Well mouth overflow risk prediction system and method

Abstract

The invention relates to the technical field of well mouth overflow, and discloses a well mouth overflow risk prediction system and method, and the system comprises a well mouth overflow monitoring information analysis module, a well mouth overflow risk evaluation module, and a well mouth overflow processing scheme planning module. On the basis of a drilling mud pool liquid level variation grade and a drilling mud pump outlet flow velocity variation grade, an intelligent identification algorithm and preset drilling opening overflow risk grade data are combined to predict and intelligently evaluate the risk grade of mud overflow at a drilling opening in the drilling process. The overflow risk of the drilling opening is intelligently predicted based on the mud pit liquid level change parameter and the outlet flow speed change parameter; according to the drilling mouth overflow risk level prediction data, the drilling management platform, the display screen and the buzzer are combined to execute risk prompting operation of mud overflow accidents of the drilling mouth in the drilling process, timely and visual feedback of a drilling mouth overflow risk prediction result is achieved, and the response speed of drilling mouth overflow state monitoring is increased.

Description

Technical Field

[0001] The present invention relates to the technical field of wellhead overflow in drilling, and specifically to a system and method for predicting the risk of wellhead overflow in drilling. Background Technique

[0002] The main reason for wellhead overflow is that the bottom hole pressure is lower than the formation pore pressure, and its pressure exceeds the drilling fluid column pressure, resulting in the abnormal intrusion of the fluid formed by the combination of oil, gas, and water in the formation into the wellbore and flowing out of the wellhead. This phenomenon is called wellhead overflow. When drilling water gushes out, phenomena such as hole wall collapse, sand gushing, and drill tool sinking often occur; the risk prediction of wellhead overflow usually monitors the wellhead overflow state based on the bottom hole pressure and the formation void pressure. However, due to the complex and variable underground state during the drilling process and measurement errors, it is impossible to achieve intelligent, precise, and reliable monitoring of the wellhead overflow state based on the change parameters of the mud pit liquid level and the outlet flow rate, increasing the risk of drilling operations.

[0003] The Chinese invention patent with the publication number CN116796647B and the publication date of November 19, 2024 discloses a training and prediction method for an intelligent prediction model of drilling overflow conditions and a downhole overflow risk probability prediction system. Through data preprocessing, training a machine learning swarm intelligence model, selecting the optimal fusion model, predicting with the optimal fusion model, and visualization; it can realize real-time monitoring of the overflow conditions, and can also realize the advanced prediction of overflow, and visualize the overflow occurrence probability in the current and future time periods, and can give targeted AI operation suggestions when predicting the overflow conditions to further help avoid the occurrence of overflow; still, the above technical solutions cannot accurately predict the drilling overflow state based on the change parameters of the mud pit liquid level and the outlet flow rate. Summary of the Invention

[0004] (I) Technical Problems to be Solved To solve the above problems that due to the complex and variable underground state during the drilling process and measurement errors, it is impossible to achieve intelligent, precise, and reliable monitoring of the wellhead overflow state based on the change parameters of the mud pit liquid level and the outlet flow rate, increasing the risk of drilling operations, and to achieve the purpose of accurately collecting the change amount of the mud pit liquid level per unit time and the change amount of the outlet flow rate of the mud pump per unit time, scientifically analyzing the abnormal change level of the mud pit liquid level, intelligently analyzing the abnormal change level of the outlet flow rate of the mud pump, accurately predicting and evaluating the risk level of wellhead overflow, and precisely planning the emergency plan information for different wellhead overflow risks.

[0005] (II) Technical Solutions The present invention is achieved through the following technical solutions: A method for predicting the risk of wellhead overflow in drilling, the method comprising the following steps: S1. Collect the change amount of the mud pit liquid level per unit time and the change amount of the outlet flow rate of the mud pump per unit time; S2. Analyze and process the abnormal change level of the mud pit liquid level during the drilling process based on the change amount of the mud pit liquid level per unit time and the intervals of the change amounts of the mud pit liquid level per unit time for different abnormal change levels, and generate the analysis data of the abnormal change level of the mud pit liquid level during drilling; S3. Analyze and process the abnormal change level of the outlet flow rate of the mud pump during the drilling process based on the change amount of the outlet flow rate of the mud pump per unit time and the intervals of the change amounts of the outlet flow rate of the mud pump per unit time for different abnormal change levels, and generate the analysis data of the abnormal change level of the outlet flow rate of the mud pump during drilling; S4. Perform risk level prediction processing on the risk of mud overflow at the drilling wellhead during the drilling process based on the analysis data of the abnormal change level of the mud pit liquid level, the analysis data of the abnormal change level of the outlet flow rate of the mud pump, and the risk level data of the wellhead overflow, and generate the predicted data of the risk level of the wellhead overflow; S5. Execute the risk warning operation for the accident of mud overflow at the drilling wellhead during the drilling process according to the predicted data of the risk level of the wellhead overflow; S6. Plan the emergency treatment plan for mud overflows with different risk levels at the drilling wellhead during the drilling process based on the predicted data of the risk level of the wellhead overflow and the emergency treatment plan data for different overflow risk levels at the drilling wellhead, and generate the planned data of the emergency treatment plan for the wellhead overflow risk; S7. Execute the risk emergency feedback operation for the accident of mud overflow at the drilling wellhead during the drilling process based on the planned data of the emergency treatment plan for the wellhead overflow risk.

[0006] Preferably, the specific operation steps for collecting the change amount of the mud pit liquid level per unit time and the change amount of the outlet flow rate of the mud pump per unit time are as follows: S11. Online collect the information on the increase change amount of the mud liquid level in the mud pit during the drilling process per unit time through an ultrasonic liquid level sensor, and generate the change amount of the mud pit liquid level per unit time; Online collect the information on the change amount of the outlet flow rate of the mud pump during the drilling process per unit time through a mud flowmeter, and generate the change amount of the outlet flow rate of the mud pump per unit time.

[0007] Preferably, the specific operation steps for analyzing and processing the abnormal change level of the mud pit liquid level during the drilling process based on the change amount of the mud pit liquid level per unit time and the intervals of the change amounts of the mud pit liquid level per unit time for different abnormal change levels, and generating the analysis data of the abnormal change level of the mud pit liquid level during drilling are as follows: S21. Establish a set of intervals of the change amounts of the mud pit liquid level per unit time for different abnormal change levels , ; where represents the interval of the change amount of the mud pit liquid level per unit time for different abnormal change levels corresponding to the th type of abnormal change level type of the mud pit liquid level during drilling, Represents the maximum value of the number of types of abnormal change levels of the drilling mud pit liquid level; among them , among them and respectively represent the range of the change amount of the drilling mud pit liquid level per unit time for different abnormal change levels The minimum change amount of the drilling mud pit liquid level per unit time and the maximum change amount of the drilling mud pit liquid level per unit time for different abnormal change levels. The abnormal change level type of the drilling mud pit liquid level represents the degree of increase in the mud liquid level per unit time in the drilling mud pit. The greater the degree of increase in the mud liquid level per unit time, the greater the abnormal change level of the drilling mud pit liquid level during the drilling process, and the greater the risk of overflow accident at the drilling wellhead; The range of the change amount of the drilling mud pit liquid level per unit time for different abnormal change levels represents the range value of the standard change amount of the mud liquid level per unit time in the drilling mud pit set for different types of abnormal change levels of the drilling mud pit liquid level; S22. Use the K-D tree nearest neighbor search algorithm to compare the change amount of the drilling mud pit liquid level per unit time with the set of ranges of the change amount of the drilling mud pit liquid level per unit time for different abnormal change levels Among them, the range of the change amount of the drilling mud pit liquid level per unit time for different abnormal change levels Among them, the minimum change amount of the drilling mud pit liquid level per unit time for different abnormal change levels and the maximum change amount of the drilling mud pit liquid level per unit time for different abnormal change levels to perform a numerical comparison of the change amount of the drilling mud pit liquid level per unit time, and search for the range of the change amount of the drilling mud pit liquid level per unit time for different abnormal change levels corresponding to the text information of the abnormal change level type of the drilling mud pit liquid level, and generate the analysis data of the abnormal change level of the drilling mud pit liquid level through data identification.

[0008] Preferably, the specific operation steps for analyzing the abnormal change level of the outlet flow rate of the mud pump during the drilling process according to the change amount of the outlet flow rate of the mud pump per unit time and the range of the change amount of the outlet flow rate of the mud pump per unit time for different abnormal change levels are as follows: S31. Establish a set of ranges of the change amount of the outlet flow rate of the mud pump per unit time for different abnormal change levels , ; among them represents the range of the change amount of the outlet flow rate of the mud pump per unit time corresponding to the th type of abnormal change level of the outlet flow rate of the drilling mud pump, represents the maximum value of the number of types of abnormal change levels of the outlet flow rate of the drilling mud pump; among them , among them and respectively represent the range of the change amount of the outlet flow rate of the mud pump per unit time for different abnormal change levels The minimum change amount of the mud pump outlet flow rate per unit time and the maximum change amount of the mud pump outlet flow rate per unit time at different abnormal change levels, where the abnormal change level type of the drilling mud pump outlet flow rate represents the degree of increase in the mud outlet flow rate of the drilling mud pump per unit time. The greater the degree of increase in the mud outlet flow rate per unit time, the greater the abnormal change level of the mud pump outlet flow rate during drilling, and the greater the risk of overflow accident at the drilling wellhead; the change amount interval of the mud pump outlet flow rate per unit time at different abnormal change levels represents the range value of the standard increase degree of the mud outlet flow rate of the standard drilling mud pump per unit time set for different types of abnormal change levels of the drilling mud pump outlet flow rate; S32. Use the uniform cost search algorithm to combine the change amount of the mud pump outlet flow rate per unit time with the set of change amount intervals of the mud pump outlet flow rate per unit time at different abnormal change levels in the change amount intervals of the mud pump outlet flow rate per unit time at different abnormal change levels in the minimum change amount of the mud pump outlet flow rate per unit time at different abnormal change levels and the maximum change amount of the mud pump outlet flow rate per unit time at different abnormal change levels to perform a numerical comparison of the change amount of the mud pump outlet flow rate per unit time, and search for the change amount interval of the mud pump outlet flow rate per unit time at different abnormal change levels to which the change amount of the mud pump outlet flow rate per unit time belongs The corresponding text information of the abnormal change level type of the drilling mud pump outlet flow rate is generated, and the analysis data of the abnormal change level of the drilling mud pump outlet flow rate is generated through data identification.

[0009] Preferably, based on the analysis data of the abnormal change level of the drilling mud pool liquid level, the analysis data of the abnormal change level of the drilling mud pump outlet flow rate, and the drilling wellhead overflow risk level data, the risk level prediction process of mud overflow at the drilling wellhead during drilling is performed. The specific operation steps for generating the drilling wellhead overflow risk level prediction data are as follows: S41. Establish a set of drilling wellhead overflow risk level data , ; where represents the drilling wellhead overflow risk level data corresponding to the th combination type of drilling mud abnormal change states, represents the maximum value of the number of combination types of drilling mud abnormal change levels. The combination type of drilling mud abnormal change levels represents an index data type for evaluating the drilling wellhead overflow risk level mainly formed by combining the abnormal change level information of the drilling mud pool liquid level and the abnormal change level information of the drilling mud pump outlet flow rate; the drilling wellhead overflow risk level data represents the standard drilling wellhead overflow risk level evaluation information set based on the combination type of drilling mud abnormal change levels; the greater the drilling wellhead overflow risk level, the greater the risk of overflow accident at the drilling wellhead; S42, combining the drilling mud pool liquid level abnormality level analysis data, the drilling mud pump outlet flow rate abnormality level analysis data and the wellhead overflow risk level data Wellhead overflow risk level data described in Perform keyword matching of drilling mud pool liquid level abnormality level and drilling mud pump outlet flow rate abnormality level, and search for the drilling mud pool liquid level abnormality level analysis data and the drilling mud pump outlet flow rate abnormality level analysis data corresponding to the wellhead overflow risk level data. , and generate drilling head overflow risk level prediction data through data identification; the specific operation steps for generating the drilling head overflow risk level prediction data are as follows: S421, initializing parameters and updating the maximum number of iterations T of the algorithm; S422, initializing the risk prediction data set of the seagull population overflow risk level at the wellhead The position in the search space of S423: Calculate the wellhead overflow risk level data set Wellhead overflow risk level data described in The fitness value of the drilling mud pool liquid level abnormality level analysis data and the drilling mud pump outlet flow rate abnormality level analysis data is retained and the global optimal position is retained; S424, Migration, Global Search: Risk prediction of seagull migration behavior has three main steps: first, to meet collision avoidance conditions and ensure population diversity; second, to calculate the direction of the optimal position; third, to move to a new position based on the direction of the optimal position; S4241. Calculate the risk prediction data set of the overflow risk level of the seagull at the wellhead. The new position of the seagull that does not collide with the adjacent risk prediction seagulls during the movement in the search space ;in , ,in, Data collection for risk prediction of seagull overflow risk level at the wellhead The current position in the search space of is the current iteration number; Represents the control risk prediction seagull overflow risk level data set at the wellhead The adjustment parameters of the motion behavior in the search space of Display Control Correction factor for frequency of change, Represents a random number in the range [0,2]; S4242: Calculate the overflow risk level data set at the wellhead The search space of the drilling mud pool liquid level abnormality level analysis data and the drilling mud pump outlet flow rate abnormality level analysis data that best matches the drilling well overflow risk level data The direction of the best position ;in , ,in Indicates the drilling port overflow risk level data that best matches the drilling mud pool liquid level abnormality level analysis data and the drilling mud pump outlet flow rate abnormality level analysis data In the wellhead overflow risk level data collection The current best position in the search space of Represents the control risk prediction seagull overflow risk level data set at the wellhead Random numbers for global and local search capabilities in the search space; Represents a random number in the range [0,1]; S4243, according to the wellhead overflow risk level data set The search space of the drilling mud pool liquid level abnormality level analysis data and the drilling mud pump outlet flow rate abnormality level analysis data that best matches the drilling well overflow risk level data The direction of the best position moves to the new position , , that is, the overflow risk level data set at the wellhead according to the direction of the optimal position The drilling mud pool liquid level abnormality level analysis data and the drilling mud pump outlet flow rate abnormality level analysis data that best match the drilling well overflow risk level data are searched in the search space new location; S425. Attacking prey, local search, risk prediction, seagull overflow risk level data set at the wellhead Search the search space for the drilling mud pool liquid level abnormality level analysis data and the drilling mud pump outlet flow rate abnormality level analysis data that match the drilling well overflow risk level data The prey performs spiral motion in the air, and the risk prediction seagull attacks the drilling mud pool liquid level abnormality level analysis data and the drilling mud pump outlet flow rate abnormality level analysis data matching the drilling port overflow risk level data. After the prey, update the overflow risk level data set at the wellhead The new position of the search space ,in , that is, the risk prediction seagull is the data set of the overflow risk level at the wellhead Search for the wellhead overflow risk level data that matches the analysis data of the abnormal change level of the drilling mud pit liquid level and the analysis data of the abnormal change level of the outlet flow rate of the drilling mud pump in the search space prey; S426. When the maximum number of iterations T is reached, output the wellhead overflow risk level data that matches the analysis data of the abnormal change level of the drilling mud pit liquid level and the analysis data of the abnormal change level of the outlet flow rate of the drilling mud pump ; Otherwise, return to step S423; S427. The wellhead overflow risk level data output in step S426 Generate wellhead overflow risk level prediction data through data identification.

[0010] Preferably, the specific operation steps for performing the risk warning operation of the mud overflow accident at the wellhead during the drilling process according to the wellhead overflow risk level prediction data are as follows: S51. Transmit the wellhead overflow risk level prediction data to the drilling management platform through the Internet of Things communication network, output the wellhead overflow risk level prediction result through the display screen, and cooperate with the buzzer to perform the wellhead overflow risk warning operation.

[0011] Preferably, the specific operation steps for generating the wellhead overflow risk emergency treatment plan planning data by performing the emergency treatment plan planning for different risk level mud overflows at the wellhead during the drilling process based on the wellhead overflow risk level prediction data and the emergency treatment plan data for different overflow risk levels at the wellhead are as follows: S61. Establish a data set of emergency treatment plans for different overflow risk levels at the wellhead[[ID=2--1]] , ; where represents the emergency treatment plan data for different overflow risk levels at the wellhead corresponding to the th type of wellhead overflow risk level type, represents the maximum value of the number of wellhead overflow risk level types; the emergency treatment plan data for different overflow risk levels at the wellhead represents the optimal wellhead overflow risk emergency treatment plan information set based on the wellhead overflow risk level type; the emergency treatment plan data for different overflow risk levels at the wellhead includes the emergency treatment method for stopping drilling, the emergency treatment method for shutting in the well, and the emergency treatment method for killing the well; S62. Use the iterative search algorithm to compare the wellhead overflow risk level prediction data with the data set of emergency treatment plans for different overflow risk levels at the wellhead in the emergency treatment plan data for different overflow risk levels at the wellhead Perform keyword matching for the overflow risk level of the drilling wellhead, and search for the emergency treatment plan data corresponding to different overflow risk levels of the drilling wellhead for the predicted data of the overflow risk level of the drilling wellhead. And generate the emergency treatment plan planning data for the overflow risk of the drilling wellhead through data identification.

[0012] Preferably, the specific operation steps for performing the risk emergency feedback operation for the mud overflow accident at the drilling wellhead during the drilling process based on the emergency treatment plan planning data for the overflow risk of the drilling wellhead are as follows: S71. Transmit the emergency treatment plan planning data for the overflow risk of the drilling wellhead to the drilling management platform through the Internet of Things communication network, and the drilling management platform feeds back and notifies the drilling emergency management department to perform the risk emergency feedback operation for the mud overflow accident at the drilling wellhead during the drilling process.

[0013] A drilling wellhead overflow risk prediction system for implementing the above-mentioned drilling wellhead overflow risk prediction method, the system includes a drilling wellhead overflow monitoring information analysis module, a drilling wellhead overflow risk assessment module, and a drilling wellhead overflow treatment plan planning module; The drilling wellhead overflow monitoring information analysis module includes a unit time mud pit liquid level change amount acquisition unit, a unit time mud pump outlet flow rate change amount acquisition unit, a different anomaly level unit time mud pit liquid level change amount interval storage unit, a mud pit liquid level anomaly level analysis unit, a different anomaly level unit time mud pump outlet flow rate change amount interval storage unit, and a mud pump outlet flow rate anomaly level analysis unit; The unit time mud pit liquid level change amount acquisition unit acquires the unit time mud pit liquid level change amount through an ultrasonic liquid level sensor; the unit time mud pump outlet flow rate change amount acquisition unit acquires the unit time mud pump outlet flow rate change amount through a mud flowmeter; the different anomaly level unit time mud pit liquid level change amount interval storage unit is used to store different anomaly level unit time mud pit liquid level change amount intervals; the mud pit liquid level anomaly level analysis unit performs analysis and processing on the anomaly level of the mud pit liquid level during the drilling process based on the unit time mud pit liquid level change amount and different anomaly level unit time mud pit liquid level change amount intervals, and generates drilling mud pit liquid level anomaly level analysis data; the different anomaly level unit time mud pump outlet flow rate change amount interval storage unit is used to store different anomaly level unit time mud pump outlet flow rate change amount intervals; the mud pump outlet flow rate anomaly level analysis unit performs analysis and processing on the anomaly level of the mud pump outlet flow rate during the drilling process according to the unit time mud pump outlet flow rate change amount and different anomaly level unit time mud pump outlet flow rate change amount intervals, and generates drilling mud pump outlet flow rate anomaly level analysis data; The wellhead overflow risk assessment module includes a wellhead overflow risk level storage unit, a wellhead overflow risk level prediction unit, and a wellhead overflow risk level prediction result output unit; The wellhead overflow risk level storage unit is used to store wellhead overflow risk level data; the wellhead overflow risk level prediction unit performs risk level prediction processing on the occurrence of mud overflow at the wellhead during the drilling process based on the abnormal change level analysis data of the mud pit liquid level, the abnormal change level analysis data of the outlet flow rate of the mud pump, and the wellhead overflow risk level data, and generates wellhead overflow risk level prediction data; the wellhead overflow risk level prediction result output unit performs risk warning operations on the occurrence of mud overflow accidents at the wellhead during the drilling process according to the wellhead overflow risk level prediction data and in combination with the drilling management platform, the display screen, and the buzzer; The wellhead overflow treatment plan planning module includes an emergency treatment plan storage unit for different overflow risk levels at the wellhead, a wellhead overflow risk emergency treatment plan planning unit, and a wellhead overflow risk emergency feedback unit; The emergency treatment plan storage unit for different overflow risk levels at the wellhead is used to store emergency treatment plan data for different overflow risk levels at the wellhead; the wellhead overflow risk emergency treatment plan planning unit performs emergency treatment plan planning processing on the occurrence of mud overflow with different risk levels at the wellhead during the drilling process based on the wellhead overflow risk level prediction data and the emergency treatment plan data for different overflow risk levels at the wellhead, and generates wellhead overflow risk emergency treatment plan planning data; the wellhead overflow risk emergency feedback unit performs risk emergency feedback operations on the occurrence of mud overflow accidents at the wellhead during the drilling process based on the wellhead overflow risk emergency treatment plan planning data and in combination with the drilling management platform to notify the drilling emergency management department;

[0014] (III) Beneficial effects The present invention provides a wellhead overflow risk prediction system and method. It has the following beneficial effects: 1. Dynamically and reliably collect the parameters of the change in the liquid level of the mud pit per unit time and the parameters of the change in the flow rate at the outlet of the mud pump per unit time through ultrasonic liquid level sensors and mud flow meters, and provide reliable data support for the intelligent evaluation of the abnormal change level of the liquid level in the drilling mud pit and the abnormal change level of the flow rate at the outlet of the drilling mud pump during the drilling process; based on the change in the liquid level of the mud pit per unit time, combined with the intelligent search algorithm and the intervals of the change in the liquid level of the mud pit per unit time at different abnormal change levels stored in the big data, conduct an autonomous and dynamic analysis of the abnormal change level of the liquid level in the mud pit during the drilling process to achieve precise monitoring of the change state of the liquid level in the mud pit during the drilling process; according to the change in the flow rate at the outlet of the mud pump per unit time and combined with the intelligent search algorithm and the preset intervals of the change in the flow rate at the outlet of the mud pump per unit time at different abnormal change levels, conduct an intelligent statistics of the abnormal change level of the flow rate at the outlet of the mud pump during the drilling process to achieve digital detection of the flow rate state at the outlet of the mud pump during the drilling process and improve the scientific nature of the monitoring of the overflow risk at the drilling wellhead.

[0015] 2. Conduct an intelligent evaluation of the risk level prediction of mud overflow at the drilling wellhead during the drilling process by combining the abnormal change level of the liquid level in the drilling mud pit, the abnormal change level of the flow rate at the outlet of the drilling mud pump, the intelligent recognition algorithm, and the preset data of the overflow risk level at the drilling wellhead, and realize the intelligent prediction of the overflow risk at the drilling wellhead based on the change parameters of the liquid level in the mud pit and the change parameters of the outlet flow rate, and improve the reliability of the prediction result of the overflow risk at the drilling wellhead; according to the prediction data of the overflow risk level at the drilling wellhead and combined with the drilling management platform, display screen, and buzzer, perform the risk warning operation of mud overflow accident at the drilling wellhead during the drilling process, and realize the timely and intuitive feedback of the prediction result of the overflow risk at the drilling wellhead to improve the response speed of the monitoring of the overflow state at the drilling wellhead.

[0016] 3. Based on the prediction information of the overflow risk level at the drilling wellhead, combined with the intelligent search algorithm and the data of the emergency treatment plans for different overflow risk levels at the drilling wellhead stored in the big data, conduct a precise and rapid planning of the emergency treatment plans for mud overflow at different risk levels at the drilling wellhead during the drilling process to realize the intelligent and reliable planning of the emergency treatment plans for the overflow risk at the drilling wellhead and improve the safety and rationality of the treatment of the overflow accident at the drilling wellhead; based on the planning information of the emergency treatment plans for the overflow risk at the drilling wellhead and combined with the drilling management platform, notify the drilling emergency management department to perform the risk emergency feedback operation of mud overflow accident at the drilling wellhead during the drilling process, and realize the intelligent visualization processing of the overflow danger and treatment plan at the drilling wellhead to improve the intelligence and efficiency of the treatment of the overflow risk at the drilling wellhead. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic diagram of the modules of a system for predicting the overflow risk at a drilling wellhead provided by the present invention; Figure 2 It is a flowchart of a method for predicting the overflow risk at a drilling wellhead provided by the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] The embodiments of the wellhead overflow risk prediction system and method are as follows: Embodiment 1: See also Figure 1 - Figure 2 A method for predicting wellhead overflow risk comprises the following steps: S1. Collect the change of the mud pool liquid level per unit time and the change of the mud pump outlet flow rate per unit time; S2. Analyze and process the abnormal change level of the mud pool liquid level during drilling based on the change amount of the mud pool liquid level per unit time and the intervals of the change amount of the mud pool liquid level per unit time of different abnormal change levels, and generate drilling mud pool liquid level abnormal change level analysis data; S3. Analyze and process the abnormal variation level of the mud pump outlet flow rate during the drilling process based on the change in the mud pump outlet flow rate per unit time and the intervals of the change in the mud pump outlet flow rate per unit time at different abnormal variation levels, and generate drilling mud pump outlet flow rate abnormal variation level analysis data; S4. Predicting the risk level of mud overflow at the wellhead during the drilling process based on the drilling mud pool liquid level abnormality level analysis data, the drilling mud pump outlet flow velocity abnormality level analysis data, and the wellhead overflow risk level data to generate wellhead overflow risk level prediction data; S5. Execute risk warning operations for mud overflow accidents at the wellhead during drilling based on the wellhead overflow risk level prediction data; S6. Planning emergency treatment plans for mud overflows at different risk levels at the drill head during the drilling process based on the well head overflow risk level prediction data and the emergency treatment plan data for different well head overflow risk levels, thereby generating planning data for the emergency treatment plan for the well head overflow risk; S7. Based on the wellhead overflow risk emergency treatment plan planning data, perform risk emergency feedback operations for mud overflow accidents occurring at the wellhead during the drilling process.

[0020] For further information, see Figure 1 - Figure 2 The specific steps for collecting the change in the mud pool liquid level per unit time and the change in the mud pump outlet flow rate per unit time are as follows: S11, using an ultrasonic level sensor to collect online information on the amount of change in the mud level in the mud pool during the drilling process per unit time, and generate a unit time mud pool level change; The mud flow meter is used to collect the outlet flow rate change information of the mud pump during the drilling process per unit time online, and the outlet flow rate change of the mud pump per unit time is generated.

[0021] The specific steps for analyzing and processing the abnormal level of the mud pool during drilling are as follows: S21. Establish a set of intervals for the change in the mud pool liquid level per unit time at different mutation levels , ;in Indicates The range of the amount of change of the mud pool liquid level per unit time corresponding to the different types of drilling mud pool liquid level change levels is as follows: Indicates the maximum number of drilling mud pool liquid level abnormality level types; ,in and Respectively represent the intervals of the change in the mud pool liquid level per unit time at different mutation levels The minimum change in the mud pool liquid level per unit time for different abnormality levels and the maximum change in the mud pool liquid level per unit time for different abnormality levels are shown. The drilling mud pool liquid level abnormality level type indicates the degree of change in the mud level rise per unit time in the drilling mud pool. The greater the degree of change in the mud level rise per unit time, the greater the abnormality level of the mud pool liquid level during the drilling process, and the greater the risk of overflow accidents at the wellhead. The range of the mud pool liquid level change per unit time for different abnormality levels indicates the range of the standard drilling mud pool liquid level change per unit time set for different types of drilling mud pool liquid level abnormality levels. S22, using the KD tree nearest neighbor search algorithm to compare the unit time mud pool liquid level change and the unit time mud pool liquid level change interval set of different mutation levels. The range of the change of the mud pool liquid level per unit time at different mutation levels Minimum change of mud pool liquid level per unit time at different mutation levels The maximum change of the mud pool liquid level per unit time at different mutation levels Compare the values of the mud pool level change per unit time and search for the different abnormality levels and intervals of the mud pool level change per unit time. The corresponding drilling mud pool liquid level abnormality grade type text information is used, and the drilling mud pool liquid level abnormality grade analysis data is generated through data identification.

[0022] The specific steps for analyzing and processing the abnormal variation level of the mud pump outlet flow rate during drilling are to generate the analysis data of the abnormal variation level of the mud pump outlet flow rate during drilling according to the variation of the mud pump outlet flow rate per unit time and the variation range of the mud pump outlet flow rate per unit time of different abnormal variation levels. S31. Establish a set of intervals for the change in the mud pump outlet flow rate per unit time at different levels of abnormality , ;in Indicates The different types of drilling mud pump outlet flow rate variation levels correspond to the unit time intervals of the mud pump outlet flow rate variation levels. Indicates the maximum number of types of flow rate variation at the outlet of the drilling mud pump; ,in and Respectively represent the intervals of the change in the mud pump outlet flow rate per unit time at different abnormality levels The minimum change in the mud pump outlet flow rate per unit time for different abnormality levels and the maximum change in the mud pump outlet flow rate per unit time for different abnormality levels are shown. The abnormality level type of the drilling mud pump outlet flow rate indicates the degree of increase in the mud pump outlet flow rate per unit time. The greater the degree of increase in the mud pump outlet flow rate per unit time, the greater the abnormality level of the mud pump outlet flow rate during the drilling process, and the greater the risk of overflow accidents at the wellhead. The range of the change in the mud pump outlet flow rate per unit time for different abnormality levels indicates the range of the standard degree of increase in the mud pump outlet flow rate per unit time set for different types of drilling mud pump outlet flow rate abnormality levels. S32, using a unified cost search algorithm to compare the unit time mud pump outlet flow rate change and the unit time mud pump outlet flow rate change interval set of different abnormality levels The variation range of mud pump outlet flow rate per unit time at different abnormality levels Minimum change of mud pump outlet flow rate per unit time at different abnormality levels The maximum change of mud pump outlet flow rate per unit time at different abnormality levels Compare the values of the change in the outlet flow rate of the mud pump per unit time, and search for the different abnormal levels and intervals of the change in the outlet flow rate of the mud pump per unit time. The corresponding drilling mud pump outlet flow rate abnormality level type text information is used, and the drilling mud pump outlet flow rate abnormality level analysis data is generated through data identification.

[0023] Through the cooperation of the unit-time mud pit liquid level change amount acquisition unit and the unit-time mud pump outlet flow rate change amount acquisition unit, the ultrasonic liquid level sensor and the mud flowmeter are respectively used to dynamically and reliably acquire the unit-time mud pit liquid level change amount parameter and the unit-time mud pump outlet flow rate change amount parameter, providing reliable data support for the intelligent evaluation of the abnormal change level of the drilling mud pit liquid level and the abnormal change level of the mud pump outlet flow rate during the drilling process; the mud pit liquid level abnormal change level analysis unit, based on the unit-time mud pit liquid level change amount, combines the intelligent search algorithm and the unit-time mud pit liquid level change amount interval of different abnormal change levels stored in the big data to perform the autonomous dynamic analysis of the abnormal change level of the mud pit liquid level during the drilling process, realizing the accurate monitoring of the change state of the mud pit liquid level during the drilling process; the mud pump outlet flow rate abnormal change level analysis unit, according to the unit-time mud pump outlet flow rate change amount and combines the intelligent search algorithm and the unit-time mud pump outlet flow rate change amount interval preset by the standard to perform the intelligent statistics of the abnormal change level of the mud pump outlet flow rate during the drilling process, realizing the digital detection of the mud pump outlet flow rate state during the drilling process, and improving the scientificity of the overflow risk monitoring at the drilling wellhead.

[0024] Further, please refer to Figure 1 - Figure 2 , and the specific operation steps for predicting the risk level of mud overflow at the drilling wellhead based on the analysis data of the abnormal change level of the drilling mud pit liquid level, the analysis data of the abnormal change level of the mud pump outlet flow rate and the risk level data of the mud overflow at the drilling wellhead are as follows: S41. Establish a set of risk level data for mud overflow at the drilling wellhead , ; where represents the risk level data of the mud overflow at the drilling wellhead corresponding to the th combination type of drilling mud abnormal change state, represents the maximum value of the number of combination types of drilling mud abnormal change levels. The combination type of drilling mud abnormal change levels represents an index data type for evaluating the risk level of mud overflow at the drilling wellhead mainly formed by the combination of the abnormal change level information of the drilling mud pit liquid level and the abnormal change level information of the mud pump outlet flow rate; the risk level data of the mud overflow at the drilling wellhead represents the standard risk level evaluation information of the mud overflow at the drilling wellhead set based on the combination type of drilling mud abnormal change levels; the greater the risk level of the mud overflow at the drilling wellhead, the greater the risk of the overflow accident at the drilling wellhead; S42. Combine the analysis data of the abnormal change level of the drilling mud pit liquid level, the analysis data of the abnormal change level of the mud pump outlet flow rate and the risk level data of the mud overflow at the drilling wellhead in the set of the risk level data of the mud overflow at the drilling wellhead Perform keyword matching on the abnormal change level of the drilling mud pit liquid level and the abnormal change level of the outlet flow rate of the drilling mud pump, and search for the drilling well overflow risk level data corresponding to the abnormal change level analysis data of the drilling mud pit liquid level and the abnormal change level analysis data of the outlet flow rate of the drilling mud pump , and generate the predicted data of the drilling well overflow risk level through data identification; the specific operation steps for generating the predicted data of the drilling well overflow risk level are as follows: S421. Initialize parameters and update the maximum number of iterations T of the algorithm; S422. Initialize the positions of the risk prediction seagull population in the search space of the drilling well overflow risk level data set ; S423. Calculate the fitness values of the drilling well overflow risk level data in the drilling well overflow risk level data set and the abnormal change level analysis data of the drilling mud pit liquid level and the abnormal change level analysis data of the outlet flow rate of the drilling mud pump, and retain the global optimal position; S424. Migration, global search: The migration behavior of the risk prediction seagull mainly has three steps. First, it is necessary to meet the collision avoidance condition to ensure population diversity; second, calculate the direction of the best position; third, move to a new position according to the direction of the best position; S4241. Calculate the new position where the risk prediction seagull does not collide with adjacent risk prediction seagulls during the internal movement process in the search space of the drilling well overflow risk level data set ; where ; , where is the current position of the risk prediction seagull in the search space of the drilling well overflow risk level data set ; is the current number of iterations; represents the adjustment parameter that controls the movement behavior of the risk prediction seagull in the search space of the drilling well overflow risk level data set , represents control the correction coefficient of the change frequency, represents a random number in the range of [0, 2]; S4242. Calculate the direction of the best position of the drilling well overflow risk level data that best matches the abnormal change level analysis data of the drilling mud pit liquid level and the abnormal change level analysis data of the outlet flow rate of the drilling mud pump in the search space of the drilling well overflow risk level data set ; where ; , where ​​​​Indicates the drilling well overflow risk level data that best matches the analysis data of the liquid level variation level in the drilling mud pit and the analysis data of the outlet flow rate variation level of the drilling mud pump At the current best position in the search space of the drilling well overflow risk level data set ; Indicates a random number that controls the global and local search capabilities of the risk prediction seagull in the search space of the drilling well overflow risk level data set ; Indicates a random number within the range of [0, 1]; S4243. According to the drilling well overflow risk level data set Search space and the drilling well overflow risk level data that best matches the analysis data of the liquid level variation level in the drilling mud pit and the analysis data of the outlet flow rate variation level of the drilling mud pump Move to a new position in the direction of the best position , , that is, search in the search space of the drilling well overflow risk level data set according to the direction of the best position to find the drilling well overflow risk level data that best matches the analysis data of the liquid level variation level in the drilling mud pit and the analysis data of the outlet flow rate variation level of the drilling mud pump ; New position; S425. Attack the prey, perform local search. The risk prediction seagull searches in the search space of the drilling well overflow risk level data set For the drilling well overflow risk level data that matches the analysis data of the liquid level variation level in the drilling mud pit and the analysis data of the outlet flow rate variation level of the drilling mud pump When attacking the prey, perform a spiral motion in the air. After the risk prediction seagull attacks the drilling well overflow risk level data that matches the analysis data of the liquid level variation level in the drilling mud pit and the analysis data of the outlet flow rate variation level of the drilling mud pump Prey, update the new position in the search space of the drilling well overflow risk level data set , where , that is, the risk prediction seagull searches in the search space of the drilling well overflow risk level data set For the drilling well overflow risk level data that matches the analysis data of the liquid level variation level in the drilling mud pit and the analysis data of the outlet flow rate variation level of the drilling mud pump Prey; ; S426. When the maximum number of iterations T is satisfied, output the drilling well overflow risk level data that matches the analysis data of the liquid level variation level in the drilling mud pit and the analysis data of the outlet flow rate variation level of the drilling mud pump ; Otherwise, return to step S423; S427. The drilling wellhead overflow risk level data output in step S426 is used to generate drilling wellhead overflow risk level prediction data through data identification.

[0025] The specific operation steps for performing the risk warning operation of mud overflow accident at the drilling wellhead during the drilling process according to the drilling wellhead overflow risk level prediction data are as follows: S51. Transmit the drilling wellhead overflow risk level prediction data to the drilling management platform through the Internet of Things communication network, output the drilling wellhead overflow risk level prediction result through the display screen, and cooperate with the buzzer to perform the drilling wellhead overflow risk warning operation.

[0026] Through the drilling wellhead overflow risk level prediction unit, based on the abnormal change level of the drilling mud pit liquid level and the abnormal change level of the drilling mud pump outlet flow rate, and combined with the intelligent recognition algorithm and the preset drilling wellhead overflow risk level data, perform the intelligent evaluation of the risk level prediction of mud overflow at the drilling wellhead during the drilling process, realize the intelligent prediction of the drilling wellhead overflow risk based on the mud pit liquid level change parameters and the outlet flow rate change parameters, and improve the reliability of the drilling wellhead overflow risk prediction result; the drilling wellhead overflow risk level prediction result output unit, according to the drilling wellhead overflow risk level prediction data and combined with the drilling management platform, the display screen and the buzzer, perform the risk warning operation of mud overflow accident at the drilling wellhead during the drilling process, realize the timely and intuitive feedback of the drilling wellhead overflow risk prediction result, and improve the response speed of the drilling wellhead overflow state monitoring.

[0027] Furthermore, please refer to Figure 1 - Figure 2 and perform the emergency treatment plan planning for mud overflow with different risk levels at the drilling wellhead during the drilling process according to the drilling wellhead overflow risk level prediction data and the emergency treatment plan data for different overflow risk levels at the drilling wellhead. The specific operation steps for generating the drilling wellhead overflow risk emergency treatment plan planning data are as follows: S61. Establish a data set of emergency treatment plans for different overflow risk levels at the drilling wellhead , where represents the emergency treatment plan data for different overflow risk levels at the drilling wellhead corresponding to the th type of drilling wellhead overflow risk level type, represents the maximum value of the number of drilling wellhead overflow risk level types; the emergency treatment plan data for different overflow risk levels at the drilling wellhead represents the optimal drilling wellhead overflow risk emergency treatment plan information set based on the drilling wellhead overflow risk level type; the emergency treatment plan data for different overflow risk levels at the drilling wellhead includes the emergency treatment method for stopping drilling, the emergency treatment method for shutting in the well, and the emergency treatment method for killing the well; S62. Use the iterative search algorithm to combine the drilling wellhead overflow risk level prediction data with the data set of emergency treatment plans for different overflow risk levels at the drilling wellhead Emergency treatment plan data for different overflow risk levels at the drilling wellhead Perform keyword matching for the overflow risk level at the drilling wellhead to search for the emergency treatment plan data for different overflow risk levels at the drilling wellhead corresponding to the predicted data of the overflow risk level at the drilling wellhead and generate the emergency treatment plan planning data for the overflow risk at the drilling wellhead through data identification.

[0028] The specific operation steps for performing the risk emergency feedback operation in case of mud overflow accident at the drilling wellhead during the drilling process based on the emergency treatment plan planning data for the overflow risk at the drilling wellhead are as follows: S71. Transmit the emergency treatment plan planning data for the overflow risk at the drilling wellhead to the drilling management platform through the Internet of Things communication network. The drilling management platform feeds back and notifies the drilling emergency management department to perform the risk emergency feedback operation in case of mud overflow accident at the drilling wellhead during the drilling process.

[0029] Through the emergency treatment plan planning unit for the overflow risk at the drilling wellhead, based on the predicted information of the overflow risk level at the drilling wellhead, combined with the intelligent search algorithm and the emergency treatment plan data for different overflow risk levels at the drilling wellhead stored in the big data, accurately and quickly plan the emergency treatment plan for mud overflow with different risk levels at the drilling wellhead during the drilling process, realize the intelligent and reliable planning of the emergency treatment plan for the overflow risk at the drilling wellhead, and improve the safety and rationality of the treatment of the overflow accident at the drilling wellhead; the emergency feedback unit for the overflow risk at the drilling wellhead, based on the emergency treatment plan planning information for the overflow risk at the drilling wellhead and combined with the feedback from the drilling management platform, notifies the drilling emergency management department to perform the risk emergency feedback operation in case of mud overflow accident at the drilling wellhead during the drilling process, realizes the intelligent visualization processing of the overflow danger and the treatment plan at the drilling wellhead, and improves the intelligence and efficiency of the treatment of the overflow risk at the drilling wellhead.

[0030] Through the emergency treatment plan planning unit for the overflow risk at the drilling wellhead, based on the predicted information of the overflow risk level at the drilling wellhead, combined with the intelligent search algorithm and the emergency treatment plan data for different overflow risk levels at the drilling wellhead stored in the big data, accurately and quickly plan the emergency treatment plan for mud overflow with different risk levels at the drilling wellhead during the drilling process, realize the intelligent and reliable planning of the emergency treatment plan for the overflow risk at the drilling wellhead, and improve the safety and rationality of the treatment of the overflow accident at the drilling wellhead; the emergency feedback unit for the overflow risk at the drilling wellhead, based on the emergency treatment plan planning information for the overflow risk at the drilling wellhead and combined with the feedback from the drilling management platform, notifies the drilling emergency management department to perform the risk emergency feedback operation in case of mud overflow accident at the drilling wellhead during the drilling process, realizes the intelligent visualization processing of the overflow danger and the treatment plan at the drilling wellhead, and improves the intelligence and efficiency of the treatment of the overflow risk at the drilling wellhead.

[0031] Example 2: Please refer to Figure 1 - Figure 2A wellhead overflow risk prediction system is used to implement a wellhead overflow risk prediction method. The system includes a wellhead overflow monitoring information analysis module, a wellhead overflow risk assessment module, and a wellhead overflow treatment plan planning module; The drilling head overflow monitoring information analysis module includes a unit for collecting the amount of change in the mud pool liquid level per unit time, a unit for collecting the amount of change in the mud pump outlet flow rate per unit time, a unit for storing intervals of the amount of change in the mud pool liquid level per unit time at different abnormality levels, a unit for analyzing the abnormality levels of the mud pool liquid level, a unit for storing intervals of the amount of change in the mud pump outlet flow rate per unit time at different abnormality levels, and a unit for analyzing the abnormality levels of the mud pump outlet flow rate; The unit for collecting the amount of change in the mud pool liquid level per unit time uses an ultrasonic level sensor to collect the amount of change in the mud pool liquid level per unit time; the unit for collecting the amount of change in the mud pump outlet flow rate per unit time uses a mud flow meter to collect the amount of change in the mud pump outlet flow rate per unit time; the unit for storing the intervals of the amount of change in the mud pool liquid level per unit time at different abnormality levels is used to store the intervals of the amount of change in the mud pool liquid level per unit time at different abnormality levels; the unit for analyzing the level of change in the mud pool liquid level per unit time analyzes the amount of change in the mud pool liquid level per unit time and the intervals of the amount of change in the mud pool liquid level per unit time at different abnormality levels. Analyze and process the abnormal level variation level of the mud pool during drilling to generate analysis data of the abnormal level variation level of the drilling mud pool; a storage unit for the interval of the change amount of the mud pump outlet flow rate per unit time at different abnormal level is used to store the interval of the change amount of the mud pump outlet flow rate per unit time at different abnormal level; a mud pump outlet flow rate abnormality variation level analysis unit analyzes and processes the abnormal level variation level of the mud pump outlet flow rate during drilling based on the change amount of the mud pump outlet flow rate per unit time and the interval of the change amount of the mud pump outlet flow rate per unit time at different abnormal level to generate analysis data of the abnormal level variation level of the drilling mud pump outlet flow rate; The wellhead overflow risk assessment module includes a wellhead overflow risk level storage unit, a wellhead overflow risk level prediction unit, and a wellhead overflow risk level prediction result output unit; A wellhead overflow risk level storage unit is used to store wellhead overflow risk level data; a wellhead overflow risk level prediction unit performs risk level prediction processing for mud overflow at the wellhead during the drilling process based on the drilling mud pool liquid level abnormality level analysis data, the drilling mud pump outlet flow velocity abnormality level analysis data, and the wellhead overflow risk level data, and generates drilling head overflow risk level prediction data; a drilling head overflow risk level prediction result output unit performs risk warning operations for mud overflow accidents at the wellhead during the drilling process based on the drilling head overflow risk level prediction data and in combination with the drilling management platform, display screen, and buzzer; The wellhead overflow treatment plan planning module includes a wellhead overflow risk level emergency treatment plan storage unit, a wellhead overflow risk emergency treatment plan planning unit, and a wellhead overflow risk emergency feedback unit; A storage unit for emergency treatment plans of different overflow risk levels at the drilling wellhead, which is used to store the data of emergency treatment plans for different overflow risk levels at the drilling wellhead; a planning unit for emergency treatment plans of overflow risks at the drilling wellhead, which conducts planning and processing of emergency treatment plans for mud overflow with different risk levels occurring at the drilling wellhead during the drilling process based on the predicted data of overflow risk levels at the drilling wellhead and the data of emergency treatment plans for different overflow risk levels at the drilling wellhead, and generates the planning data of emergency treatment plans for overflow risks at the drilling wellhead; an emergency feedback unit for overflow risks at the drilling wellhead, based on the planning data of emergency treatment plans for overflow risks at the drilling wellhead and in combination with the feedback from the drilling management platform, notifies the drilling emergency management department to perform the risk emergency feedback operation for mud overflow accidents occurring at the drilling wellhead during the drilling process.

[0032] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for predicting the overflow risk of a drilling wellhead, characterized in that, The method includes the following steps: S1. Collect the change amount of the mud pit liquid level per unit time and the change amount of the outlet flow rate of the mud pump per unit time; S2. Conduct an analysis and processing of the abnormal change level of the mud pit liquid level during the drilling process to generate the analysis data of the abnormal change level of the mud pit liquid level during drilling; S3. Conduct an analysis and processing of the abnormal change level of the outlet flow rate of the mud pump during the drilling process to generate the analysis data of the abnormal change level of the outlet flow rate of the mud pump during drilling; S4. Conduct a risk level prediction and processing of the mud overflow at the drilling wellhead during the drilling process to generate the prediction data of the overflow risk level at the drilling wellhead; S5. Execute the risk prompt operation of the mud overflow accident at the drilling wellhead during the drilling process according to the prediction data of the overflow risk level at the drilling wellhead; S6. Conduct an emergency treatment plan planning and processing of the mud overflow with different risk levels at the drilling wellhead during the drilling process to generate the planning data of the emergency treatment plan for the overflow risk at the drilling wellhead; S7. Execute the risk emergency feedback operation of the mud overflow accident at the drilling wellhead during the drilling process based on the planning data of the emergency treatment plan for the overflow risk at the drilling wellhead.

2. The method for predicting the overflow risk of a drilling wellhead according to claim 1, characterized in that: The S1 includes the following steps: S11. Online collect the information of the increase change amount of the mud liquid level in the mud pit during the drilling process per unit time through an ultrasonic liquid level sensor, and generate the change amount of the mud pit liquid level per unit time; Online collect the information of the change amount of the outlet flow rate of the mud pump during the drilling process per unit time through a mud flowmeter, and generate the change amount of the outlet flow rate of the mud pump per unit time.

3. The method for predicting the overflow risk of a drilling wellhead according to claim 2, wherein: The S2 includes the following steps: S21. Establish a set of intervals of the change amount of the mud pit liquid level per unit time for different mutation levels , the includes , where represents the interval of the change amount of the mud pit liquid level per unit time for the th type of drilling mud pit liquid level mutation level type. Among them, , where and respectively represent the minimum change amount of the mud pit liquid level per unit time and the maximum change amount of the mud pit liquid level per unit time in the interval of the change amount of the mud pit liquid level per unit time for different mutation levels ; S22, using the KD tree nearest neighbor search algorithm to compare the unit time mud pool liquid level change with the As stated in As stated in and stated Compare the values of the mud pool level change per unit time and search for the unit time mud pool level change to which the The corresponding drilling mud pool liquid level abnormality grade type text information is used, and the drilling mud pool liquid level abnormality grade analysis data is generated through data identification.

4. The method for predicting the overflow risk of a drilling wellhead according to claim 3, characterized in that: The S3 includes the following steps: S31. Establish a set of intervals of the change amount of the outlet flow rate of the mud pump per unit time for different mutation levels , where the includes , among which represents the interval of the change amount of the outlet flow rate of the mud pump per unit time for the th type of mutation level of the outlet flow rate of the drilling mud pump; among which , among which and respectively represent the minimum change amount of the outlet flow rate of the mud pump per unit time and the maximum change amount of the outlet flow rate of the mud pump per unit time for different mutation levels in the interval of the change amount of the outlet flow rate of the mud pump per unit time for different mutation levels ; S32, using a unified cost search algorithm to compare the change in the outlet flow rate of the mud pump per unit time with the As stated in As stated in and stated Perform a numerical comparison of the change in the outlet flow rate of the mud pump per unit time, and search for the unit to which the change in the outlet flow rate of the mud pump per unit time belongs. The corresponding drilling mud pump outlet flow rate abnormality level type text information is used, and the drilling mud pump outlet flow rate abnormality level analysis data is generated through data identification.

5. A method for predicting the overflow risk of a drilling wellhead according to claim 4, characterized in that: The S4 includes the following steps: S41. Establish a data set of the overflow risk levels of the well drilling openings , where the includes ; among which represents the overflow risk level data of the well drilling opening corresponding to the th combination type of abnormal changes in the drilling mud. The combination type of abnormal changes in the drilling mud represents an index data type for evaluating the overflow risk level of the well drilling opening, which is mainly formed by combining the abnormal change level information of the liquid level in the drilling mud pit and the abnormal change level information of the flow rate at the outlet of the drilling mud pump S42. Analyze the data on the abnormal change level of the drilling mud pit liquid level, the data on the abnormal change level of the outlet flow rate of the drilling mud pump, and the described in Perform keyword matching on the abnormal change level of the drilling mud pit liquid level and the abnormal change level of the outlet flow rate of the drilling mud pump to search for the corresponding of the data on the abnormal change level of the drilling mud pit liquid level and the data on the abnormal change level of the outlet flow rate of the drilling mud pump, and generate prediction data on the overflow risk level of the drilling wellhead through data identification; The specific operation steps for generating the prediction data on the overflow risk level of the drilling wellhead are as follows: S421. Initialize the parameters and update the maximum number of iterations T of the algorithm; S422. Initialize the position of the risk prediction seagull population in the search space of the ; S423. Calculate the described in fitness values with the abnormal change level analysis data of the drilling mud pit liquid level and the abnormal change level analysis data of the outlet flow rate of the drilling mud pump, and retain the global optimal position; S424. Migration, global search: The migration behavior of the risk prediction seagulls mainly has three steps. First, it is necessary to meet the condition of avoiding collision to ensure the population diversity; second, calculate the direction of the best position; third, move to the new position according to the direction of the best position; S4241. Calculate a new position where the risk prediction seagull does not collide with adjacent risk prediction seagulls during the internal movement in the search space ; S4242. Calculate the direction of the best position of the in the search space that best matches the abnormal change level analysis data of the drilling mud pit liquid level and the abnormal change level analysis data of the outlet flow rate of the drilling mud pump ; ; S4243. Move to a new position in the direction of the best position that has the most matching search space with the abnormal change level analysis data of the drilling mud pit liquid level and the abnormal change level analysis data of the outlet flow rate of the drilling mud pump; ​ S425. Attack the prey, perform local search, and predict risks. The seagull searches for the prey that matches the analysis data of the abnormal change level of the drilling mud pool liquid level and the analysis data of the abnormal change level of the outlet flow rate of the drilling mud pump in the search space of the seagull. When searching for the prey, the seagull makes a spiral movement in the air. After the seagull attacks the prey that matches the analysis data of the abnormal change level of the drilling mud pool liquid level and the analysis data of the abnormal change level of the outlet flow rate of the drilling mud pump, it updates the new position in the search space of ; S426. When the maximum number of iterations T is satisfied, output the that matches the analysis data of the abnormal change level of the drilling mud pit liquid level and the analysis data of the abnormal change level of the outlet flow rate of the drilling mud pump; otherwise, return to step S423. S427. Generate the predicted data of the overflow risk level of the wellhead through the data identification of the output of step S426. ​ 6. The method for predicting the overflow risk of a drilling wellhead according to claim 5, characterized in that: The S5 includes the following steps: S51. Transmit the prediction data of the overflow risk level at the drilling wellhead to the drilling management platform through the Internet of Things communication network, output the prediction result of the overflow risk level at the drilling wellhead through a display screen, and cooperate with a buzzer to perform the overflow risk warning prompt operation at the drilling wellhead.

7. A method for predicting the overflow risk of a drilling wellhead according to claim 6, characterized in that: The S6 includes the following steps: S61. Establish a data set of emergency treatment plans for different overflow risk levels at the wellhead , the includes ; among which represents the emergency treatment plan data for different overflow risk levels at the wellhead corresponding to the th type of overflow risk level at the wellhead; S62. Using an iterative search algorithm, match the predicted data of the drilling well overflow risk level with the described in for keyword matching of the drilling well overflow risk level, and search for the corresponding to the predicted data of the drilling well overflow risk level, and generate the planning data for the emergency treatment plan of the drilling well overflow risk through data identification.

8. A method for predicting the overflow risk of a drilling wellhead according to claim 7, characterized in that: The S7 includes the following steps: S71. Transmit the planning data of the emergency treatment plan for the overflow risk at the drilling wellhead to the drilling management platform through the Internet of Things communication network, and the drilling management platform feeds back and notifies the drilling emergency management department to execute the risk emergency feedback operation of the mud overflow accident at the drilling wellhead during the drilling process.

9. A drilling wellhead overflow risk prediction system for implementing the drilling wellhead overflow risk prediction method according to any one of claims 1-8, characterized in that: The system includes a monitoring information analysis module for the overflow at the drilling wellhead, a risk assessment module for the overflow at the drilling wellhead, and a processing plan planning module for the overflow at the drilling wellhead.

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