Simulation data analysis method for mechanical properties of soft rock

Abstract

The invention discloses a simulation data analysis method for soft rock mechanical properties, which comprises the following steps: collecting different geological structure information and soft rock component ratio information of an oil drill bit drilling system for simulation; using a K nearest neighbor algorithm for data collection; providing a simulation analysis prompt for oil drill bit drilling parameters by setting algorithm parameters and oil drill bit drilling mechanical data types under different formation pore pressure conditions based on simulation software; sending each group of oil drill bit drilling parameter monitoring data under different formation pore pressure conditions collected by monitoring oil drill bit drilling parameters under different formation pore pressure conditions into a simulation model for oil drill bit drilling mechanical data types under different formation pore pressure conditions; solving differential equations for the simulated oil drill bit drilling mechanical data types under different formation pore pressure conditions; the invention is used for accurately and efficiently simulating oil drill bit drilling parameters under different formation pore pressure conditions for effective simulation analysis.

Description

Technical Field

[0001] The present invention relates to the field of soft rock mechanics data analysis, and in particular to a soft rock mechanics property simulation data analysis method. Background Art

[0002] With the development of simulation technology of drilling mechanics data types of oil drill bits under different formation pore pressure conditions, it has been widely used in the field of oil drilling due to its many characteristics such as accurate data, high safety factor and easy use.

[0003] At present, the oil drill bit drilling mechanics data type simulation device under different formation pore pressure conditions set on various devices mainly simulates the oil drill bit drilling mechanics data type under different formation pore pressure conditions in two ways. Remote simulation: The oil drill bit drilling mechanics data type simulation device under different formation pore pressure conditions set on the device sends the simulated feature code to the cloud, which stores big data. The cloud compares the feature code with the big data to obtain the simulation result and feeds it back to the device, so as to achieve the role of oil drill bit drilling mechanics data type simulation under different formation pore pressure conditions. However, the simulation process must be connected to the Internet, that is, the action of sending the feature code to the cloud must be completed, and the data stability and security of the feature code during the transmission process must be guaranteed; in addition, the simulation efficiency of remote simulation is affected by the transmission network and the cloud server. Once the cloud is destroyed, it will bring about a malicious reaction. On-site simulation: The feature code obtained by the simulation device under different formation pore pressure conditions set on the device is directly compared on the local device, and a database of a certain capacity is stored on the local device. This method can avoid the problems existing in remote simulation. However, the storage capacity of the local device is limited, that is, the storage repository for on-site simulation is extremely valuable and is not suitable for use in situations with large amounts of data.

[0004] In the prior art, there are many situations where multiple independent simulation devices for oil drill bit drilling mechanics data types under different formation pore pressure conditions need to be connected. In most cases, remote simulation is used for processing. However, the remote simulation method has the problems mentioned above: In addition, how to quickly and efficiently process the data relationship between the simulation devices for oil drill bit drilling mechanics data types under different formation pore pressure conditions and how to effectively manage the data of the simulation devices for oil drill bit drilling mechanics data types under different formation pore pressure conditions are also major problems that need to be urgently solved in the industry. Summary of the invention

[0005] In order to overcome the shortcomings and deficiencies of the prior art, the present invention provides a soft rock mechanical properties simulation data analysis method.

[0006] The technical solution adopted by the present invention is a method for analyzing soft rock mechanical properties simulation data provided by the present invention, the method comprising:

[0007] S100, collecting different geological structure information and soft rock component ratio information of the oil drill bit drilling system for simulation, and using K nearest neighbor algorithm to automatically train the oil drill bit drilling mechanics data types under all different formation pore pressure conditions in the different geological structure information and soft rock component ratio information of the oil drill bit drilling system to obtain the pressure value of the oil drill bit drilling data under different formation pore pressure conditions for simulation;

[0008] S200, using the pressure value of the oil drill bit drilling data under different formation pore pressure conditions to control the oil drill bit drilling mechanics data type control process under different formation pore pressure conditions using a K nearest neighbor algorithm to perform data collection;

[0009] S300, provides simulation analysis prompts for oil drill bit drilling parameters by setting algorithm parameters based on simulation software and types of oil drill bit drilling mechanics data under different formation pore pressure conditions;

[0010] S400, obtaining oil drill bit drilling parameter monitoring data and different drilling depth control quantity data under different formation pore pressure conditions, sending each group of oil drill bit drilling parameter monitoring data under different formation pore pressure conditions collected by the oil drill bit drilling parameter monitoring under different formation pore pressure conditions into the oil drill bit drilling mechanics data type simulation model under different formation pore pressure conditions, and obtaining the oil drill bit drilling mechanics data type simulation results under different formation pore pressure conditions;

[0011] S500, sending the simulation results of the types of drilling mechanics data of the oil drill bit under the different formation pore pressure conditions to the variable step-size Runge-Kutta algorithm, and solving the differential equations of the types of drilling mechanics data of the oil drill bit under the different formation pore pressure conditions simulated;

[0012] S600, simulate and judge whether there is any abnormality in the solution of the oil drill bit drilling mechanics data types under different formation pore pressure conditions solved by the differential equation.

[0013] Preferably, after the K-nearest neighbor algorithm is used to collect data for the oil drill bit drilling mechanics data type control process under different formation pore pressure conditions, the parameters of the K-nearest neighbor algorithm are dynamically optimized.

[0014] The present application also includes a method for determining whether to simulate and analyze data within a prompt for performing a simulation analysis of oil drill bit drilling parameters for oil drill bit drilling mechanics data types under different formation pore pressure conditions, the method comprising:

[0015] T100, the error interval between the simulation nodes of the types of oil drill bit drilling mechanics data under different formation pore pressure conditions in the previous group of oil drill bit drilling parameter monitoring data under different formation pore pressure conditions and the simulation nodes of the types of oil drill bit drilling mechanics data under different formation pore pressure conditions in the current group of oil drill bit drilling parameter monitoring data under different formation pore pressure conditions. If the error interval exceeds the threshold, it is determined that the types of oil drill bit drilling mechanics data under different formation pore pressure conditions need to be simulated and analyzed;

[0016] T200, if it is determined that the oil drill bit drilling mechanics data type under different formation pore pressure conditions is in the simulation analysis state, then the abnormal data in the oil drill bit drilling mechanics data type information under different formation pore pressure conditions is cleared and other oil drill bit drilling mechanics data types under different formation pore pressure conditions and oil drill bit drilling parameter monitoring data under different formation pore pressure conditions are processed;

[0017] T300, if the oil drill bit drilling mechanics data type under different formation pore pressure conditions is not running, then obtain the current time and simulate the stop collection time of the oil drill bit drilling mechanics data type under different formation pore pressure conditions, compare the stop collection time of the oil drill bit drilling mechanics data type under different formation pore pressure conditions with the set solution abnormality time threshold, if the stop collection time of the oil drill bit drilling mechanics data type under different formation pore pressure conditions exceeds the solution abnormality time threshold, it is judged that the oil drill bit drilling mechanics data type under different formation pore pressure conditions has a solution abnormality, if the stop collection time of the oil drill bit drilling mechanics data type under different formation pore pressure conditions does not exceed the solution abnormality time, then the current processing of the oil drill bit drilling mechanics data type under different formation pore pressure conditions is completed, and continue to process other simulated oil drill bit drilling parameter monitoring data under different formation pore pressure conditions.

[0018] Preferably, the threshold value adopts a dynamic form threshold value of R and G convolution operation to determine the type of oil drill bit drilling mechanics data under different formation pore pressure conditions that require simulation analysis data, wherein the letter R represents the response speed of the simulation analysis prompt of the oil drill bit drilling parameter simulation analysis, and the letter G represents the fluctuation function of the threshold value.

[0019] Preferably, if the differential equation of the previous group of oil drill bit drilling parameter monitoring data under different formation pore pressure conditions in the differential equation solution information is solved to a certain type of oil drill bit drilling mechanics data under different formation pore pressure conditions, then the platform sets a maximum number of missing groups, and does not judge that the oil drill bit drilling mechanics data type under the different formation pore pressure conditions is lost before the maximum number of missing groups is reached, and then the kernel function in the variable step-size Runge-Kutta algorithm is used to predict the oil drill bit drilling mechanics data type area under the different formation pore pressure conditions of the current group based on the position of the oil drill bit drilling mechanics data type area under the different formation pore pressure conditions in the previous group, and the predicted result is used as the oil drill bit drilling mechanics data type area under the different formation pore pressure conditions of the current group;

[0020] If the next group of oil drill bit drilling parameter monitoring data under different formation pore pressure conditions is simulated to the position of the oil drill bit drilling mechanics data type area under the different formation pore pressure conditions and the oil drill bit drilling mechanics data type area under the different formation pore pressure conditions of the current group matches, it is determined that the oil drill bit drilling mechanics data type under different formation pore pressure conditions is missing due to the simulation algorithm error;

[0021] If the maximum number of missing groups is reached, it is directly regarded as missing the type of oil drill bit drilling mechanics data under different formation pore pressure conditions, and the platform deletes the differential equation solution information of the type of oil drill bit drilling mechanics data under different formation pore pressure conditions;

[0022] If the oil drill bit drilling mechanics data type under the different formation pore pressure conditions reappears in the time period before the maximum number of missing groups is reached, it is determined that the oil drill bit drilling mechanics data type under the different formation pore pressure conditions is abnormally solved in a short time.

[0023] Preferably, the time for collecting the monitoring data of the drilling parameters of the oil drill under the different formation pore pressure conditions is set according to the monitoring requirements, and the number of groups collected per second is determined according to the control threshold.

[0024] The method of the present application is implemented by a petroleum drill bit drilling mechanics data type model simulation component under different formation pore pressure conditions, a petroleum drill bit drilling parameter monitoring data simulation component under different formation pore pressure conditions, and an abnormality solving optimization component, wherein:

[0025] The oil drill bit drilling mechanics data type model simulation component under different formation pore pressure conditions is used to simulate the oil drill bit drilling mechanics data types under different formation pore pressure conditions on the oil drill bit drilling parameter monitoring data under different formation pore pressure conditions and different drilling depth control quantity data collected by the oil drill bit drilling parameter monitoring data simulation component under different formation pore pressure conditions, and obtain simulation analysis of the oil drill bit drilling mechanics data types under different formation pore pressure conditions, oil drill bit drilling parameter simulation analysis prompts and simulation analysis oil drill bit drilling parameter simulation analysis prompt information;

[0026] The oil drill bit drilling parameter monitoring data simulation component under different formation pore pressure conditions is used to collect the oil drill bit drilling parameter monitoring data under different formation pore pressure conditions and the control amount data of different drilling depths, set the supervision area position and the oil drill bit drilling mechanics data under different formation pore pressure conditions obtained by the oil drill bit drilling mechanics data type model simulation component, prompt and simulate and analyze the oil drill bit drilling parameters, and simulate and analyze the prompt information of the analysis and match it with a specific simulation code before passing it to the abnormality solving optimization component;

[0027] The abnormality solving optimization component controls the output differential equation solver information of the oil drill bit drilling mechanics data under different formation pore pressure conditions that match the specific simulation code, searches for each of the differential equation solver information, determines whether the type of oil drill bit drilling mechanics data under the different formation pore pressure conditions is located within the supervision area according to the position of the supervision area, and optimizes the differential equation solver information again, and determines whether the type of oil drill bit drilling mechanics data under different formation pore pressure conditions should be issued a prompt signal according to the optimized differential equation solver information.

[0028] Preferably, the differential equation solver information includes: simulation codes of oil drill bit drilling mechanics data types under different formation pore pressure conditions, prompts for simulation analysis of oil drill bit drilling parameters for oil drill bit drilling mechanics data types under different formation pore pressure conditions, prompts for whether oil drill bit drilling mechanics data types under different formation pore pressure conditions enter the oil drill bit drilling mechanics data types under different formation pore pressure conditions for simulation analysis of oil drill bit drilling parameters, prompt time for oil drill bit drilling mechanics data types under different formation pore pressure conditions to enter the oil drill bit drilling mechanics data types under different formation pore pressure conditions for simulation analysis of oil drill bit drilling parameters, and whether prompt signals have been issued for oil drill bit drilling mechanics data types under different formation pore pressure conditions.

[0029] The present invention applies the K-nearest neighbor algorithm's simulation technology for oil drill bit drilling mechanics data types under different formation pore pressure conditions to the simulation of oil drill bit drilling mechanics data types under different formation pore pressure conditions. This method can accurately simulate the oil drill bit drilling mechanics data types under different formation pore pressure conditions from the oil drill bit drilling parameter monitoring data under different formation pore pressure conditions, and solve differential equations for the oil drill bit drilling mechanics data types under different formation pore pressure conditions. Then, through a series of logical judgments on the oil drill bit drilling mechanics data types with solution anomalies under different formation pore pressure conditions, the oil drill bit drilling mechanics data types under different formation pore pressure conditions are accurately and efficiently simulated and a prompt signal is generated, thereby realizing intelligent supervision of the oil drill bit drilling mechanics data types with solution anomalies under different formation pore pressure conditions. This greatly improves the efficiency of the staff and also saves a lot of manpower and material resources.

[0030] Model simulation component of oil drill bit drilling mechanics data types under different formation pore pressure conditions: The present invention uses the K nearest neighbor algorithm to collect data based on the oil drill bit drilling mechanics data type control process under different formation pore pressure conditions by controlling the oil drill bit drilling data pressure value, thereby ensuring the simulation accuracy of the oil drill bit drilling mechanics data types under different formation pore pressure conditions. The present invention also dynamically optimizes the parameters of the K nearest neighbor algorithm to ensure optimal performance under a limited budget;

[0031] Simulation component for monitoring data of oil drill bit drilling parameters under different formation pore pressure conditions: The present invention performs differential equation solving based on differential equation solving algorithm on the types of oil drill bit drilling mechanics data under different formation pore pressure conditions simulated, and maintains its individual structure, which is used to judge the status of the types of oil drill bit drilling mechanics data under different formation pore pressure conditions, and sets the differential equation solving failure threshold to avoid false alarms after abnormal solutions;

[0032] Solving abnormal optimization components: The present invention first determines whether the types of oil drill bit drilling mechanics data under different formation pore pressure conditions solved by the differential equation are within the supervision area, and proposes a variety of judgment methods for the types of oil drill bit drilling mechanics data under different formation pore pressure conditions that require simulation analysis data. By performing simulation analysis data judgment on the types of oil drill bit drilling mechanics data under different formation pore pressure conditions, the problem of false reporting of the types of oil drill bit drilling mechanics data under different formation pore pressure conditions in the simulation analysis data in the traditional method is avoided.

[0033] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0034] The present invention proposes a simulation data analysis method for soft rock mechanical properties. The present invention sets a simulation algorithm with a solution anomaly, and together with the core simulation algorithm, forms an intelligent simulation platform for solving anomalies in oil drill bit drilling mechanical data types under different formation pore pressure conditions; the method proposed in the present invention can effectively control the oil drill bit drilling parameters in the oil drill bit drilling system, thereby protecting the accuracy of oil drill bit drilling, assisting in building a safe and effective oil drill bit drilling system, and effectively simulating and analyzing the oil drill bit drilling data, thereby realizing effective management of the oil drill bit drilling mechanical data. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings:

[0036] Figure 1 This is the first flow chart of the soft rock mechanical property simulation data analysis method of the present invention;

[0037] Figure 2 This is the second flow chart of the soft rock mechanical properties simulation data analysis method of the present invention. DETAILED DESCRIPTION

[0038] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application may be combined with each other. The present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0039] like Figure 1 As shown, a method for analyzing simulation data of soft rock mechanical properties comprises:

[0040] S100, collecting different geological structure information and soft rock component ratio information of the oil drill bit drilling system for simulation, and using K nearest neighbor algorithm to automatically train the oil drill bit drilling mechanics data types under all different formation pore pressure conditions in the different geological structure information and soft rock component ratio information of the oil drill bit drilling system to obtain the pressure value of the oil drill bit drilling data under different formation pore pressure conditions for simulation;

[0041] S200, using the pressure value of the oil drill bit drilling data under different formation pore pressure conditions to control the oil drill bit drilling mechanics data type control process under different formation pore pressure conditions using a K nearest neighbor algorithm to perform data collection;

[0042] S300, provides simulation analysis prompts for oil drill bit drilling parameters by setting algorithm parameters based on simulation software and types of oil drill bit drilling mechanics data under different formation pore pressure conditions;

[0043] S400, obtaining oil drill bit drilling parameter monitoring data and different drilling depth control quantity data under different formation pore pressure conditions, sending each group of oil drill bit drilling parameter monitoring data under different formation pore pressure conditions collected by the oil drill bit drilling parameter monitoring under different formation pore pressure conditions into the oil drill bit drilling mechanics data type simulation model under different formation pore pressure conditions, and obtaining the oil drill bit drilling mechanics data type simulation results under different formation pore pressure conditions;

[0044] S500, sending the simulation results of the types of drilling mechanics data of the oil drill bit under the different formation pore pressure conditions to the variable step-size Runge-Kutta algorithm, and solving the differential equations of the types of drilling mechanics data of the oil drill bit under the different formation pore pressure conditions simulated;

[0045] S600, simulate and judge whether there is any abnormality in the solution of the oil drill bit drilling mechanics data types under different formation pore pressure conditions solved by the differential equation.

[0046] After using the K-nearest neighbor algorithm to collect data for the type control process of oil drill bit drilling mechanics data under different formation pore pressure conditions, the parameters of the K-nearest neighbor algorithm are dynamically optimized.

[0047] like Figure 2 As shown, the present application also includes a method for judging whether to simulate and analyze data within the oil drill bit drilling mechanics data type under different formation pore pressure conditions and the oil drill bit drilling mechanics data type under different formation pore pressure conditions for oil drill bit drilling parameter simulation analysis prompts, the method comprising:

[0048] T100, the error interval between the simulation nodes of the types of oil drill bit drilling mechanics data under different formation pore pressure conditions in the previous group of oil drill bit drilling parameter monitoring data under different formation pore pressure conditions and the simulation nodes of the types of oil drill bit drilling mechanics data under different formation pore pressure conditions in the current group of oil drill bit drilling parameter monitoring data under different formation pore pressure conditions. If the error interval exceeds the threshold, it is determined that the types of oil drill bit drilling mechanics data under different formation pore pressure conditions need to be simulated and analyzed;

[0049] T200, if it is determined that the oil drill bit drilling mechanics data type under different formation pore pressure conditions is in the simulation analysis state, then the abnormal data in the oil drill bit drilling mechanics data type information under different formation pore pressure conditions is cleared and other oil drill bit drilling mechanics data types under different formation pore pressure conditions and oil drill bit drilling parameter monitoring data under different formation pore pressure conditions are processed;

[0050] T300, if the oil drill bit drilling mechanics data type under different formation pore pressure conditions is not running, then obtain the current time and simulate the stop collection time of the oil drill bit drilling mechanics data type under different formation pore pressure conditions, compare the stop collection time of the oil drill bit drilling mechanics data type under different formation pore pressure conditions with the set solution abnormality time threshold, if the stop collection time of the oil drill bit drilling mechanics data type under different formation pore pressure conditions exceeds the solution abnormality time threshold, it is judged that the oil drill bit drilling mechanics data type under different formation pore pressure conditions has a solution abnormality, if the stop collection time of the oil drill bit drilling mechanics data type under different formation pore pressure conditions does not exceed the solution abnormality time, then the current processing of the oil drill bit drilling mechanics data type under different formation pore pressure conditions is completed, and continue to process other simulated oil drill bit drilling parameter monitoring data under different formation pore pressure conditions.

[0051] The threshold uses a dynamic form threshold of the convolution operation of R and G to determine the type of oil drill bit drilling mechanics data under different formation pore pressure conditions that require simulation analysis data, where the letter R represents the response speed of the simulation analysis prompt of the oil drill bit drilling parameter simulation analysis, and the letter G represents the fluctuation function of the threshold.

[0052] If the differential equation of the previous group of oil drill bit drilling parameter monitoring data under different formation pore pressure conditions in the differential equation solution information is solved to a certain type of oil drill bit drilling mechanics data under different formation pore pressure conditions, and the differential equation in the current group is not solved to the type of oil drill bit drilling mechanics data under the said different formation pore pressure conditions, then the platform sets a maximum number of missing groups. Before the maximum number of missing groups is reached, it is not judged that the type of oil drill bit drilling mechanics data under the said different formation pore pressure conditions is lost. Then, the kernel function in the variable step-size Runge-Kutta algorithm is used to predict the type area of ​​oil drill bit drilling mechanics data under the said different formation pore pressure conditions in the current group based on the position of the type area of ​​oil drill bit drilling mechanics data under the said different formation pore pressure conditions in the previous group, and the predicted result is used as the type area of ​​oil drill bit drilling mechanics data under the said different formation pore pressure conditions in the current group;

[0053] If the next group of oil drill bit drilling parameter monitoring data under different formation pore pressure conditions is simulated to the position of the oil drill bit drilling mechanics data type area under the different formation pore pressure conditions and the oil drill bit drilling mechanics data type area under the different formation pore pressure conditions of the current group matches, it is determined that the oil drill bit drilling mechanics data type under different formation pore pressure conditions is missing due to the simulation algorithm error;

[0054] If the maximum number of missing groups is reached, it is directly regarded as missing the type of oil drill bit drilling mechanics data under different formation pore pressure conditions, and the platform deletes the differential equation solution information of the type of oil drill bit drilling mechanics data under different formation pore pressure conditions;

[0055] If the oil drill bit drilling mechanics data type under the different formation pore pressure conditions reappears in the time period before the maximum number of missing groups is reached, it is determined that the oil drill bit drilling mechanics data type under the different formation pore pressure conditions is abnormally solved in a short time.

[0056] The time for collecting the monitoring data of the drilling parameters of the oil drill under the different formation pore pressure conditions is set according to the monitoring requirements, and the number of groups collected per second is determined according to the control threshold.

[0057] The soft rock mechanical properties simulation data analysis method of this application is implemented through the following components:

[0058] The oil drill bit drilling mechanics data type model simulation component under different formation pore pressure conditions first collects data for simulation based on actual scenarios. After obtaining the data, the K-nearest neighbor algorithm is used to automatically train the oil drill bit drilling mechanics data types under all different formation pore pressure conditions in the oil drill bit drilling system's different geological structure information and soft rock component ratio information, and the pressure value of the oil drill bit drilling data under different formation pore pressure conditions for simulation is obtained.

[0059] In order to better ensure the simulation effect, the present invention can greatly increase the amount of simulation data by controlling the oil drill bit drilling data pressure value under the simulation of different formation pore pressure conditions using data enhancement methods such as translation, flipping, and scaling.

[0060] Then, by simulating the pressure value of the oil drill bit drilling data under different formation pore pressure conditions, the K nearest neighbor algorithm is used to collect data based on the type control process of the oil drill bit drilling mechanics data under different formation pore pressure conditions to ensure the accuracy of the model.

[0061] After obtaining the simulated model, the traditional method generally directly deploys and utilizes the simulated original model in combination with the business program. This method not only has a slow reasoning speed but also consumes a lot of hardware resources.

[0062] In order to ensure the real-time simulation of oil drill bit drilling mechanics data types under different formation pore pressure conditions in the business, the original model in the present invention uses the particle swarm algorithm to optimize the model speed, position optimization, weight quantization and other operations to optimize the model reasoning throughput, and performs forward reasoning to accelerate the reasoning.

[0063] The data simulation component for monitoring oil drill bit drilling parameters under different formation pore pressure conditions, firstly, the intelligent simulation platform of the present invention sets the algorithm parameters based on the simulation software, and the cloud page displays in real time the screen for setting the oil drill bit drilling parameter monitoring under different formation pore pressure conditions. The user can use the mouse to draw the types of oil drill bit drilling mechanics data under different formation pore pressure conditions in the screen to perform oil drill bit drilling parameter simulation analysis prompts. When the user finishes drawing, the algorithm settings will be sent to the algorithm server through the network.

[0064] After the algorithm is controlled to the setting, it will pull the real-time data of the oil drill bit drilling parameter monitoring under different formation pore pressure conditions according to the specified different drilling depth control flow address, and send each set of oil drill bit drilling parameter monitoring data under different formation pore pressure conditions into the simulated oil drill bit drilling mechanics data type simulation model under different formation pore pressure conditions to obtain the simulation results of the oil drill bit drilling mechanics data types under different formation pore pressure conditions.

[0065] Then, the simulation results of the types of oil drill bit drilling mechanics data under different formation pore pressure conditions are sent to the variable step-size Runge-Kutta algorithm to solve the differential equations of the types of oil drill bit drilling mechanics data under different formation pore pressure conditions.

[0066] The advantage of solving differential equations is that the types of oil drill bit drilling mechanics data under the same and different formation pore pressure conditions in the time series are matched and assigned the same simulation code, avoiding the problem of continuous prompt signals of the same oil drill bit drilling parameters when continuously simulating.

[0067] Solve the abnormal optimization component, according to the differential equation solving information of the differential equation solver of the oil drill bit drilling parameter monitoring data simulation component under different formation pore pressure conditions, traverse all the oil drill bit drilling mechanics data types under different formation pore pressure conditions solved by the differential equation, if it is the oil drill bit drilling mechanics data type under different formation pore pressure conditions solved by the new differential equation, then initialize its information;

[0068] If the previous platform has solved the differential equation to the type of oil drill bit drilling mechanics data under different formation pore pressure conditions, and the current group has solved the differential equation to the type of oil drill bit drilling mechanics data under different formation pore pressure conditions, first determine whether it is within the oil drill bit drilling mechanics data type under different formation pore pressure conditions for the oil drill bit drilling parameter simulation analysis prompt, and use the oil drill bit drilling mechanics data type under different formation pore pressure conditions for the oil drill bit drilling parameter simulation analysis prompt time and frequency and simulation analysis oil drill bit drilling parameter simulation analysis prompt signal to determine whether the oil drill bit drilling mechanics data type under different formation pore pressure conditions is within the oil drill bit drilling mechanics data type under different formation pore pressure conditions for the oil drill bit drilling parameter simulation analysis prompt.

[0069] The specific method is: firstly, obtaining the time and frequency of the simulation analysis prompt of the oil drill bit drilling parameter simulation analysis and the simulation analysis prompt signal of the oil drill bit drilling parameter simulation analysis;

[0070] If the oil drill bit drilling mechanics data types under different formation pore pressure conditions are simulated and analyzed in the oil drill bit drilling parameter simulation prompt, it is judged that the oil drill bit drilling mechanics data types under different formation pore pressure conditions have abnormal solutions;

[0071] If only part of the data is located in the prompt for the simulation analysis of oil drill bit drilling parameters for the oil drill bit drilling mechanics data types under different formation pore pressure conditions, then it is judged whether the location of the oil drill bit drilling mechanics data types under different formation pore pressure conditions is located in the prompt for the simulation analysis of oil drill bit drilling parameters for the oil drill bit drilling mechanics data types under different formation pore pressure conditions. If it is located, it is judged that there is a solution abnormality in the oil drill bit drilling mechanics data types under different formation pore pressure conditions; the rest are deemed to have no solution abnormality.

[0072] If the type of oil drill bit drilling mechanics data under different formation pore pressure conditions is not within the prompt for oil drill bit drilling mechanics data type under different formation pore pressure conditions for oil drill bit drilling parameter simulation analysis, the processing of the current type of oil drill bit drilling mechanics data under different formation pore pressure conditions is completed, and other simulations of oil drill bit drilling parameter monitoring data under different formation pore pressure conditions continue to be processed. When all types of oil drill bit drilling mechanics data under different formation pore pressure conditions are traversed, the processing of the current group is completed, and the next group is obtained.

[0073] If the types of oil drill bit drilling mechanics data under different formation pore pressure conditions are located in the prompt for simulation analysis of oil drill bit drilling parameters under different formation pore pressure conditions, the present invention adopts a method for judging whether the types of oil drill bit drilling mechanics data under different formation pore pressure conditions are simulated analysis data, so as to avoid the problem that the types of oil drill bit drilling mechanics data under different formation pore pressure conditions are always in the prompt for simulation analysis of oil drill bit drilling parameters under different formation pore pressure conditions due to traffic jams or other reasons during slow driving over a large area and are mistakenly considered to have a solution abnormality and a prompt signal.

[0074] The specific method is as follows: (1) simulating the error interval between the simulation nodes of the oil drill bit drilling mechanics data types under different formation pore pressure conditions in the previous group of oil drill bit drilling parameter monitoring data and the simulation nodes of the oil drill bit drilling mechanics data types under different formation pore pressure conditions in the current group; if the error interval exceeds a certain threshold, it is determined that the oil drill bit drilling mechanics data types under different formation pore pressure conditions need to be simulated and analyzed;

[0075] (2) Due to the different error intervals of the types of drilling mechanics data of oil drill bits under different formation pore pressure conditions and the different error intervals of the monitoring of drilling parameters of oil drill bits under different formation pore pressure conditions, the error intervals in the monitoring data of drilling parameters of oil drill bits under different formation pore pressure conditions are different. The Uox sizes simulated by the types of drilling mechanics data of oil drill bits under different formation pore pressure conditions at different distances will be very different; for example, the actual road surface error intervals corresponding to the 10 error intervals far away and the 10 error intervals near are different.

[0076] Therefore, if the method in step (1) uses a single threshold as a judgment condition, it will result in different simulation analysis data standards for judging the types of oil drill bit drilling mechanics data under different formation pore pressure conditions at different distances.

[0077] The present invention proposes to use the dynamic threshold as the convolution operation form of R and G to judge whether the type of oil drill bit drilling mechanics data under different formation pore pressure conditions is simulation analysis data;

[0078] The effect of setting a dynamic threshold is that when the simulation analysis prompts a larger value for the oil drill bit drilling parameter simulation analysis, the corresponding error interval threshold is larger, and when the simulation analysis prompts a smaller value for the oil drill bit drilling parameter simulation analysis, the corresponding error interval threshold is smaller, thereby making it more accurate to monitor the oil drill bit drilling parameters under different formation pore pressure conditions at different distances within the error interval and to perform simulation analysis and judgment on the types of oil drill bit drilling mechanics data under different formation pore pressure conditions.

[0079] If the type of oil drill bit drilling mechanics data under different formation pore pressure conditions is being simulated and analyzed, the abnormal data in the oil drill bit drilling mechanics data type information under different formation pore pressure conditions is cleared, and other simulations of oil drill bit drilling parameter monitoring data under different formation pore pressure conditions are continued;

[0080] If the type of oil drill bit drilling mechanics data under different formation pore pressure conditions is not being simulated and analyzed, the current time is obtained and the stop collection time of the oil drill bit drilling mechanics data type under different formation pore pressure conditions is simulated, and the stop collection time of the oil drill bit drilling mechanics data type under different formation pore pressure conditions is compared with the threshold value of the time with solution abnormality. If the threshold value of the time with solution abnormality is exceeded, it is determined that the oil drill bit drilling mechanics data type under different formation pore pressure conditions has a solution abnormality, and the oil drill bit drilling mechanics data type information under different formation pore pressure conditions is sent to the cloud through the network. After the cloud control receives the prompt signal message, the prompt signal information will be displayed on the page; if it does not exceed the solution abnormality time, the processing of the oil drill bit drilling mechanics data type under the current different formation pore pressure conditions is completed, and other simulations of the oil drill bit drilling parameter monitoring data under different formation pore pressure conditions continue to be processed.

[0081] If the previous set of differential equations in the differential equation solution information solves a certain oil drill bit drilling parameter, but the differential equations in the current set are not solved, the following three situations will occur:

[0082] 1. The simulation algorithm failed to detect the types of oil drill bit drilling mechanics data under different formation pore pressure conditions;

[0083] 2. The types of oil drill bit drilling mechanics data under different formation pore pressure conditions are beyond the solution range;

[0084] 3. There are solution anomalies. Other objects solve the types of oil drill drilling mechanics data under different formation pore pressure conditions abnormally, resulting in the simulation algorithm being unable to simulate the types of oil drill drilling mechanics data under different formation pore pressure conditions.

[0085] In view of the above situation, the specific processing method of the present invention is as follows: combining the above three possible situations, setting a maximum number of missing groups, and not judging the loss of the oil drill bit drilling mechanics data type under different formation pore pressure conditions before reaching the maximum number of missing groups. The kernel function in the variable step-size Runge-Kutta algorithm is used to predict the oil drill bit drilling mechanics data type area under different formation pore pressure conditions of the current group based on the position of the oil drill bit drilling mechanics data type area under different formation pore pressure conditions of the previous group, and the predicted result is used as the oil drill bit drilling mechanics data type area under different formation pore pressure conditions of the current group, but the differential equation solution state is still the differential equation not solved.

[0086] For the first case, if the simulation algorithm fails to detect the oil drill bit drilling mechanics data type under different formation pore pressure conditions due to an error, then when the next group of oil drill bit drilling mechanics data type areas under different formation pore pressure conditions are simulated, the oil drill bit drilling mechanics data type areas under different formation pore pressure conditions obtained by the differential equation solving algorithm will match the oil drill bit drilling mechanics data type areas under different formation pore pressure conditions of the current group, avoiding the problem of repeated prompt signals caused by unstable simulation algorithms;

[0087] For the second case, when the maximum number of missing groups is reached, the algorithm regards that the types of oil drill bit drilling mechanics data under the current different formation pore pressure conditions are missing, and deletes the differential equation solution information of the types of oil drill bit drilling mechanics data under the different formation pore pressure conditions;

[0088] For the third case, if the anomaly is solved in a short time, after the oil drill bit drilling mechanics data type reappears under different formation pore pressure conditions, the differential equation solving algorithm can still match the oil drill bit drilling mechanics data type area under the previous different formation pore pressure conditions with the oil drill bit drilling mechanics data type area under different formation pore pressure conditions after solving the anomaly, and simulate the oil drill bit drilling mechanics data type under the same different formation pore pressure conditions, avoiding the problem of repeated prompt signals.

[0089] The maximum number of missing groups is recommended to be set to the time for collecting oil drill bit drilling parameter monitoring data under different formation pore pressure conditions. The time length is set according to the monitoring requirements, and the number of groups collected per second is determined by the control threshold.

[0090] The specific oil drill bit drilling mechanics data type model simulation component under different formation pore pressure conditions, the oil drill bit drilling parameter monitoring data simulation component under different formation pore pressure conditions and the abnormal optimization component communicate with each other through the following contents:

[0091] The oil drill bit drilling mechanics data type model simulation component under different formation pore pressure conditions generates a model file after simulation and acceleration;

[0092] The simulation component of the oil drill bit drilling parameter monitoring data under different formation pore pressure conditions first obtains the cloud settings through network communication; the cloud settings specifically include: the location of the oil drill bit drilling parameter monitoring supervision area under different formation pore pressure conditions;

[0093] After the setting is completed, the simulation component for monitoring data of oil drill bit drilling parameters under different formation pore pressure conditions loads the model file of the simulation component for the types of oil drill bit drilling mechanics data under different formation pore pressure conditions, and simulates the types of oil drill bit drilling mechanics data under different formation pore pressure conditions for the oil drill bit drilling parameter monitoring data and different drilling depth control data, and obtains the simulation analysis of the types of oil drill bit drilling mechanics data under different formation pore pressure conditions, the simulation analysis prompts of oil drill bit drilling parameters, and the simulation analysis prompts of oil drill bit drilling parameters;

[0094] Then, the simulation analysis prompts of the drilling parameters of the oil drill bit are sent to the variable step-size Runge-Kutta algorithm, and after matching the specific simulation code for each simulation analysis prompt of the drilling parameters of the oil drill bit, the prompts are passed into the abnormal optimization component for solving the differential equation solver information, wherein the differential equation solver information includes the simulation code of the drilling mechanics data type of the oil drill bit under different formation pore pressure conditions, the drilling mechanics data types of the oil drill bit under different formation pore pressure conditions for the simulation analysis prompts of the oil drill bit drilling parameters, whether the drilling mechanics data types of the oil drill bit under different formation pore pressure conditions enter the drilling mechanics data types of the oil drill bit under different formation pore pressure conditions for the simulation analysis prompts of the oil drill bit drilling parameters, the drilling mechanics data types of the oil drill bit under different formation pore pressure conditions enter the drilling mechanics data types of the oil drill bit under different formation pore pressure conditions for the simulation analysis prompts of the oil drill bit drilling parameters, and whether the drilling mechanics data types of the oil drill bit under different formation pore pressure conditions have been issued prompt signals;

[0095] The abnormality solving optimization component traverses each differential equation solver information, determines whether the type of oil drill bit drilling mechanics data under different formation pore pressure conditions is located within the supervision area according to the position of the supervision area, optimizes the differential equation solver information, and determines whether the type of oil drill bit drilling mechanics data under different formation pore pressure conditions should issue a prompt signal according to the differential equation solver information.

[0096] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", "connect", and "fix" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood by specific circumstances.

[0097] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various equivalent changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for analyzing simulation data of mechanical properties of soft rock, characterized in that: The method includes: S100, collecting different geological structure information and soft rock component ratio information of the oil drill bit drilling system for simulation, and using K nearest neighbor algorithm to automatically train the oil drill bit drilling mechanics data types under all different formation pore pressure conditions in the different geological structure information and soft rock component ratio information of the oil drill bit drilling system to obtain the pressure value of the oil drill bit drilling data under different formation pore pressure conditions for simulation; S200, using the pressure value of the oil drill bit drilling data under different formation pore pressure conditions to control the oil drill bit drilling mechanics data type control process under different formation pore pressure conditions using a K nearest neighbor algorithm to perform data collection; S300, provides simulation analysis prompts for oil drill bit drilling parameters by setting algorithm parameters based on simulation software and types of oil drill bit drilling mechanics data under different formation pore pressure conditions; S400, obtaining oil drill bit drilling parameter monitoring data and different drilling depth control quantity data under different formation pore pressure conditions, sending each group of oil drill bit drilling parameter monitoring data under different formation pore pressure conditions collected by the oil drill bit drilling parameter monitoring under different formation pore pressure conditions into the oil drill bit drilling mechanics data type simulation model under different formation pore pressure conditions, and obtaining the oil drill bit drilling mechanics data type simulation results under different formation pore pressure conditions; S500, sending the simulation results of the types of drilling mechanics data of the oil drill bit under the different formation pore pressure conditions to the variable step-size Runge-Kutta algorithm, and solving the differential equations of the types of drilling mechanics data of the oil drill bit under the different formation pore pressure conditions simulated; S600, simulating and determining whether there is any abnormality in the type of drilling mechanics data of the oil drill bit under the different formation pore pressure conditions solved by the differential equation; After using the K-nearest neighbor algorithm to collect data for the type control process of oil drill bit drilling mechanics data under different formation pore pressure conditions, the parameters of the K-nearest neighbor algorithm are dynamically optimized; The simulation software operation includes: T100, the error interval between the simulation nodes of the types of oil drill bit drilling mechanics data under different formation pore pressure conditions in the previous group of oil drill bit drilling parameter monitoring data under different formation pore pressure conditions and the simulation nodes of the types of oil drill bit drilling mechanics data under different formation pore pressure conditions in the current group of oil drill bit drilling parameter monitoring data under different formation pore pressure conditions. If the error interval exceeds the threshold, it is determined that the types of oil drill bit drilling mechanics data under different formation pore pressure conditions need simulation analysis; T200, if it is determined that the oil drill bit drilling mechanics data type under different formation pore pressure conditions is in the simulation analysis state, then the abnormal data in the oil drill bit drilling mechanics data type information under different formation pore pressure conditions is cleared and other oil drill bit drilling mechanics data types under different formation pore pressure conditions and oil drill bit drilling parameter monitoring data under different formation pore pressure conditions are processed; T300, if the oil drill bit drilling mechanics data under different formation pore pressure conditions is not running, then the current time is obtained and the stop acquisition time of the oil drill bit drilling mechanics data types under different formation pore pressure conditions is simulated, and the stop acquisition time of the oil drill bit drilling mechanics data types under different formation pore pressure conditions is compared with the set solution abnormality time threshold. If the stop acquisition time of the oil drill bit drilling mechanics data types under different formation pore pressure conditions exceeds the solution abnormality time threshold, it is determined that the oil drill bit drilling mechanics data types under different formation pore pressure conditions have solution abnormalities. If the stop acquisition time of the oil drill bit drilling mechanics data types under different formation pore pressure conditions does not exceed the solution abnormality time, the current processing of the oil drill bit drilling mechanics data types under different formation pore pressure conditions is completed, and other simulations of oil drill bit drilling parameter monitoring data under different formation pore pressure conditions are continued to be processed; The threshold value uses a dynamic form threshold value of the convolution operation of R and G to determine the type of oil drill bit drilling mechanics data under different formation pore pressure conditions and needs to be simulated and analyzed, wherein the letter R in the formula represents the response speed of the simulation analysis prompt of the oil drill bit drilling parameter simulation analysis, and the letter G represents the fluctuation function of the threshold value; If the differential equation of the previous group of oil drill bit drilling parameter monitoring data under different formation pore pressure conditions in the differential equation solution information is solved to a certain type of oil drill bit drilling mechanics data under different formation pore pressure conditions, and the differential equation in the current group is not solved to the type of oil drill bit drilling mechanics data under the said different formation pore pressure conditions, then the platform sets a maximum number of missing groups. Before the maximum number of missing groups is reached, it is not judged that the type of oil drill bit drilling mechanics data under the said different formation pore pressure conditions is lost. Then, the kernel function in the variable step-size Runge-Kutta algorithm is used to predict the type area of ​​oil drill bit drilling mechanics data under the said different formation pore pressure conditions in the current group based on the position of the type area of ​​oil drill bit drilling mechanics data under the said different formation pore pressure conditions in the previous group, and the predicted result is used as the type area of ​​oil drill bit drilling mechanics data under the said different formation pore pressure conditions in the current group; If the next set of oil drill bit drilling parameter monitoring data under different formation pore pressure conditions is simulated to the position of the oil drill bit drilling mechanics data type area under the said different formation pore pressure conditions and the oil drill bit drilling mechanics data type area under the said current set of oil drill bit drilling mechanics data type areas under different formation pore pressure conditions match, it is judged that the oil drill bit drilling mechanics data types under different formation pore pressure conditions are missing due to the simulation algorithm error; if the maximum number of missing groups is reached, it is directly regarded as the oil drill bit drilling mechanics data types under the said different formation pore pressure conditions are missing, and the platform deletes the differential equation solution information of the oil drill bit drilling mechanics data types under these different formation pore pressure conditions; if the oil drill bit drilling mechanics data types under the said different formation pore pressure conditions reappear in the time period when the maximum number of missing groups is not reached, it is judged that the oil drill bit drilling mechanics data types under the said different formation pore pressure conditions are abnormally solved in a short time.

2. The soft rock mechanical properties simulation data analysis method according to claim 1, characterized in that: The time for collecting the monitoring data of the drilling parameters of the oil drill under the different formation pore pressure conditions is set according to the monitoring requirements, and the number of groups collected per second is determined according to the control threshold.

3. The soft rock mechanical properties simulation data analysis method according to claim 1, characterized in that: The method is realized through the oil drill bit drilling mechanics data type model simulation component under different formation pore pressure conditions, the oil drill bit drilling parameter monitoring data simulation component under different formation pore pressure conditions and the abnormality solving optimization component. The oil drill bit drilling mechanics data type model simulation component under different formation pore pressure conditions is used to simulate the oil drill bit drilling mechanics data type under different formation pore pressure conditions for the oil drill bit drilling parameter monitoring data under different formation pore pressure conditions and the different drilling depth control quantity data collected by the oil drill bit drilling parameter monitoring data simulation component under different formation pore pressure conditions, and obtain oil drill bit drilling parameter simulation analysis prompt information; The oil drill bit drilling parameter monitoring data simulation component under different formation pore pressure conditions is used to collect the oil drill bit drilling parameter monitoring data under different formation pore pressure conditions and the control amount data of different drilling depths, set the supervision area position and the oil drill bit drilling mechanics data under different formation pore pressure conditions obtained by the oil drill bit drilling mechanics data type model simulation component, prompt and simulate and analyze the oil drill bit drilling parameters, and simulate and analyze the prompt information of the analysis and match it with a specific simulation code before passing it to the abnormality solving optimization component; The abnormal solution optimization component is used to control the output differential equation solver information of the oil drill bit drilling mechanics data under different formation pore pressure conditions that match the specific simulation code, search for each differential equation solver information, and judge whether the type of oil drill bit drilling mechanics data under the different formation pore pressure conditions is located in the supervision area according to the position of the supervision area, and optimize the differential equation solver information again, and judge whether the type of oil drill bit drilling mechanics data under different formation pore pressure conditions should be issued a prompt signal according to the optimized differential equation solver information.

4. The soft rock mechanical properties simulation data analysis method according to claim 3 is characterized in that: The differential equation solver information includes: simulation codes of oil drill bit drilling mechanics data types under different formation pore pressure conditions, prompts for simulation analysis of oil drill bit drilling parameters for oil drill bit drilling mechanics data types under different formation pore pressure conditions, whether the oil drill bit drilling mechanics data types under different formation pore pressure conditions enter the oil drill bit drilling mechanics data types under different formation pore pressure conditions for simulation analysis of oil drill bit drilling parameters, the time when the oil drill bit drilling mechanics data types under different formation pore pressure conditions enter the oil drill bit drilling mechanics data types under different formation pore pressure conditions for simulation analysis of oil drill bit drilling parameters, and whether prompt signals have been issued for the oil drill bit drilling mechanics data types under different formation pore pressure conditions.

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