CN117471922A - Intelligent control method and system for oil casing electric punching equipment - Google Patents
Intelligent control method and system for oil casing electric punching equipment Download PDFInfo
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Abstract
The application provides an intelligent control method and system of oil casing electric punching equipment, and relates to the technical field of intelligent control, wherein the method comprises the following steps: receiving basic information of an oil casing to be perforated; configuring a constraint drilling diameter and a constraint drilling depth; performing bit control optimizing to generate bit expected rotation speed time sequence information and bit expected feeding speed time sequence information; performing analysis of the liquid pressurization reverse mapping channel to generate liquid pressurization optimal control parameters, wherein the liquid pressurization optimal control parameters comprise recommended pressurization liquid flow time sequence information, recommended pressurization duration time sequence information and recommended pressurization liquid temperature time sequence information; the intelligent control of the electric punching equipment is executed, the technical problems that the aperture and the depth are difficult to stably control and the drilling defect is large due to the fact that subjective control is usually carried out by combining vision in the prior art are solved, the accurate and stable control of the aperture and the depth is achieved, and therefore the technical effects of punching control precision and accuracy are improved.
Description
Technical Field
The application relates to the technical field of intelligent control, in particular to an intelligent control method and system of oil casing electric punching equipment.
Background
In the petroleum industry, an oil casing is an important device for protecting and supporting the oil well casing, and the drilling of the oil casing can meet various requirements, for example, data such as underground pressure, temperature and the like can be transmitted to a ground control system, chemical agents such as water shutoff agents, blocking removal agents and the like can be injected into the underground, underground formation pressure can be balanced, and the casing is prevented from being broken or deformed due to overlarge formation pressure.
An oil casing electric perforating device is a mechanical device for perforating oil casings. With the development of the petroleum industry, the need for oil casing perforating equipment is also increasing. However, conventional perforation methods often combine vision with subjective control, resulting in difficulty in stable control of pore size and depth, and large defects in drilling.
Disclosure of Invention
The application provides an intelligent control method and system of an oil casing electric punching device, which are used for solving the technical problems in the prior art that the aperture and the depth are difficult to stably control and the drilling defect is large because subjective control is usually carried out by combining vision.
According to a first aspect of the present application, there is provided an intelligent control method of an oil casing electric punching device, comprising: receiving basic information of an oil casing to be perforated, wherein the basic information of the oil casing to be perforated comprises information of the wall thickness of the oil casing, information of the diameter of the oil casing and information of the material of the oil casing; configuring a constraint drilling diameter and a constraint drilling depth based on a drilling constraint table according to the oil casing wall thickness information and the oil casing diameter information; performing drill bit control optimizing on the constraint drilling diameter and the constraint drilling depth through the oil casing material information to generate drill bit expected rotation speed time sequence information and drill bit expected feeding speed time sequence information; according to the time sequence information of the expected rotation speed of the drill bit and the time sequence information of the expected feeding speed of the drill bit, analyzing a liquid pressurization reverse mapping channel to generate liquid pressurization optimization control parameters, wherein the liquid pressurization optimization control parameters comprise recommended pressurization liquid flow time sequence information, recommended pressurization duration time sequence information and recommended pressurization liquid temperature time sequence information; and performing intelligent control of the electric punching equipment according to the recommended pressurized liquid flow time sequence information, the recommended pressurized time sequence information and the recommended pressurized liquid temperature time sequence information.
According to a second aspect of the present application, there is provided an intelligent control system for an oil casing electric perforating apparatus, comprising: the base information receiving module is used for receiving base information of the oil casing to be perforated, wherein the base information of the oil casing to be perforated comprises oil casing wall thickness information, oil casing diameter information and oil casing material information; the drilling parameter configuration module is used for configuring constraint drilling diameter and constraint drilling depth based on a drilling constraint table according to the oil casing wall thickness information and the oil casing diameter information; the drill bit control optimizing module is used for performing drill bit control optimizing through the oil casing material information, the constraint drilling diameter and the constraint drilling depth, and generating drill bit expected rotation speed time sequence information and drill bit expected feeding speed time sequence information; the liquid pressurization reverse analysis module is used for executing analysis of a liquid pressurization reverse mapping channel according to the time sequence information of the expected rotation speed of the drill bit and the time sequence information of the expected feeding speed of the drill bit to generate liquid pressurization optimal control parameters, wherein the liquid pressurization optimal control parameters comprise recommended pressurization liquid flow time sequence information, recommended pressurization duration time sequence information and recommended pressurization liquid temperature time sequence information; the intelligent control module is used for performing intelligent control of the electric punching equipment according to the recommended pressurized liquid flow time sequence information, the recommended pressurized time length time sequence information and the recommended pressurized liquid temperature time sequence information.
According to one or more of the schemes adopted by the application, the following beneficial effects can be achieved:
receiving basic information of an oil casing to be perforated, wherein the basic information of the oil casing to be perforated comprises information of the wall thickness of the oil casing, information of the diameter of the oil casing and information of the material of the oil casing; configuring constraint drilling diameters and constraint drilling depths based on a perforation constraint table according to the oil casing wall thickness information and the oil casing diameter information; performing drill bit control optimizing by restraining the drilling diameter and the drilling depth through oil casing material information, and generating drill bit expected rotation speed time sequence information and drill bit expected feeding speed time sequence information; performing analysis of the liquid pressurization reverse mapping channel according to the bit expected rotation speed time sequence information and the bit expected feeding speed time sequence information, and generating liquid pressurization optimization control parameters, wherein the liquid pressurization optimization control parameters comprise recommended pressurization liquid flow time sequence information, recommended pressurization duration time sequence information and recommended pressurization liquid temperature time sequence information; and performing intelligent control of the electric punching device according to the recommended pressurized liquid flow time sequence information, the recommended pressurized time sequence information and the recommended pressurized liquid temperature time sequence information. According to the method, drill bit control optimizing is conducted on oil casing material information, the drilling diameter and the drilling depth are restrained, drill bit expected rotation speed time sequence information and drill bit expected feeding speed time sequence information are generated, further analysis of a liquid pressurizing reverse mapping channel is conducted according to the drill bit expected rotation speed time sequence information and the drill bit expected feeding speed time sequence information, liquid pressurizing optimal control parameters are generated, and accurate and stable control of the aperture and the depth is achieved, so that the technical effects of drilling control precision and accuracy are improved.
Drawings
In order to more clearly illustrate the technical solutions of the present application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. The accompanying drawings, which form a part hereof, illustrate embodiments of the present application and, together with the description, serve to explain the present application and not to limit the application unduly, and to enable a person skilled in the art to make and use other drawings without the benefit of the present inventive subject matter.
Fig. 1 is a schematic flow chart of an intelligent control method of an oil casing electric punching device according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of an intelligent control system of an oil casing electric punching device according to an embodiment of the present application.
Reference numerals illustrate: the system comprises a basic information receiving module 11, a drilling parameter configuration module 12, a drill bit control optimizing module 13, a liquid pressurization reverse analysis module 14 and an intelligent control module 15.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, exemplary embodiments of the present application will be described in detail below with reference to the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application and not all of the embodiments of the present application, and it should be understood that the present application is not limited by the example embodiments described herein.
The terminology used in the description is for the purpose of describing embodiments only and is not intended to be limiting of the application. As used in this specification, the singular terms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. The terms "comprises" and/or "comprising," when used in this specification, specify the presence of steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other steps, operations, elements, components, and/or groups thereof.
Unless defined otherwise, all terms (including technical and scientific terms) used in this specification should have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. Terms, such as those defined in commonly used dictionaries, should not be interpreted in an idealized or overly formal sense unless expressly so defined herein. Like numbers refer to like elements throughout.
It should be noted that, the user information (including, but not limited to, user equipment information, user personal information, etc.) and the data (including, but not limited to, data for presentation, analyzed data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party.
Example 1
Fig. 1 is a diagram of an intelligent control method of an oil casing electric punching device according to an embodiment of the present application, where the method includes:
receiving basic information of an oil casing to be perforated, wherein the basic information of the oil casing to be perforated comprises information of the wall thickness of the oil casing, information of the diameter of the oil casing and information of the material of the oil casing;
the oil casing wall thickness information, the oil casing diameter information and the oil casing material information are basic information of the oil casing to be perforated, and the basic information of the oil casing to be perforated can be obtained by uploading the basic information of the oil casing to be perforated through a user terminal after the basic information is automatically determined by a user in combination with actual conditions.
Configuring a constraint drilling diameter and a constraint drilling depth based on a drilling constraint table according to the oil casing wall thickness information and the oil casing diameter information;
specifically, the perforation constraint table is preconfigured by an expert in the field and comprises data tables of oil casing wall thickness information, oil casing diameter information and corresponding perforation constraint diameters and depths of different specifications. And performing traversal matching in a perforation constraint table according to the oil casing wall thickness information and the oil casing diameter information, and acquiring the constraint drilling diameter and depth corresponding to the oil casing wall thickness information and the oil casing diameter information as constraint drilling diameter and constraint drilling depth.
Performing drill bit control optimizing on the constraint drilling diameter and the constraint drilling depth through the oil casing material information to generate drill bit expected rotation speed time sequence information and drill bit expected feeding speed time sequence information;
in a preferred embodiment, further comprising:
taking the oil casing material information, the constraint drilling diameter and the constraint drilling depth as constraints to carry out positive sampling to obtain an oil casing perforation sample data set, wherein any group of oil casing perforation sample data sets comprise drill bit rotation speed monitoring value time sequence information and drill bit feeding speed time sequence information; based on the bit rotation speed monitoring value time sequence information and the bit feeding speed time sequence information, performing two-by-two similar analysis on the oil casing perforation sample data set to generate a sample similarity coefficient; clustering the oil casing perforation sample data set based on a sample similarity coefficient threshold to generate multi-cluster oil casing perforation sample data; and optimally sorting the multi-cluster oil casing perforation sample data to generate the time sequence information of the expected rotation speed of the drill bit and the time sequence information of the expected feeding speed of the drill bit.
In a preferred embodiment, further comprising:
Constructing a similarity analysis function:
，
，
wherein,characterizing a rotation speed similarity coefficient or a feed speed similarity coefficient, < >>A rotation speed of the ith time zone or a feed speed of the ith time zone characterizing the first oil jacket perforation sample data, +.>A rotation speed of the ith time zone or a feed speed of the ith time zone characterizing the second oil jacket perforation sample data, +.>Characterizing a rotational speed deviation threshold or a feed speed deviation threshold, < >>Time length of the ith time zone of the first oil casing perforation sample data is characterized by +.>The ith time zone length, +_f, of the second oil casing perforation sample data is characterized>Representing a time length deviation threshold value, M representing the total time zone number of the first oil casing perforation sample data,/>Total number of time zones characterizing the second oil jacket well-perforated sample data, +.>Characterizing a first preset bias parameter, < ->Characterizing a second preset bias parameter, +.>Is the third onePresetting bias parameters, < >>Characterizing a sequence number similarity function;
according to the similarity analysis function, carrying out two-by-two similarity analysis on the time sequence information of the drill bit rotation speed monitoring value to generate a rotation speed similarity coefficient; according to the similarity analysis function, carrying out two-by-two similarity analysis on the drill feeding speed time sequence information to generate a feeding speed similarity coefficient; the rotation speed similarity coefficient and the feed speed similarity coefficient are added to the sample similarity coefficient.
In a preferred embodiment, further comprising:
traversing the multi-cluster oil sleeve perforation sample data, and calculating the sample number proportion coefficient in the cluster, wherein the sample number proportion coefficient in the cluster represents the ratio of the sample number in the cluster to the total number of samples; deleting clusters with the number of samples in the clusters smaller than or equal to a proportional coefficient threshold value to obtain high-frequency cluster oil sleeve perforation sample data; and sorting the minimum punching time length from the high-frequency cluster oil casing punching sample data, and generating the time sequence information of the expected bit rotating speed and the time sequence information of the expected bit feeding speed.
And performing drill bit control optimizing on the constraint drilling diameter and the constraint drilling depth through the oil casing material information to generate drill bit expected rotation speed time sequence information and drill bit expected feeding speed time sequence information, wherein the specific process is as follows.
Taking the oil casing material information, the constraint drilling diameter and the constraint drilling depth as constraints to perform positive sampling to obtain an oil casing drilling sample data set, in short, the positive sampling is a process of selecting a positive sample (target class) from the data set, in this embodiment, historical oil casing drilling record data which are the same as the oil casing material information, the constraint drilling diameter and the constraint drilling depth are extracted from historical oil casing drilling data through existing data mining and other technologies to serve as the oil casing drilling sample data set, wherein any group of the oil casing drilling sample data sets comprises drill bit rotation speed monitoring value time sequence information and drill bit feeding speed time sequence information, in the drilling process, a drill bit rotates at a high speed to enter the oil casing, drill bit rotation speed and drill bit feeding speed are monitored and recorded in real time, and therefore drill bit rotation speed monitoring value time sequence information and drill bit feeding speed time sequence information under continuous time can be directly extracted.
Further, based on the bit rotation speed monitoring value time sequence information and the bit feeding speed time sequence information, performing two-to-two similar analysis on the oil casing perforation sample data set to generate a sample similarity coefficient, namely, performing similarity comparison on any two groups of oil casing perforation sample data sets, wherein the specific process is as follows:
first, a similarity analysis function is constructed:
，
，
wherein,characterizing a rotation speed similarity coefficient or a feed speed similarity coefficient, < >>The rotation speed of the ith time zone or the feeding speed of the ith time zone representing the first oil casing perforation sample data, wherein the control amount in each time zone is the same, and the time zone can be understood as the time in the bit rotation speed monitoring value time sequence information and the bit feeding speed time sequence information, and the time in the bit rotation speed monitoring value time sequence information and the bit feeding speed time sequence information can be determined by the time zone>Characterization of the secondRotation speed of the ith time zone or feeding speed of the ith time zone of the oil jacket perforation sample data, +.>Characterizing the rotational speed deviation threshold, or the feed speed deviation threshold, is set by the person skilled in the art himself,time length of the ith time zone of the first oil casing perforation sample data is characterized by +.>The ith time zone length, +_f, of the second oil casing perforation sample data is characterized >A time deviation threshold value is represented, which is set by a person skilled in the art, M represents the total time zone number of the first oil casing perforation sample data,/o>Total number of time zones characterizing the second oil jacket well-perforated sample data, +.>Characterizing a first preset bias parameter, < ->Characterizing a second preset bias parameter, +.>For the third preset bias parameter, +.>Characterization sequence number similarity function,/->Is a statistical symbol, in this embodiment, the statistical table is used for counting the rotation speed of the ith time zone of the first oil casing perforation sample data or the feeding speed of the ith time zone and the ith time zone of the second oil casing perforation sample dataThe deviation between the rotational speed or the feed speed in the i-th time zone is less than or equal to the rotational speed deviation threshold or the feed speed deviation threshold, and further calculates the ratio of the maximum value thereof to the maximum value in M, N, that is, the maximum value of the total number of time zones.
And simultaneously counting the number of time length deviation between the time length of the ith time zone of the first oil sleeve perforation sample data and the time length of the ith time zone of the second oil sleeve perforation sample data, wherein the time length deviation is smaller than or equal to a time length deviation threshold value, and then calculating the ratio of the time length deviation to the maximum value of the total number of time zones. That is, when two-by-two similarity analysis is performed on the oil casing perforation sample data set, the similarity analysis can be performed on the bit rotation speed and the bit feed speed, respectively, by the similarity analysis function.
And according to the similarity analysis function, carrying out two-by-two similarity analysis on the time sequence information of the drill bit rotation speed monitoring values to generate a rotation speed similarity coefficient, specifically, extracting the rotation speed monitoring values of all time zones from any two time sequence information of the drill bit rotation speed monitoring values and substituting the rotation speed monitoring values into the similarity analysis function to obtain the rotation speed similarity coefficient. Similarly, according to the similarity analysis function, the drill bit feeding speeds of all time zones are extracted from any two drill bit feeding speed time sequence information and substituted into the similarity analysis function, and the feeding speed similarity coefficients are obtained. Finally, the rotation speed similarity coefficient and the feed speed similarity coefficient are added to the sample similarity coefficient. Therefore, similarity analysis of the bit rotation speed and the bit feeding speed is respectively carried out, data support is provided for follow-up bit optimizing control, and stability and control precision of bit punching control are improved.
Further, clustering is performed on the oil sleeve perforation sample data set based on sample similarity coefficient thresholds, and multi-cluster oil sleeve perforation sample data is generated, wherein the sample similarity coefficient thresholds comprise a rotation speed similarity coefficient threshold and a feed speed similarity coefficient threshold, and the sample similarity coefficient thresholds are determined by a person skilled in the art in combination with actual experience. And when the rotation speed similarity coefficient is smaller than the rotation speed similarity coefficient threshold value and the feeding speed similarity coefficient is smaller than the feeding speed similarity coefficient threshold value, gathering the corresponding oil casing perforation sample data into one type, thereby obtaining multi-cluster oil casing perforation sample data.
And then optimizing and sorting the multi-cluster oil casing perforation sample data to generate the time sequence information of the expected rotation speed of the drill bit and the time sequence information of the expected feeding speed of the drill bit, wherein the specific process is as follows:
traversing the multi-cluster oil sleeve perforation sample data, extracting the data quantity of each cluster of oil sleeve perforation sample data as the number of samples in the cluster, further extracting the total quantity of data in the oil sleeve perforation sample data set as the total number of samples, and further calculating the ratio of the number of samples in the cluster to the total number of samples as the ratio coefficient of the number of samples in the cluster. And deleting the cluster with the sample number proportion coefficient smaller than or equal to the proportion coefficient threshold value in the cluster, and combining the reserved multi-cluster oil sleeve punching sample data to be used as high-frequency cluster oil sleeve punching sample data, wherein the proportion coefficient threshold value is set by a person skilled in the art, and the effect of controlling and optimizing is improved by reserving the punching sample data with better performance in order to remove the punching sample data with worse performance.
And sorting the minimum punching time length from the high-frequency cluster oil sleeve punching sample data, namely extracting the punching time length according to the time sequence information of the bit rotation speed monitoring value and the time sequence information of the bit feeding speed in the high-frequency cluster oil sleeve punching sample data, and selecting the time sequence information of the bit rotation speed monitoring value and the time sequence information of the bit feeding speed with the minimum punching time length as the time sequence information of the bit expected rotation speed and the time sequence information of the bit expected feeding speed. Therefore, the drill bit control optimizing is realized, and the control stability of the drilling diameter and the drilling depth is improved.
According to the time sequence information of the expected rotation speed of the drill bit and the time sequence information of the expected feeding speed of the drill bit, analyzing a liquid pressurization reverse mapping channel to generate liquid pressurization optimization control parameters, wherein the liquid pressurization optimization control parameters comprise recommended pressurization liquid flow time sequence information, recommended pressurization duration time sequence information and recommended pressurization liquid temperature time sequence information;
in a preferred embodiment, further comprising:
performing intersection segmentation on the time sequence information of the expected rotating speed of the drill bit and the time sequence information of the expected feeding speed of the drill bit, and extracting the expected rotating speed of a first time zone and the expected feeding speed of the first time zone; executing the analysis of the liquid pressurization reverse mapping channel according to the first time zone expected rotation speed and the first time zone expected feeding speed to generate a first time zone liquid pressurization optimization control parameter; adding the first time zone liquid pressurization optimal control parameter to the liquid pressurization optimal control parameter; and repeating the iteration until the processing of the time sequence information of the expected rotating speed of the drill bit and the time sequence information of the expected feeding speed of the drill bit is finished, and outputting the liquid pressurization optimization control parameters.
In a preferred embodiment, further comprising:
collecting rotation speed monitoring data, feeding speed monitoring data and liquid pressurization control parameter identification data; constructing a reverse mapping loss function, and configuring the liquid pressurization reverse mapping channel based on the rotation speed monitoring data, the feeding speed monitoring data and the liquid pressurization control parameter identification data; wherein, when at least 0.9×m loss values in the continuous M training of the reverse mapping loss function are smaller than or equal to a preset loss value, the liquid pressurization reverse mapping channel is generated; and executing the analysis of the liquid pressurization reverse mapping channel according to the first time zone expected rotation speed and the first time zone expected feeding speed to generate the first time zone liquid pressurization optimal control parameter.
In a preferred embodiment, further comprising:
the reverse mapping loss function is:
，
wherein,characterizing the training loss value, Q characterizing the training constraint number of statistical training loss values, < ->Characterization of the pressurized liquid flow prediction value of the kth training,/->Predictive value of the duration of pressurization characterizing the kth training, for example>Characterization of the pressurized liquid temperature prediction value of the kth training,/->Pressurized fluid flow identification value for kth training,/- >A pressurization duration identification value for characterizing the kth training, < >>A pressurized liquid temperature identification value characterizing the kth training,/->，/>And->For normalizing the adjustment factor.
According to the bit expected rotation speed time sequence information and the bit expected feeding speed time sequence information, analyzing a liquid pressurizing reverse mapping channel is executed, and liquid pressurizing optimization control parameters are generated, wherein the liquid pressurizing optimization control parameters comprise recommended pressurizing liquid flow time sequence information, recommended pressurizing duration time sequence information and recommended pressurizing liquid temperature time sequence information, and a general oil casing electric drilling device performs pressurizing control on a bit to drill through hydraulic equipment.
Specifically, the desired rotation speed timing information and the desired feeding speed timing information are divided into intersections, and the intersections are divided into larger time zones in smaller time zones, that is, the desired rotation speed timing information and the desired feeding speed timing information are identical in duration, but the desired rotation speed timing information and the desired feeding speed timing information may include a plurality of time zones, and the time zones may be different from each other, for example, a first time zone of the desired rotation speed timing information is 1 minute, a first time zone of the desired feeding speed timing information is 2 minutes, and then the larger time zone is divided into 1 minute in smaller time zone, that is, a rotation speed and a feeding speed corresponding to one minute are extracted from the desired rotation speed timing information and the desired feeding speed timing information as the desired rotation speed and the desired feeding speed of the first time zone.
And executing the analysis of the liquid pressurization reverse mapping channel according to the first time zone expected rotation speed and the first time zone expected feeding speed to generate a first time zone liquid pressurization optimization control parameter, wherein the specific process is as follows:
the method comprises the steps of collecting rotation speed monitoring data, feeding speed monitoring data and liquid pressurization control parameter identification data, wherein the liquid pressurization control parameter identification data comprises a pressurized liquid flow identification value, a pressurization duration identification value and a pressurized liquid temperature identification value, and understandably, the rotation speed monitoring data, the feeding speed monitoring data and the liquid pressurization control parameter identification data are training data for constructing the liquid pressurization reverse mapping channel, and can be obtained by extracting historical perforation record data.
Constructing a reverse mapping loss function, wherein the reverse mapping loss function is as follows:
，
wherein,characterizing training loss values, Q characterizing training constraint times for statistical training loss values, set by the person skilled in the art at his own discretion, e.g. 100 times,/o>Characterization of the pressurized liquid flow prediction value of the kth training,/->Predictive value of the duration of pressurization characterizing the kth training, for example>Characterization of the pressurized liquid temperature prediction value of the kth training,/- >Pressurized fluid flow identification value for kth training,/->A pressurization duration identification value for characterizing the kth training, < >>A pressurized liquid temperature identification value characterizing the kth training,/->，/>And->For normalizing the adjustment coefficients, the normalization adjustment coefficients are used for mapping the data of different scales to a value range between 0 and 1 in a unified manner, and are specifically set by a person skilled in the art.
In colloquial terms, the liquid pressurization reverse mapping channel is a functional model for pressurization control analysis according to the rotation speed and the feeding speed, and can be constructed based on the existing machine learning model, such as a neural network model, so that the liquid pressurization reverse mapping channel is trained by the rotation speed monitoring data, the feeding speed monitoring data and the liquid pressurization control parameter identification data, specifically, the rotation speed monitoring data and the feeding speed monitoring data are input into the liquid pressurization reverse mapping channel, and a pressurization liquid temperature predicted value, a pressurization liquid flow predicted value and a pressurization duration predicted value are output. Substituting the pressurized liquid flow identification value, the pressurized time length identification value, the pressurized liquid temperature prediction value, the pressurized liquid flow prediction value and the pressurized time length prediction value in the liquid pressurization control parameter identification data into a reverse mapping loss function to obtain a training loss value of one training, and continuously repeating the training for a plurality of times to obtain the training loss value.
And when at least 0.9×m loss values in M continuous training of the reverse mapping loss function are smaller than or equal to preset loss values, generating the liquid pressurization reverse mapping channel, wherein M is an integer greater than 0, and the preset loss values are set by a person skilled in the art in combination with actual self. For example, in 100 continuous training, if the training loss value is less than or equal to the preset loss value for 90 times, the liquid pressurization reverse mapping channel is considered to be trained to be converged, and the trained liquid pressurization reverse mapping channel is obtained, so that model support is provided for liquid pressurization optimization control.
Inputting the first time zone expected rotation speed and the first time zone expected feeding speed into the liquid pressurization reverse mapping channel for analysis, and outputting the first time zone liquid pressurization optimal control parameters, wherein the first time zone liquid pressurization optimal control parameters comprise pressurized liquid flow, pressurized time and pressurized liquid temperature. Adding the first time zone liquid pressurization optimal control parameter to the liquid pressurization optimal control parameter. Repeating iteration, namely extracting the expected rotation speed of the second time zone and the expected feeding speed of the second time zone, acquiring the liquid pressurization optimal control parameters of the second time zone by adopting the same method, adding the liquid pressurization optimal control parameters into the liquid pressurization optimal control parameters, and so on until the time sequence information of the expected rotation speed of the drill bit and the time sequence information of the expected feeding speed of the drill bit are processed, stopping outputting the liquid pressurization optimal control parameters, thereby realizing accurate liquid pressurization analysis under different time zones and improving the control stability and accuracy of the electric punching equipment.
The liquid pressurization optimization control parameters comprise pressurization liquid flow rates, pressurization time periods and pressurization liquid temperatures which correspond to the time zones respectively, the pressurization liquid flow rates which correspond to the time zones respectively are arranged to form recommended pressurization liquid flow time sequence information according to time zone sequence, the pressurization time periods which correspond to the time zones respectively are arranged to form recommended pressurization time sequence information, and the pressurization liquid temperatures which correspond to the time zones respectively are arranged to form recommended pressurization liquid temperature time sequence information.
And performing intelligent control of the electric punching equipment according to the recommended pressurized liquid flow time sequence information, the recommended pressurized time sequence information and the recommended pressurized liquid temperature time sequence information.
The intelligent control of the electric punching equipment is executed according to the recommended pressurized liquid flow time sequence information, the recommended pressurized time length time sequence information and the recommended pressurized liquid temperature time sequence information, specifically, the pressurized liquid flow is generally controlled through electric pump rotation, the corresponding pump rotation speed can be matched based on the recommended pressurized liquid flow time sequence information according to the pump rotation speed-pressurized liquid flow meter of the actually-used oil sleeve electric punching equipment, and the electric control is carried out by combining the recommended pressurized time length time sequence information and the recommended pressurized liquid temperature time sequence information. The pump rotation speed-pressurized liquid flow meter is configured by a person skilled in the art in combination with practical situations, wherein the pump rotation speeds correspond to different pressurized liquid flow rates.
Based on the above analysis, the one or more technical solutions provided in the present application can achieve the following beneficial effects:
receiving basic information of an oil casing to be perforated, wherein the basic information of the oil casing to be perforated comprises information of the wall thickness of the oil casing, information of the diameter of the oil casing and information of the material of the oil casing; configuring constraint drilling diameters and constraint drilling depths based on a perforation constraint table according to the oil casing wall thickness information and the oil casing diameter information; performing drill bit control optimizing by restraining the drilling diameter and the drilling depth through oil casing material information, and generating drill bit expected rotation speed time sequence information and drill bit expected feeding speed time sequence information; performing analysis of the liquid pressurization reverse mapping channel according to the bit expected rotation speed time sequence information and the bit expected feeding speed time sequence information, and generating liquid pressurization optimization control parameters, wherein the liquid pressurization optimization control parameters comprise recommended pressurization liquid flow time sequence information, recommended pressurization duration time sequence information and recommended pressurization liquid temperature time sequence information; and performing intelligent control of the electric punching device according to the recommended pressurized liquid flow time sequence information, the recommended pressurized time sequence information and the recommended pressurized liquid temperature time sequence information. According to the method, drill bit control optimizing is conducted on oil casing material information, the drilling diameter and the drilling depth are restrained, drill bit expected rotation speed time sequence information and drill bit expected feeding speed time sequence information are generated, further analysis of a liquid pressurizing reverse mapping channel is conducted according to the drill bit expected rotation speed time sequence information and the drill bit expected feeding speed time sequence information, liquid pressurizing optimal control parameters are generated, and accurate and stable control of the aperture and the depth is achieved, so that the technical effects of drilling control precision and accuracy are improved.
Example two
Based on the same inventive concept as the intelligent control method of the oil casing electric punching device in the foregoing embodiment, as shown in fig. 2, the present application further provides an intelligent control system of the oil casing electric punching device, where the system includes:
the base information receiving module 11 is used for receiving base information of an oil casing to be perforated, wherein the base information of the oil casing to be perforated comprises oil casing wall thickness information, oil casing diameter information and oil casing material information;
a drilling parameter configuration module 12, wherein the drilling parameter configuration module 12 is used for configuring a constraint drilling diameter and a constraint drilling depth based on a drilling constraint table according to the oil casing wall thickness information and the oil casing diameter information;
the drill bit control optimizing module 13 is used for performing drill bit control optimizing through the oil casing material information, the constraint drilling diameter and the constraint drilling depth, and generating drill bit expected rotation speed time sequence information and drill bit expected feeding speed time sequence information;
the liquid pressurization reverse analysis module 14 is configured to perform analysis of a liquid pressurization reverse mapping channel according to the bit expected rotation speed time sequence information and the bit expected feeding speed time sequence information, and generate a liquid pressurization optimization control parameter, where the liquid pressurization optimization control parameter includes recommended pressurization liquid flow time sequence information, recommended pressurization duration time sequence information and recommended pressurization liquid temperature time sequence information;
The intelligent control module 15 is used for performing intelligent control of the electric punching device according to the recommended pressurized liquid flow time sequence information, the recommended pressurized time length time sequence information and the recommended pressurized liquid temperature time sequence information.
Further, the drill control optimizing module 13 further includes:
taking the oil casing material information, the constraint drilling diameter and the constraint drilling depth as constraints to carry out positive sampling to obtain an oil casing perforation sample data set, wherein any group of oil casing perforation sample data sets comprise drill bit rotation speed monitoring value time sequence information and drill bit feeding speed time sequence information;
based on the bit rotation speed monitoring value time sequence information and the bit feeding speed time sequence information, performing two-by-two similar analysis on the oil casing perforation sample data set to generate a sample similarity coefficient;
clustering the oil casing perforation sample data set based on a sample similarity coefficient threshold to generate multi-cluster oil casing perforation sample data;
and optimally sorting the multi-cluster oil casing perforation sample data to generate the time sequence information of the expected rotation speed of the drill bit and the time sequence information of the expected feeding speed of the drill bit.
Further, the drill control optimizing module 13 further includes:
constructing a similarity analysis function:
，
，
wherein,characterizing a rotation speed similarity coefficient or a feed speed similarity coefficient, < >>A rotation speed of the ith time zone or a feed speed of the ith time zone characterizing the first oil jacket perforation sample data, +.>A rotation speed of the ith time zone or a feed speed of the ith time zone characterizing the second oil jacket perforation sample data, +.>Characterizing a rotational speed deviation threshold or a feed speed deviation threshold, < >>Time length of the ith time zone of the first oil casing perforation sample data is characterized by +.>The ith time zone length, +_f, of the second oil casing perforation sample data is characterized>Representing a time length deviation threshold value, M representing the total time zone number of the first oil casing perforation sample data,/>Total number of time zones characterizing the second oil jacket well-perforated sample data, +.>Characterizing a first preset bias parameter, < ->Characterizing a second preset bias parameter, +.>For the third preset bias parameter, +.>Characterizing a sequence number similarity function;
according to the similarity analysis function, carrying out two-by-two similarity analysis on the time sequence information of the drill bit rotation speed monitoring value to generate a rotation speed similarity coefficient;
according to the similarity analysis function, carrying out two-by-two similarity analysis on the drill feeding speed time sequence information to generate a feeding speed similarity coefficient;
The rotation speed similarity coefficient and the feed speed similarity coefficient are added to the sample similarity coefficient.
Further, the drill control optimizing module 13 further includes:
traversing the multi-cluster oil sleeve perforation sample data, and calculating the sample number proportion coefficient in the cluster, wherein the sample number proportion coefficient in the cluster represents the ratio of the sample number in the cluster to the total number of samples;
deleting clusters with the number of samples in the clusters smaller than or equal to a proportional coefficient threshold value to obtain high-frequency cluster oil sleeve perforation sample data;
and sorting the minimum punching time length from the high-frequency cluster oil casing punching sample data, and generating the time sequence information of the expected bit rotating speed and the time sequence information of the expected bit feeding speed.
Further, the liquid pressurized reverse osmosis module 14 further comprises:
performing intersection segmentation on the time sequence information of the expected rotating speed of the drill bit and the time sequence information of the expected feeding speed of the drill bit, and extracting the expected rotating speed of a first time zone and the expected feeding speed of the first time zone;
executing the analysis of the liquid pressurization reverse mapping channel according to the first time zone expected rotation speed and the first time zone expected feeding speed to generate a first time zone liquid pressurization optimization control parameter;
Adding the first time zone liquid pressurization optimal control parameter to the liquid pressurization optimal control parameter;
and repeating the iteration until the processing of the time sequence information of the expected rotating speed of the drill bit and the time sequence information of the expected feeding speed of the drill bit is finished, and outputting the liquid pressurization optimization control parameters.
Further, the liquid pressurized reverse osmosis module 14 further comprises:
collecting rotation speed monitoring data, feeding speed monitoring data and liquid pressurization control parameter identification data;
constructing a reverse mapping loss function, and configuring the liquid pressurization reverse mapping channel based on the rotation speed monitoring data, the feeding speed monitoring data and the liquid pressurization control parameter identification data;
wherein, when at least 0.9×m loss values in the continuous M training of the reverse mapping loss function are smaller than or equal to a preset loss value, the liquid pressurization reverse mapping channel is generated;
and executing the analysis of the liquid pressurization reverse mapping channel according to the first time zone expected rotation speed and the first time zone expected feeding speed to generate the first time zone liquid pressurization optimal control parameter.
Further, the liquid pressurized reverse osmosis module 14 further comprises:
The reverse mapping loss function is:
，
wherein,characterizing the training loss value, Q characterizing the training constraint number of statistical training loss values, < ->Characterization of the pressurized liquid flow prediction value of the kth training,/->Predictive value of the duration of pressurization characterizing the kth training, for example>Characterization of the pressurized liquid temperature prediction value of the kth training,/->Pressurized fluid flow identification value for kth training,/->A pressurization duration identification value for characterizing the kth training, < >>A pressurized liquid temperature identification value characterizing the kth training,/->，/>And->For normalizing the adjustment factor.
The specific example of the intelligent control method of the oil casing electric punching device in the first embodiment is also applicable to the intelligent control system of the oil casing electric punching device in the present embodiment, and by the foregoing detailed description of the intelligent control method of the oil casing electric punching device, those skilled in the art can clearly know the intelligent control system of the oil casing electric punching device in the present embodiment, so that the details will not be described herein for brevity of the description.
It should be understood that the various forms of flow shown above, reordered, added, or deleted steps may be used, as long as the desired results of the presently disclosed technology are achieved, and are not limited herein.
Note that the above is only a preferred embodiment of the present application and the technical principle applied. Those skilled in the art will appreciate that the present application is not limited to the particular embodiments described herein, but is capable of numerous obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the present application. Therefore, while the present application has been described in connection with the above embodiments, the present application is not limited to the above embodiments, but may include many other equivalent embodiments without departing from the spirit of the present application, the scope of which is defined by the scope of the appended claims.
Claims (8)
1. An intelligent control method of an oil casing electric punching device is characterized by comprising the following steps:
receiving basic information of an oil casing to be perforated, wherein the basic information of the oil casing to be perforated comprises information of the wall thickness of the oil casing, information of the diameter of the oil casing and information of the material of the oil casing;
configuring a constraint drilling diameter and a constraint drilling depth based on a drilling constraint table according to the oil casing wall thickness information and the oil casing diameter information;
performing drill bit control optimizing on the constraint drilling diameter and the constraint drilling depth through the oil casing material information to generate drill bit expected rotation speed time sequence information and drill bit expected feeding speed time sequence information;
According to the time sequence information of the expected rotation speed of the drill bit and the time sequence information of the expected feeding speed of the drill bit, analyzing a liquid pressurization reverse mapping channel to generate liquid pressurization optimization control parameters, wherein the liquid pressurization optimization control parameters comprise recommended pressurization liquid flow time sequence information, recommended pressurization duration time sequence information and recommended pressurization liquid temperature time sequence information;
and performing intelligent control of the electric punching equipment according to the recommended pressurized liquid flow time sequence information, the recommended pressurized time sequence information and the recommended pressurized liquid temperature time sequence information.
2. The method of claim 1, wherein the generating the bit desired rotational speed timing information and the bit desired feed speed timing information by bit control optimizing the constrained borehole diameter and the constrained borehole depth from the oil casing material information comprises:
taking the oil casing material information, the constraint drilling diameter and the constraint drilling depth as constraints to carry out positive sampling to obtain an oil casing perforation sample data set, wherein any group of oil casing perforation sample data sets comprise drill bit rotation speed monitoring value time sequence information and drill bit feeding speed time sequence information;
Based on the bit rotation speed monitoring value time sequence information and the bit feeding speed time sequence information, performing two-by-two similar analysis on the oil casing perforation sample data set to generate a sample similarity coefficient;
clustering the oil casing perforation sample data set based on a sample similarity coefficient threshold to generate multi-cluster oil casing perforation sample data;
and optimally sorting the multi-cluster oil casing perforation sample data to generate the time sequence information of the expected rotation speed of the drill bit and the time sequence information of the expected feeding speed of the drill bit.
3. The method of claim 2, wherein performing a two-by-two phase analysis of the oil casing perforation sample dataset based on the bit rotational speed monitor timing information and the bit feed speed timing information, generating sample similarity coefficients comprises:
constructing a similarity analysis function:
，
，
wherein,characterizing a rotation speed similarity coefficient or a feed speed similarity coefficient, < >>A rotation speed of the ith time zone or a feed speed of the ith time zone characterizing the first oil jacket perforation sample data, +.>A rotation speed of the ith time zone or a feed speed of the ith time zone characterizing the second oil jacket perforation sample data, +. >Characterizing a rotational speed deviation threshold or a feed speed deviation threshold, < >>Time length of the ith time zone of the first oil casing perforation sample data is characterized by +.>The ith time zone length, +_f, of the second oil casing perforation sample data is characterized>Representing a time length deviation threshold value, M representing the total time zone number of the first oil casing perforation sample data,/>Total number of time zones characterizing the second oil jacket well-perforated sample data, +.>Characterizing a first pre-set bias parameter,characterizing a second preset bias parameter, +.>For the third preset bias parameter, +.>Characterizing a sequence number similarity function; according to the similarity analysis function, carrying out two-by-two similarity analysis on the time sequence information of the drill bit rotation speed monitoring value to generate a rotation speed similarity coefficient;
according to the similarity analysis function, carrying out two-by-two similarity analysis on the drill feeding speed time sequence information to generate a feeding speed similarity coefficient;
the rotation speed similarity coefficient and the feed speed similarity coefficient are added to the sample similarity coefficient.
4. The method of claim 2, wherein optimally sorting the multi-cluster oil casing perforation sample data to generate the bit desired rotational speed timing information and the bit desired feed speed timing information comprises:
Traversing the multi-cluster oil sleeve perforation sample data, and calculating the sample number proportion coefficient in the cluster, wherein the sample number proportion coefficient in the cluster represents the ratio of the sample number in the cluster to the total number of samples;
deleting clusters with the number of samples in the clusters smaller than or equal to a proportional coefficient threshold value to obtain high-frequency cluster oil sleeve perforation sample data;
and sorting the minimum punching time length from the high-frequency cluster oil casing punching sample data, and generating the time sequence information of the expected bit rotating speed and the time sequence information of the expected bit feeding speed.
5. The method of claim 1, wherein performing an analysis of the liquid pressurization reverse map channel based on the bit desired rotational speed timing information and the bit desired feed speed timing information generates liquid pressurization optimization control parameters, wherein the liquid pressurization optimization control parameters include recommended pressurization liquid flow timing information, recommended pressurization duration timing information, and recommended pressurization liquid temperature timing information, comprising:
performing intersection segmentation on the time sequence information of the expected rotating speed of the drill bit and the time sequence information of the expected feeding speed of the drill bit, and extracting the expected rotating speed of a first time zone and the expected feeding speed of the first time zone;
Executing the analysis of the liquid pressurization reverse mapping channel according to the first time zone expected rotation speed and the first time zone expected feeding speed to generate a first time zone liquid pressurization optimization control parameter;
adding the first time zone liquid pressurization optimal control parameter to the liquid pressurization optimal control parameter;
and repeating the iteration until the processing of the time sequence information of the expected rotating speed of the drill bit and the time sequence information of the expected feeding speed of the drill bit is finished, and outputting the liquid pressurization optimization control parameters.
6. The method of claim 5, wherein performing the parsing of the liquid pressurization reverse map passage based on the first time zone desired rotational speed and the first time zone desired feed speed, generating a first time zone liquid pressurization optimization control parameter comprises:
collecting rotation speed monitoring data, feeding speed monitoring data and liquid pressurization control parameter identification data;
constructing a reverse mapping loss function, and configuring the liquid pressurization reverse mapping channel based on the rotation speed monitoring data, the feeding speed monitoring data and the liquid pressurization control parameter identification data;
wherein, when at least 0.9×m loss values in the continuous M training of the reverse mapping loss function are smaller than or equal to a preset loss value, the liquid pressurization reverse mapping channel is generated;
And executing the analysis of the liquid pressurization reverse mapping channel according to the first time zone expected rotation speed and the first time zone expected feeding speed to generate the first time zone liquid pressurization optimal control parameter.
7. The method of claim 6, wherein the inverse mapping loss function is:
，
wherein,characterizing the training loss value, Q characterizing the training constraint number of statistical training loss values, < ->Characterization of the pressurized liquid flow prediction value of the kth training,/->Predictive value of the duration of pressurization characterizing the kth training, for example>Characterization of the pressurized liquid temperature prediction value of the kth training,/->Pressurized fluid flow identification value for kth training,/->A pressurization duration identification value for characterizing the kth training, < >>A pressurized liquid temperature identification value characterizing the kth training,/->,/>And->For normalizing the adjustment factor.
8. An intelligent control system for an oil casing electrically operated perforating apparatus, characterized by the steps for performing the method of any of claims 1 to 7, the system comprising:
the base information receiving module is used for receiving base information of the oil casing to be perforated, wherein the base information of the oil casing to be perforated comprises oil casing wall thickness information, oil casing diameter information and oil casing material information;
The drilling parameter configuration module is used for configuring constraint drilling diameter and constraint drilling depth based on a drilling constraint table according to the oil casing wall thickness information and the oil casing diameter information;
the drill bit control optimizing module is used for performing drill bit control optimizing through the oil casing material information, the constraint drilling diameter and the constraint drilling depth, and generating drill bit expected rotation speed time sequence information and drill bit expected feeding speed time sequence information;
the liquid pressurization reverse analysis module is used for executing analysis of a liquid pressurization reverse mapping channel according to the time sequence information of the expected rotation speed of the drill bit and the time sequence information of the expected feeding speed of the drill bit to generate liquid pressurization optimal control parameters, wherein the liquid pressurization optimal control parameters comprise recommended pressurization liquid flow time sequence information, recommended pressurization duration time sequence information and recommended pressurization liquid temperature time sequence information;
the intelligent control module is used for performing intelligent control of the electric punching equipment according to the recommended pressurized liquid flow time sequence information, the recommended pressurized time length time sequence information and the recommended pressurized liquid temperature time sequence information.
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