 6c To reduce the pressure from 1.2 to 0 MPa, the adjustment time is 16 seconds, and the steady-state error is 0.2 MPa.

[0123] As can be seen from the figure, the pressure rise time below 4MPa is approximately 15 to 25 seconds, which is longer than the pressure drop time. The stability error is 0 to 0.2MPa, which meets the accuracy requirement of 0.2MPa and the adjustment time within 30 seconds. Due to safety factors and site conditions, no tests were conducted for pressures above 4MPa.

[0124] Analysis of the control process of the expert control algorithm in this section shows that the control action factor is relatively large in the initial stage of control, and the opening changes relatively quickly. However, due to the large Cv value in the large opening range, the pressure changes slowly, and the overall pressure rise rate is relatively slow. In the middle stage of control, the action factor decreases, but as the opening decreases, the pressure change accelerates, so the pressure rise rate accelerates. In the later stage, in order to reduce overshoot, the minimum control action coefficient is set, so the opening changes slowly, and the pressure slowly reaches the set value.

[0125] As the pressure setpoint increases, the time constant of the wellhead pressure increases, and overshoot will gradually occur. However, if the overshoot exceeds the accuracy range, the pressure reduction rule will be triggered, and the pressure will eventually stabilize within the accuracy range. Within the accuracy range, the algorithm will stop increasing and decreasing the pressure, and the pressure will slowly "drift" back to the setpoint due to inertia.

[0126] Figure 7a For the variable flow test, the flow rate was reduced from 13 L / s to 8 L / s, the set value was 1 MPa, the adjustment time was 10 s, and the maximum error was 0.4 MPa.

[0127] Figure 7b For the variable flow rate experiment, the flow rate was increased from 8 L / s to 13 L / s, the set value was 0.8 MPa, the adjustment time was 10 s, and the maximum error was 0.3 MPa.

[0128] Figure 7c For the variable flow rate experiment, the flow rate was increased from 8 L / s to 13 L / s, the set value was 3 MPa, the adjustment time was 25 s, and the maximum error was 0.5 MPa.

[0129] The experimental results show that in the variable flow rate experiment, the maximum tracking error is within 0.5 MPa, and the adjustment time is 10 to 25 seconds. As the flow rate increases, the wellhead pressure rises. When the wellhead pressure exceeds the accuracy range, a pressure reduction rule is triggered, slowly adjusting the wellhead pressure back to the set value. When the flow rate decreases, the wellhead pressure initially decreases. When the wellhead pressure exceeds the accuracy range, a pressure increase rule is triggered, and the wellhead pressure rises slowly. In the large opening range, to reduce overshoot, the control action factor is set relatively small, resulting in slower opening changes and therefore a slightly longer adjustment time.

[0130] Field test results show that the expert control strategy in the method has good overall control effect, with an accuracy of 0.3MPa and an adjustment time within 20s, which meets the requirements of pressure controlled drilling.

[0131] In one embodiment, based on a pressure control strategy corresponding to the drilling conditions, drilling site information is processed to obtain a set value for the throttle valve opening, including:

[0132] When the pressure control strategy is a back pressure fuzzy control strategy, the measured value of the wellhead back pressure is determined based on the drilling site information. The measured value of the wellhead back pressure is input into the fuzzy PID controller, and the set value of the throttle valve opening is output. The fuzzy PID controller includes a fuzzy controller and a PID controller. The fuzzy controller is a two-dimensional controller with two inputs and three outputs. The two inputs are the pressure error and its rate of change, and the three outputs are the three adjustable parameters of the PID controller.

[0133] In practice, the fuzzy control strategy mainly involves first defining input and output variables, then selecting linguistic variables and membership functions, and finally performing fuzzy inference.

[0134] The following section uses a controlled-pressure drilling system as an example to explain the specific steps of the backpressure fuzzy control strategy under normal drilling conditions:

[0135] Figure 8 This is a basic schematic diagram of fuzzy PID control. R(s) is the input wellhead pressure value (wellhead pressure setpoint), Y(s) is the system output signal (wellhead pressure measurement value), E(s) is the difference between the system pressure setpoint and the actual measurement value, U(s) is the output of a conventional PID controller, i.e., the throttle valve opening setpoint, e is the pressure error, ec is its error change rate, E and EC are the fuzzy quantities after fuzzifying e and ec, respectively, and K... p proportionality coefficient, K i K is the integral coefficient. d is the differential coefficient.

[0136] (1) Define input and output variables:

[0137] The fuzzy PID controller is a two-dimensional controller with two inputs and three outputs. The pressure error e and its rate of change ec are the input variables, and ΔK is the output variable. p ΔK i and ΔK d For output variables.

[0138] Input e: Based on the pressure control capability of the pressure-controlled equipment and the requirements of the site conditions, the upper limit of the wellhead pressure is set to 6 MPa (this can be adjusted according to specific site conditions and equipment capacity). When the pressure exceeds the limit, the system stops working, and the throttle valve fully opens to release pressure. Based on the actual application of pressure-controlled drilling, the pressure differential generally will not exceed 4 MPa (the set value is obtained from hydraulic calculations, and fluctuations are common). Quantification factor k eThe smaller the value of k, the more stable the system, but the longer the adjustment time. e =1. Therefore, based on actual needs and design optimization, the basic universe of discourse is: [-4, 4]; its standard universe of discourse is: [-4, 4].

[0139] Input ec: The program scan cycle of the S7-400 CPU in the pressure control device is 150ms, meaning it retrieves values ​​from the input register and refreshes the output register every 150ms. Based on the throttle valve's operating speed, the maximum differential pressure change is estimated to be 1MPa. Quantization factor k ec The larger the value of k, the stronger its ability to suppress system changes. ec =3, its fundamental domain is [-1, 1]; its standard domain is [-3, 3].

[0140] If the actual inputs e and ec are not within their fundamental universe of discourse, then amplitude limiting is required.

[0141] Output ΔK p Wellhead pressure control requires no overshoot, ΔK p The value should not be too large, the adjustment time should be extended, and the scaling factor k u1 =0.1, the fundamental universe of discourse is [-0.6, 0.6]; its standard universe of discourse is [-6, 6].

[0142] Output ΔK i Improve wellhead pressure control accuracy, ΔK i The scaling factor k can be appropriately increased. u2 =0.05, the fundamental universe of discourse is [-0.3, 0.3]; its standard universe of discourse is [-6, 6].

[0143] Output ΔK d During drilling, there are many interfering factors, and the wellhead pressure fluctuates frequently, therefore ΔK d The scaling factor k cannot be too large, otherwise it will cause oscillations. u3 =0.15, with the fundamental universe of discourse being [-0.9, 0.9]; and its standard universe of discourse being [-6, 6].

[0144] (2) Selection of linguistic variables and membership functions:

[0145] Input the universe values ​​of linguistic variables e and ec, and output the linguistic variable ΔK. p ΔK i and ΔK d The domain of discourse can take seven values: "negative large" (NB), "negative medium" (NM), "negative small" (NS), "zero" (ZO), "positive small" (PS), "positive medium" (PM), and "positive large" (PB).

[0146] The wellhead pressure setpoint is calculated using a wellbore model and transmitted to the controller via hydraulic software. During drilling, the wellbore model parameters change, and the pressure setpoint changes in real time. Therefore, the system primarily focuses on quickly and accurately tracking the setpoint, i.e., improving control accuracy when the error *e* is small. To achieve this, a finer fuzzy subset partition is used near zero, occupying a smaller domain of discourse. This allows for precise and nuanced control actions near zero, resulting in a triangular membership function. Further away from zero, near extreme points, a faster system response is needed. Therefore, a bell-shaped membership function with lower resolution is chosen for *e*, and a Z-shaped membership function is chosen for *ec*.

[0147] The membership function curves of e and ec are as follows: Figure 9 (a) Figure 9 As shown in (b) of the diagram.

[0148] ΔK p ΔK i ΔK d The membership function is chosen to be a Gaussian membership function, ΔK. p The center point of the Gaussian function is [-6, -4, -2, 0, 2, 4, 6], the width is 0.75, the subset membership function intersection point β is small (β < 0.4), ΔK p The change is gradual. ΔK i The center point of the Gaussian function and ΔK p The width varies with the center point [1.5, 1.25, 1, 0.75], ΔK i The value is relatively large, and the closer it is to the extreme value, the slower the change. ΔK d The center point of the Gaussian function is [-6, -3, -1, 0, 1, 3, 6], the width is 1, and ΔK d The output is small, and the change slows down as it gets closer to zero.

[0149] ΔK p ΔK i ΔK d Membership function curve as shown Figure 10 As shown in (a), (b) and (c) in the figure.

[0150] (3) Rulemaking

[0151] e and ec are the criteria for tuning PID parameters. The effects of drilling factors (opening degree, flow rate, density, etc.) on wellhead pressure are reflected in the changes of e and ec. For example, ec increases when the flow rate increases, and ec changes when the density fluctuates. Therefore, when formulating control rules, different combinations of e and ec are analyzed to determine possible operating conditions, thereby considering changes in the control action (opening degree setpoint), and then ΔK is adjusted according to the meaning of the three PID parameters. p ΔKi ΔK d The PID parameters are analyzed as follows:

[0152] proportionality coefficient K p Its function is to accelerate the system's response speed and improve the system's adjustment accuracy. p The larger the value, the faster the response speed and the higher the adjustment accuracy, but it is prone to overshoot. p The smaller the value, the lower the adjustment precision and the slower the response speed, resulting in a longer adjustment time and a corresponding deterioration in static and dynamic characteristics; the integral coefficient K i Its function is to eliminate the steady-state error K of the system. i The larger K is, the faster the static error is eliminated, but K i An excessively large K value can lead to integral saturation, resulting in significant overshoot. i If the differential coefficient K is too small, the static error is difficult to eliminate, and the set adjustment accuracy cannot be achieved; d The purpose of this is to improve the dynamic characteristics of the system. Its main function is to suppress the change of deviation in any direction. It is necessary to control the differential constant in advance so that it is not too large. Otherwise, the response process will be braked in advance, the adjustment time will be extended, and the differential element will amplify the measurement noise and reduce the system's noise immunity.

[0153] Based on expert control rules, the following parameter tuning principles are proposed:

[0154] (1) When the system starts, the hydraulic software begins to transmit the pressure setpoint. At this time, the pressure error e is relatively large. In order to speed up the adjustment, ΔK p A larger value can be chosen; however, the instantaneous change of error e (ec) is large, which may lead to differential oversaturation, causing the control action to reach its upper limit and the opening to close too small. Therefore, a moderate ΔK should be chosen. d ;ΔK i Set to 0 to prevent wellhead pressure overshoot and integral saturation.

[0155] (2) During the pressurization process, e and ec decrease with the change of the dynamic process and are at a moderate level. At this time, ΔK p ΔK d Take the mean value, ΔK i Appropriate addition ensures that the pressure adjustment time remains within the acceptable range without overshooting.

[0156] (3) When the wellhead pressure is basically stable, e and ec are relatively small, and at this time ΔK p ΔK i Increasing the value of ΔK enhances the stability of the system, while ΔK d The value of ΔK is determined based on ec. To prevent oscillation and enhance anti-interference capability, when ec is large, ΔK d When the smaller value is taken, and ec is relatively small, ΔK dTake the larger one.

[0157] (4) When e > 0, it indicates a pressure increase process, and when e < 0, it indicates a pressure decrease process. The parameters of the pressure increase process change smoothly, which enhances stability and makes it less prone to overshoot. The parameters of the pressure decrease process change rapidly and have a strong control effect, quickly reaching the set value.

[0158] Based on the above PID parameter tuning principles, the output quantity ΔK can be obtained. p ΔK i and ΔK d The control rules are shown in Tables 1, 2, and 3.

[0159] Table 1

[0160]

[0161] Table 2

[0162]

[0163] Table 3

[0164]

[0165] (5) Fuzzy reasoning: The fuzzy decision adopts the Mamdani type algorithm. Based on the membership function of each fuzzy subset and the fuzzy control rule table, the fuzzy matrix table of PID parameters is designed offline by fuzzy synthesis reasoning, and the correction parameters are found and substituted into the following formula for calculation.

[0166]

[0167] Among them, K p (k) is the scaling factor at time k, K p (k-1) represents the scaling factor at time k-1, {e(k), ec(k)} p Let K be the proportionality coefficient change as a function of the pressure error and the rate of change of the error at time k. i (k) is the integral coefficient at time k, K i (k-1) represents the integral coefficients at time k-1, {e(k), ec(k)} i Let K be a function of the change in the integral coefficient with respect to the pressure error and the rate of change of the error at time k. d (k) is the differential coefficient at time k, K d (k-1) represents the differential coefficients at time k-1, {e(k), ec(k)} d It is a function of the change in the differential coefficient with respect to the pressure error and the rate of change of the error at time k.

[0168] During online operation, the control system completes online correction of PID parameters by processing the results of fuzzy logic rules, looking up tables, and performing calculations, using the defuzzified ΔK.p ΔK i and ΔK d The parameters are used for PID control; the control flow is shown below. Figure 11 .

[0169] To further illustrate the feasibility of the method described in this invention, a dynamic simulation model of wellhead pressure was built based on the fine-controlled pressure drilling test data of a certain well, as follows:

[0170]

[0171] Where Δp is the pressure difference, Δq is the flow difference, ΔZ is the throttle valve opening difference, and T... p In the field of control science and engineering, s represents the time constant, which is a mathematical complex frequency domain parameter, while m and c are intermediate temporary parameters with no practical significance. The specific calculation formula is as follows:

[0172]

[0173]

[0174]

[0175] Wherein: T p In the field of control science and engineering, ρ represents the time constant, where p is the wellhead pressure, p0 is the initial pressure, Z is the throttle valve opening, and ρ out Q is the density of the mud outlet. in To inject flow rate into the mud, Q out Q is the mud outlet flow rate. out0 Where C is the initial flow rate, Cv is the throttling coefficient, and V is the flow rate at the initial moment. ann Let θ be the annular volume, β be the fluid compressibility coefficient, and θ be the mathematical representation of the partial derivative.

[0176] The Cv value in the model is obtained from the Z-Cv fitting curve equation (2) above, and the model parameters are shown in Table 4.

[0177] Table 4

[0178]

[0179] The initial PID parameters of the fuzzy controller are set to: K p =1,K i =20,K d =5, the opening degree is adjusted starting from 70%, the wellhead pressure setpoint is initially 2MPa, set to 3MPa after 20s, and set to 1MPa after 40s. The fuzzy PID control effect is as follows: Figure 12 rise time t r The time is 2 seconds, and the adjustment time is t. sThe duration is 5 to 10 seconds, with an overshoot of less than 5%.

[0180] Figure 13 The adjustment effect of the fuzzy PID controller when adding 15%, 30%, and 20% flow disturbances, and the settling time t. s Within 5 seconds, with no overshoot.

[0181] Figure 14 To improve the tracking effect of the fuzzy PID on changes in the setpoint, a sinusoidal signal was selected with a setpoint of 1 MPa and an amplitude of 0.2 MPa.

[0182] The simulation curves show that the fuzzy PID controller can effectively overcome interference factors such as flow fluctuations, and can quickly track real-time changes in the set value, with an adjustment time of 5 to 10 seconds and an overshoot of less than 5%.

[0183] In one embodiment, based on a pressure control strategy corresponding to the drilling conditions, drilling site information is processed to obtain a set value for the throttle valve opening, including:

[0184] When the pressure control strategy is the riser pressure prediction control strategy, the measured value of the riser pressure is determined based on the drilling site information, the measured value of the riser pressure is input into the riser pressure prediction controller, and the set value of the throttle valve opening is output. The riser pressure prediction controller is established based on the dynamic matrix control algorithm.

[0185] In practice, the riser pressure setpoint can be calculated in real time using a mathematical model of the relationship between riser pressure and bottom hole pressure, based on a dynamic matrix control algorithm. Then, the riser pressure can be adjusted by changing the opening of the wellhead throttle valve to achieve pressure-controlled underbalanced drilling.

[0186] The principle of dynamic matrix control algorithm is as follows: Figure 15 It consists of three parts: prediction, correction, and control.

[0187] The difference vector between the expected output value and the predicted output value at time P is multiplied by the dynamic vector dT to obtain the control increment Δu(k):

[0188]

[0189] Where Δu(k) is the control increment, A is the dynamic matrix composed of the parameters in the step vector a, T is the matrix transpose, Q is the error weight matrix, R is the control weight matrix, and ω P (k) represents the given desired output value. This is the predicted output value at the current time obtained by the dynamic matrix control algorithm.

[0190] The control quantity u(k) can be calculated from the control increment Δu(k) through digital integration (accumulation operation):

[0191] u(k)=u(k-1)+Δu(k) (10)

[0192] Where u(k) is the control quantity at time k, u(k-1) is the control quantity at time k-1, Δu(k) is the control increment at time k, and k is the time.

[0193] The system's N predicted output values ​​for the future are equal to the product of the control increment Δu(k) and the step vector a:

[0194]

[0195] Where a is the step vector, that is, the vector composed of the sampled values ​​of the unit step response of the controlled object (a = [a1, a, ..., a)). i , ..., a N ] T ), To predict the value at time k+i from the value at time k, i.e., the predicted output value at a future time (i = 1, 2, ..., N), Let Δu(k) be the initial predicted output value, which is the initial predicted value of the output at time k+i, assuming that the control action remains unchanged, at time k (i = 1, 2, ..., N), and let Δu(k) be the control increment.

[0196] The prediction error e(k+1) is equal to the difference between the actual output value of the object at time k+1 and the predicted output value at that time:

[0197]

[0198] Where e(k+1) is the prediction error, and y(k+1) is the actual output value of the object at time k+1. The predicted output value of the object at time k+1

[0199] After multiplying the error vector e(k+1) by the correction vector h, the corrected prediction output value is calculated. Through shift correction, the corrected prediction output value is obtained.

[0200]

[0201] in, The output prediction (N-dimensional vector) is obtained after shift correction. For the reason The N-dimensional vector consists of weights, where h is the N-dimensional error correction vector composed of weights and e(k+1) is the prediction error vector.

[0202] In the formula, Let (k+1)·T be the predicted output value of the system at time (k+i)·T (i = 1, ..., N) after error correction. This is the error correction vector.

[0203] Finally, according to equation (14), the initial predicted value at that moment is obtained by shifting.

[0204]

[0205] in, Let S be the initial predicted value at time k+1 (an N-dimensional vector), and S be the shift matrix (an N-dimensional matrix). This is the predicted output value (N-dimensional vector) after shift correction.

[0206] In the next cycle, the deviations from the predicted values ​​and expected values, as well as the control increments, are recalculated.

[0207] The value of the optimization time-domain parameter P affects the system's stability and speed. A smaller value of P results in a faster response but poorer stability, making the system prone to overshoot and oscillations. A larger value improves robustness but slows the response. The control time-domain parameter M represents the number of changes in the control quantity, i.e., the length of the predicted output controlled by the algorithm. A smaller value leads to poorer tracking performance. Increasing the control time-domain parameter M can improve the system's control capability but reduces stability and increases the matrix dimension in the algorithm, increasing computational complexity and reducing real-time performance. For a simple control system, a value of 1 is generally sufficient. However, for complex controlled objects, we need to gradually increase its value until the control objective is met.

[0208] Based on the principle of the dynamic matrix prediction algorithm, please refer to the flowchart of the dynamic matrix control algorithm. Figure 16 A riser pressure control system based on a dynamic matrix control algorithm was constructed. The riser pressure model was defined, and the parameters of the dynamic matrix control algorithm (DMC) were initialized, including the control time domain M, optimization time domain P, and sampling time T. s , cut-off step size N, etc.

[0209] The riser pressure model was obtained through systematic identification of a test well, and the specific steps are as follows:

[0210] Wellbore parameters are shown in Table 5:

[0211] Table 5

[0212]

[0213] First, a signal is sent to the throttle valve, setting its opening to 40%. After the pressure stabilizes, the signal is changed, setting the valve opening to 30%, which is equivalent to giving the controlled object a step change. Because the riser pressure has self-balancing properties, the pressure will stabilize again at a certain value. Once the pressure stabilizes again, the response curve of the riser pressure over time and the experimental data can be obtained, such as... Figure 17 The input data is the throttle valve opening Z, and the output data is the riser pressure P. s The least squares identification algorithm is used. The valve opening Z and the riser pressure P are used to identify the valve. s As the input and output data of the system, the data is first zero-mean normalized. A process model is selected, the system order is 1, and a delay element is added. The model obtained through identification is:

[0214]

[0215] Where G(s) is the identified transfer function and e is the pressure error.

[0216] In this example, the system's identification results show a goodness of fit of 88.5%, indicating high fitting accuracy that meets the accuracy requirements. The discrete unit step response sequence is then obtained using the above model and used as a linear prediction model in DMC control.

[0217] The results of the DMC control experiment are as follows:

[0218] (1) Keeping other parameters constant in the program, the riser pressure setpoint changes stepwise, with control time domain M=1 and prediction time domain P=60. The control effect is shown below. Figure 18a , Figure 18b .

[0219] (2) Add disturbances to the program. The riser pressure is set to 8MPa. Add output disturbances of 2MPa, 5MPa, and -5MPa at 80s, 160s, and 240s respectively. The tracking effect is as follows: Figure 19a , Figure 19b .

[0220] (3) When the model is mismatched, that is, when the identified process model parameters Ks, Tp, and τ do not match the actual model parameters, the performance of the simulation analysis algorithm is analyzed. The following simulations are performed for the mismatch of Ks, Tp, and τ respectively.

[0221] Ks mismatch, the increase or decrease of process gain, and its impact on control are as follows: Figure 20a , Figure 20b As shown.

[0222] Tp mismatch, the increase or decrease of the process time constant, and its impact on control are as follows: Figure 21a , Figure 21b As shown.

[0223] τ-mismatch, the increase or decrease of pure time delay, and its impact on control are as follows: Figure 22a , Figure 22b As shown.

[0224] As can be seen from the above model mismatch control effect diagram, process gain Ks mismatch will cause a relatively large change in the output of the control action. The smaller Ks is, the larger the control action, but the impact on the control effect is not significant, and good control effect can still be maintained. The process time constant Tp has a significant impact on the control effect. When Tp decreases, the system overshoot increases and the settling time decreases. When Tp increases, the system control becomes more stable. Pure time delay τ mismatch has a relatively small impact on the system. When τ decreases, the system control effect is better and the overshoot is smaller. When τ increases, the system overshoot increases slightly, but the overall system control effect is still good.

[0225] Simulation results analysis of model mismatch can guide system design, requiring that the design consider the situation of model parameter mismatch as much as possible to enhance the adaptability of the control system and enable it to cope with large changes in operating conditions. Due to the nonlinearity of the throttle valve, the step response curve is different at different opening degrees. Therefore, when designing the system, the step response curve should be selected in the lower opening degree range to maximize the process gain Ks, i.e., Ks 实际 ≤Ks 模型 =Ks max The process time constant Tp takes its minimum value, i.e., Tp 实际 ≥Tp 模型 =Tp min When model mismatch occurs, the system maintains good control performance. The pure time delay τ is related to the propagation speed of the pressure wave, and should be calculated as large as possible as possible as τ as a model parameter based on possible changes in drilling conditions. 实际 ≤τ 模型 =τ max .

[0226] Dynamic matrix control (DMC) uses a step response that is readily available in engineering as a mathematical model. It has low computational load, simple algorithm, and is convenient for online real-time operation. It has good regulation quality and strong robustness. It can suppress the large hysteresis characteristics of the controlled object. It has a good effect on the riser pressure predictive control in this example. The adjustment time is 25 to 50 seconds and the overshoot is controlled below 5%, which meets the requirements of riser pressure control.

[0227] In summary, after processing the drilling site information according to the pressure control strategy corresponding to the drilling conditions to obtain the set value of the throttle valve opening, a pressure control command can be determined based on the set value of the throttle valve opening and sent to the actuator so that the actuator can perform the corresponding operation according to the pressure control command. In this embodiment of the invention, the actuator may refer to the throttle valve.

[0228] It should be clarified that the actuators of the above three strategies (the set value obtained from the control strategy, i.e. how much the throttle valve should be opened, and then the throttle valve is opened or closed automatically or manually, this is the actuator) can all be throttle valves, and the results obtained from the three strategies can also be the set value of the throttle valve, i.e. the opening degree of the throttle valve.

[0229] To further explain, all three strategies can be viewed as consisting of three parts: measured value input, control algorithm calculation, and setpoint (operated value) output. The measured value input refers to sending the wellhead back pressure measurement or riser pressure measurement value from the field to the controller (this process is automatic). The controller then calculates the measured value according to a specific control algorithm (different control algorithms represent different control strategies). After the calculation is complete, the setpoint (operated value) is obtained. The valve opening can be manually changed based on the calculated setpoint, or the throttle valve can automatically change its opening based on the setpoint.

[0230] In addition, after the operating conditions are judged or determined, the engineer can select the control strategy and control algorithm to change. However, the current measured value and the calculated set value will not change immediately. Therefore, it is only necessary to ensure that the calculated set value of the previous control algorithm and the calculated set value of the next control algorithm are consistent before and after the control algorithm switch. This is a disturbance-free switch.

[0231] The structure for implementing the pressure control method in this embodiment of the invention may include:

[0232] ① Sensors are used to collect field data such as pressure before and after the throttle valve, throttle valve opening, mud pump outlet flow rate, and riser pressure.

[0233] ②Programmable logic controller (PLC), used to receive data collected by sensors, calculate control algorithms for different control strategies, communicate with the host computer (usually via network cable), and transmit commands (usually current or voltage signals) to actuators (such as throttle valves, flat valves, proportional valves, switches, relays, etc.).

[0234] ③ The host computer enables human-machine interaction, displaying real-time data collected on-site to engineers or operators. Engineers or operators can also send commands (usually electrical signals) to the programmable controller (PLC) via the host computer (e.g., after determining the current operating condition, selecting or clicking the corresponding operating condition button or text on the host computer, which then transmits this signal to the PLC, which switches to the appropriate control algorithm), achieving remote control. The host computer can also participate in the implementation of some control algorithms; it displays the control algorithm calculation results to engineers, who can then determine whether to execute or use the results, whether the actuator executes automatically or requires manual operation based on the calculation results.

[0235] The following example illustrates the specific operation process of the embodiments of the present invention in practical application:

[0236] ① Data collected on-site reaches the programmable controller;

[0237] ② Engineers or operators can see the measurement data through the host computer, judge or determine the current working condition, select or click the corresponding working condition button or text on the host computer, and the host computer sends this to the programmable controller through communication signals;

[0238] ③ After receiving the signal from the host computer, the programmable controller switches between different control algorithms according to the selected working conditions (the theory of the control algorithm has been explained in detail in this patent), and solves the control algorithm. The solution is then sent back to the host computer.

[0239] ④ Engineers or operators can view the calculation results through the host computer.

[0240] ⑤ The engineer or operator determines whether the solution is feasible. If feasible, they choose whether to have the programmable controller execute the result or to manually operate the actuator based on the result. If not feasible, the engineer or operator decides on the operating instructions, such as the opening degree of a throttle valve.

[0241] ⑥ If the feasibility of the solution is not determined by engineers or operators, but the solution is adopted entirely, steps ④ and ⑤ can be skipped, and full automatic control can be achieved.

[0242] ⑦ The programmable controller sends the calculation result to the actuator through a current or voltage signal. The actuator automatically executes the signal. For example, the programmable controller sends a voltage signal to the electronic control unit of the proportional valve. The electronic control unit drives the proportional valve core to move, which in turn causes the throttle valve core to move under the drive of hydraulic oil, ultimately changing the opening degree of the throttle valve.

[0243] This invention also provides a drilling pressure control device, as described in the following embodiments. Since the principle by which this device solves the problem is similar to that of the drilling pressure control method, the implementation of this device can be referred to the implementation of the drilling pressure control method, and repeated details will not be elaborated further.

[0244] Figure 23 This is a schematic diagram of the drilling pressure control device in an embodiment of the present invention. Figure 23 As shown, the drilling pressure control device in this embodiment of the invention may specifically include:

[0245] The drilling site information acquisition module 231 is used to acquire drilling site information collected by different sensors, including drilling site information such as pressure information before and after the choke valve, choke valve opening information, drilling fluid density information, mud pump outlet flow rate information, wellhead back pressure information, and riser pressure information.

[0246] The drilling condition determination module 232 is used to query the first database based on the drilling site information to determine the drilling condition corresponding to the drilling site information. The first database stores drilling conditions corresponding to different drilling site information, including valve position tracking condition, normal drilling condition and gas intrusion condition.

[0247] The pressure control strategy determination module 233 is used to query the second database according to the drilling conditions to determine the pressure control strategy corresponding to the drilling conditions. The second database stores pressure control strategies corresponding to different drilling conditions, including expert control strategies, back pressure fuzzy control strategies and riser pressure prediction control strategies.

[0248] The drilling site information processing module 234 is used to process the drilling site information according to the pressure control strategy corresponding to the drilling conditions to obtain the set value of the throttle valve opening.

[0249] The pressure control command determination and transmission module 235 is used to determine the pressure control command based on the set value of the throttle valve opening and send the pressure control command to the actuator so that the actuator can perform the corresponding operation according to the pressure control command.

[0250] In one embodiment, the pressure control strategy determination module is specifically used for:

[0251] When the drilling operation is valve position tracking operation, the second database is queried according to the valve position tracking operation to determine the pressure control strategy corresponding to the valve position tracking operation as the expert control strategy.

[0252] When the drilling condition is normal drilling condition, the second database is queried according to the normal drilling condition to determine the pressure control strategy corresponding to the normal drilling condition as the back pressure fuzzy control strategy.

[0253] When the drilling operation is under gas invasion conditions, the second database is queried based on the gas invasion conditions to determine the pressure control strategy corresponding to the gas invasion conditions as the riser pressure prediction control strategy.

[0254] In one embodiment, the drilling site information processing module is specifically used for:

[0255] When the pressure control strategy is an expert control strategy, the throttle valve opening measurement value, mud pump outlet flow value, and drilling fluid density value are determined based on drilling site information.

[0256] The measured values ​​of the throttle valve opening, the mud pump outlet flow rate, and the drilling fluid density are input into the expert PID controller. The influence factors in the expert PID controller are assigned segmented values, and the set value of the throttle valve opening is output. The expert PID controller is designed based on the influence factors and control factors. The influence factors represent the factors that directly or indirectly affect the wellhead pressure, and the control factors represent the control capability of the throttle valve at different opening degrees.

[0257] In one embodiment, the drilling site information processing module is specifically used for:

[0258] When the pressure control strategy is a back pressure fuzzy control strategy, the measured value of the wellhead back pressure is determined based on the drilling site information. The measured value of the wellhead back pressure is input into the fuzzy PID controller, and the set value of the throttle valve opening is output. The fuzzy PID controller includes a fuzzy controller and a PID controller. The fuzzy controller is a two-dimensional controller with two inputs and three outputs. The two inputs are the pressure error and its rate of change, and the three outputs are the three adjustable parameters of the PID controller.

[0259] In one embodiment, the drilling site information processing module is specifically used for:

[0260] When the pressure control strategy is the riser pressure prediction control strategy, the measured value of the riser pressure is determined based on the drilling site information, the measured value of the riser pressure is input into the riser pressure prediction controller, and the set value of the throttle valve opening is output. The riser pressure prediction controller is established based on the dynamic matrix control algorithm.

[0261] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described drilling pressure control method.

[0262] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described drilling pressure control method.

[0263] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described drilling pressure control method.

[0264] In summary, the embodiments of the present invention acquire drilling site information collected by different sensors; query a first database based on the drilling site information to determine the drilling conditions corresponding to the drilling site information. The first database stores drilling conditions corresponding to different drilling site information, including valve position tracking conditions, normal drilling conditions, and gas intrusion conditions; query a second database based on the drilling conditions to determine the pressure control strategy corresponding to the drilling conditions. The second database stores pressure control strategies corresponding to different drilling conditions, including expert control strategies, back pressure fuzzy control strategies, and riser pressure prediction control strategies; process the drilling site information according to the pressure control strategy corresponding to the drilling conditions to obtain the set value of the throttle valve opening; determine the pressure control command based on the set value of the throttle valve opening, and send the pressure control command to the actuator so that the actuator can perform the corresponding operation according to the pressure control command. This can form a multi-condition, multi-strategy pressure control method, reducing drilling costs and improving drilling efficiency.

[0265] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0266] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0267] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0268] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0269] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A drilling pressure control method, characterized in that, include: Acquire drilling site information collected by different sensors, including drilling site information such as pressure before and after the choke valve, choke valve opening information, drilling fluid density information, mud pump outlet flow rate information, wellhead back pressure information, and riser pressure information; The drilling conditions corresponding to the drilling site information are determined by querying the first database based on the drilling site information. The first database stores drilling conditions corresponding to different drilling site information, including valve position tracking conditions, normal drilling conditions, and gas intrusion conditions. The second database is queried based on the drilling conditions to determine the pressure control strategy corresponding to the drilling conditions. The second database stores pressure control strategies corresponding to different drilling conditions, including expert control strategies, back pressure fuzzy control strategies, and riser pressure prediction control strategies. Based on the pressure control strategy corresponding to the drilling conditions, the drilling site information is processed to obtain the set value of the throttle valve opening. The pressure control command is determined based on the set value of the throttle valve opening and sent to the actuator so that the actuator can perform the corresponding operation according to the pressure control command. Based on the pressure control strategy corresponding to the drilling conditions, the drilling site information is processed to obtain the set value of the throttle valve opening, including: When the pressure control strategy is an expert control strategy, the throttle valve opening measurement value, mud pump outlet flow value, and drilling fluid density value are determined based on drilling site information. When using expert control strategies to solve the problem of controlling wellhead pressure in actual equipment, the influencing factors are analyzed, including throttle valve opening Z, outlet flow rate Q, and drilling fluid density D. By analyzing these influencing factors, appropriate state description variables are selected to form control rules. Based on the characteristic equation of fluid flow in a pipe, the flow rate Q through the throttle valve is obtained. v The pressure difference ΔP between it and the pressure before and after it v The relationship is: Where Cv is the throttling coefficient; ΔP v σ is the pressure difference across the throttle valve; Q is the fluid density; v This refers to the flow rate of the throttle valve; After specifying the units for each variable, the coefficient Cv depends on the flow cross-sectional area and is related to the valve type, diameter, and opening degree. The measured values ​​of the throttle valve opening, the mud pump outlet flow rate, and the drilling fluid density are input into the expert PID controller. The influence factors in the expert PID controller are assigned segmented values, and the set value of the throttle valve opening is output. The expert PID controller is designed based on the influence factors and control factors. The influence factors represent the factors that directly or indirectly affect the wellhead pressure, and the control factors represent the control capability of the throttle valve at different opening degrees.

2. The method as described in claim 1, characterized in that, Based on the drilling conditions, a second database is consulted to determine the pressure control strategy corresponding to the drilling conditions, including: When the drilling operation is valve position tracking operation, the second database is queried according to the valve position tracking operation to determine the pressure control strategy corresponding to the valve position tracking operation as the expert control strategy. When the drilling condition is normal drilling condition, the second database is queried according to the normal drilling condition to determine the pressure control strategy corresponding to the normal drilling condition as the back pressure fuzzy control strategy. When the drilling operation is under gas invasion conditions, the second database is queried based on the gas invasion conditions to determine the pressure control strategy corresponding to the gas invasion conditions as the riser pressure prediction control strategy.

3. The method as described in claim 2, characterized in that, Based on the pressure control strategy corresponding to the drilling conditions, the drilling site information is processed to obtain the set value of the throttle valve opening, including: When the pressure control strategy is a back pressure fuzzy control strategy, the measured value of the wellhead back pressure is determined based on the drilling site information. The measured value of the wellhead back pressure is input into the fuzzy PID controller, and the set value of the throttle valve opening is output. The fuzzy PID controller includes a fuzzy controller and a PID controller. The fuzzy controller is a two-dimensional controller with two inputs and three outputs. The two inputs are the pressure error and its rate of change, and the three outputs are the three adjustable parameters of the PID controller.

4. The method as described in claim 2, characterized in that, Based on the pressure control strategy corresponding to the drilling conditions, the drilling site information is processed to obtain the set value of the throttle valve opening, including: When the pressure control strategy is the riser pressure prediction control strategy, the measured value of the riser pressure is determined based on the drilling site information, the measured value of the riser pressure is input into the riser pressure prediction controller, and the set value of the throttle valve opening is output. The riser pressure prediction controller is established based on the dynamic matrix control algorithm.

5. A drilling pressure control device, characterized in that, include: The drilling site information acquisition module is used to acquire drilling site information collected by different sensors. The drilling site information includes pressure information before and after the choke valve, choke valve opening information, drilling fluid density information, mud pump outlet flow rate information, wellhead back pressure information, and riser pressure information. The drilling condition determination module is used to query the first database based on the drilling site information to determine the drilling condition corresponding to the drilling site information. The first database stores the drilling conditions corresponding to different drilling site information, including valve position tracking condition, normal drilling condition and gas intrusion condition. The pressure control strategy determination module is used to query the second database based on the drilling conditions to determine the pressure control strategy corresponding to the drilling conditions. The second database stores pressure control strategies corresponding to different drilling conditions, including expert control strategies, back pressure fuzzy control strategies, and riser pressure prediction control strategies. The drilling site information processing module is used to process drilling site information according to the pressure control strategy corresponding to the drilling conditions, and obtain the set value of the throttle valve opening. The pressure control command determination and transmission module is used to determine the pressure control command based on the set value of the throttle valve opening, and send the pressure control command to the actuator so that the actuator can perform the corresponding operation according to the pressure control command; The drilling site information processing module is used to determine the throttle valve opening measurement value, mud pump outlet flow value, and drilling fluid density value based on the drilling site information when the pressure control strategy is an expert control strategy. When using expert control strategies to solve the problem of controlling wellhead pressure in actual equipment, the influencing factors are analyzed, including throttle valve opening Z, outlet flow rate Q, and drilling fluid density D. By analyzing these influencing factors, appropriate state description variables are selected to form control rules. Based on the characteristic equation of fluid flow in a pipe, the flow rate Q through the throttle valve is obtained. v The pressure difference ΔP between it and the pressure before and after it v The relationship is: Where Cv is the throttling coefficient; ΔP v ρ is the pressure difference across the throttle valve; Q is the fluid density; v This refers to the flow rate of the throttle valve; After specifying the units for each variable, the coefficient Cv depends on the flow cross-sectional area and is related to the valve type, diameter, and opening degree. The measured values ​​of the throttle valve opening, the mud pump outlet flow rate, and the drilling fluid density are input into the expert PID controller. The influence factors in the expert PID controller are assigned segmented values, and the set value of the throttle valve opening is output. The expert PID controller is designed based on the influence factors and control factors. The influence factors represent the factors that directly or indirectly affect the wellhead pressure, and the control factors represent the control capability of the throttle valve at different opening degrees.

6. The apparatus as claimed in claim 5, characterized in that, The pressure control strategy determination module is specifically used for: When the drilling operation is valve position tracking operation, the second database is queried according to the valve position tracking operation to determine the pressure control strategy corresponding to the valve position tracking operation as the expert control strategy. When the drilling condition is normal drilling condition, the second database is queried according to the normal drilling condition to determine the pressure control strategy corresponding to the normal drilling condition as the back pressure fuzzy control strategy. When the drilling operation is under gas invasion conditions, the second database is queried based on the gas invasion conditions to determine the pressure control strategy corresponding to the gas invasion conditions as the riser pressure prediction control strategy.

7. The apparatus as claimed in claim 6, characterized in that, The drilling site information processing module is specifically used for: When the pressure control strategy is a back pressure fuzzy control strategy, the measured value of the wellhead back pressure is determined based on the drilling site information. The measured value of the wellhead back pressure is input into the fuzzy PID controller, and the set value of the throttle valve opening is output. The fuzzy PID controller includes a fuzzy controller and a PID controller. The fuzzy controller is a two-dimensional controller with two inputs and three outputs. The two inputs are the pressure error and its rate of change, and the three outputs are the three adjustable parameters of the PID controller.

8. The apparatus as claimed in claim 6, characterized in that, The drilling site information processing module is specifically used for: When the pressure control strategy is the riser pressure prediction control strategy, the measured value of the riser pressure is determined based on the drilling site information, the measured value of the riser pressure is input into the riser pressure prediction controller, and the set value of the throttle valve opening is output. The riser pressure prediction controller is established based on the dynamic matrix control algorithm.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1 to 4.

11. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method of any one of claims 1 to 4.

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