CN117072141A - Real-time early warning method and device for stuck drilling accident based on real drilling logging data - Google Patents
Real-time early warning method and device for stuck drilling accident based on real drilling logging data Download PDFInfo
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- E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B44/00—Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions
- E21B44/02—Automatic control of the tool feed
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- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
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Abstract
The application provides a real-time early warning method and device for stuck drilling accidents based on real drilling logging data, and relates to the technical field of preventing stuck drilling in petroleum exploration and development drilling engineering, wherein the method comprises the following steps: acquiring drilling data for a plurality of data points; calculating to obtain mathematical expectation and variance of random variables according to drilling data of the data points; setting a proportional relation between a first constant and a standard deviation according to the condition of a drilling site; determining the drilling data safety range by using a chebyshev inequality according to the mathematical expectation and variance of the random variable and the proportional relation between the first constant and the standard deviation; and acquiring real-time drilling data in the drilling process, and carrying out real-time early warning on the stuck drilling accident according to the real-time drilling data and the drilling data safety range.
Description
Technical Field
The application relates to the technical field of drilling engineering for preventing stuck drilling in petroleum exploration and development, in particular to a real-time early warning method and device for stuck drilling accidents based on real drilling logging data.
Background
This section is intended to provide a background or context to the embodiments of the application that are recited in the claims. The description herein is not admitted to be prior art by inclusion in this section.
The drilling sticking is a serious underground complex condition in the petroleum drilling process, and once serious blocking occurs, a plurality of accidents such as drilling tool breaking, lost circulation, overflow and the like are accompanied, so that the drilling period is greatly influenced, and super negative economic benefit is brought. Therefore, it is needed to establish a method for giving early warning of stuck drill in real time, so as to assist the field personnel to predict the abnormal stuck drill in the previous step, and take corresponding preventive measures in advance to prevent the underground accident.
When the drilling machine is in the same working condition state (such as drilling, tripping and tripping) and driller does not make obvious adjustment on drilling parameters, the whole hook load has a stable small-amplitude increasing/decreasing trend. When the hook load is suddenly changed, the hook load is often a sign of sticking.
At present, the early warning of the stuck drilling accident is mainly realized in two modes:
1. and recording the suspended weight of the winch in a stop state through a PLC, comparing the increment of the suspended weight with the set suspended weight parameter in real time, and carrying out early warning prompt according to the result. This approach suffers from the following disadvantages:
1. a specific calculation method for setting the suspended weight parameter is not provided, a certain delay time is determined manually, and real-time is difficult to achieve;
2. the effect of the field operating mode change is not taken into account.
2. Based on the logging data of the adjacent well stuck section, an early warning model is established, relevant data of the well is input to judge whether the stuck risk exists, and the following defects exist in the mode:
1. the stuck drilling judging model needs to be established on the basis of a large amount of effective data, and the current drilling data can not meet the model training requirement;
2. different wells are very likely to give wrong judgment results due to different geological conditions of drilling and stuck drilling judgment models;
3. for exploratory wells, basically no adjacent well data can be referred, and only the actual drilling condition of the exploratory well can be referred.
In view of the above, a technical solution is needed that can overcome the above-mentioned drawbacks and can perform fast, efficient, accurate and real-time drill sticking early warning.
Disclosure of Invention
In order to solve the problems in the prior art, the application provides a real-time early warning method and device for stuck drilling accidents based on real drilling logging data. The method has the advantages of simple process and high accuracy, and can be used for identifying the abnormal stuck drill and timely providing an alarm signal for related technicians through real-time early warning of the stuck drill accident of the real-time drilling logging data.
In a first aspect of the embodiment of the present application, a real-time early warning method for stuck drilling accidents based on real drilling logging data is provided, including:
acquiring drilling data for a plurality of data points;
calculating to obtain mathematical expectation and variance of random variables according to drilling data of the data points;
setting a proportional relation between a first constant and a standard deviation according to the condition of a drilling site;
determining the drilling data safety range by using a chebyshev inequality according to the mathematical expectation and variance of the random variable and the proportional relation between the first constant and the standard deviation;
and acquiring real-time drilling data in the drilling process, and carrying out real-time early warning on the stuck drilling accident according to the real-time drilling data and the drilling data safety range.
In a second aspect of the embodiment of the present application, a real-time early warning device for stuck drilling accidents based on real drilling logging data is provided, including:
the data acquisition module is used for acquiring drilling data of a plurality of data points;
the data calculation module is used for calculating the mathematical expectation and variance of the random variable according to the drilling data of the data points;
the proportional relation setting module is used for setting the proportional relation between the first constant and the standard deviation according to the condition of the drilling site;
the safety range calculation module is used for determining the safety range of drilling data by using a Chebyshev inequality according to the mathematical expectation and variance of the random variable and the proportional relation between the first constant and the standard deviation;
and the real-time early warning module is used for acquiring real-time drilling data in the drilling process and carrying out real-time early warning on the stuck drilling accident according to the real-time drilling data and the drilling data safety range.
In a third aspect of the embodiment of the present application, a computer device is provided, including a memory, a processor, and a computer program stored on the memory and capable of running on the processor, where the processor implements a real-time early warning method for a stuck drilling accident based on real drilling logging data when executing the computer program.
In a fourth aspect of the embodiments of the present application, a computer readable storage medium is provided, where a computer program is stored, where the computer program when executed by a processor implements a real-time early warning method for stuck drilling accidents based on real drilling logging data.
In a fifth aspect of the embodiments of the present application, a computer program product is provided, the computer program product comprising a computer program, which when executed by a processor, implements a real-time early warning method for stuck pipe accidents based on real-time drilling logging data.
The real-time early warning method and device for the stuck drill accident based on the real-time drilling logging data provided by the application are simple in process and are suitable for monitoring and early warning the stuck drill in the petroleum drilling site. The whole treatment process is flexible, and each oilfield company can set parameters according to the well control requirement of the oilfield company, so that the adjustment of the alarm threshold is realized, and the universality is strong. And moreover, the real-time monitoring and prevention of the stuck drilling can be realized through the drilling acquisition parameters of the target well, so that the real-time monitoring is realized, the adjacent well data do not need to be referenced, and the early warning of the stuck drilling of the first risk exploratory well in the well region can be realized.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flow chart of a real-time early warning method of stuck drilling accidents based on real drilling logging data according to an embodiment of the application.
FIG. 2 is a schematic diagram of real-time early warning according to an embodiment of the present application.
FIG. 3 is a process flow diagram of an embodiment of the present application.
Fig. 4 is a schematic diagram of a real-time early warning device for stuck drilling accidents based on real drilling logging data according to an embodiment of the present application.
FIG. 5 is a schematic diagram of a computer device according to an embodiment of the present application.
Detailed Description
The principles and spirit of the present application will be described below with reference to several exemplary embodiments. It should be understood that these embodiments are presented merely to enable those skilled in the art to better understand and practice the application and are not intended to limit the scope of the application in any way. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
Those skilled in the art will appreciate that embodiments of the application may be implemented as a system, apparatus, device, method, or computer program product. Accordingly, the present disclosure may be embodied in the following forms, namely: complete hardware, complete software (including firmware, resident software, micro-code, etc.), or a combination of hardware and software.
According to the embodiment of the application, the real-time early warning method and the device for the stuck drilling accident based on the real drilling logging data, which are simple in process, high in accuracy and predictive in advance, can accurately identify the stuck drilling abnormality and provide an alarm signal for relevant technicians in time, and relate to the technical field of preventing stuck drilling in petroleum exploration and development drilling engineering.
The principles and spirit of the present application are explained in detail below with reference to several representative embodiments thereof.
Fig. 1 is a flow chart of a real-time early warning method of stuck drilling accidents based on real drilling logging data according to an embodiment of the application. As shown in fig. 1, the method includes:
s101, drilling data of a plurality of data points are obtained;
s102, calculating to obtain mathematical expectation and variance of random variables according to drilling data of the data points;
s103, setting a proportional relation between a first constant and a standard deviation according to the condition of a drilling site;
s104, determining the drilling data safety range by using a Chebyshev inequality according to the mathematical expectation and variance of the random variable and the proportional relation between the first constant and the standard deviation;
s105, acquiring real-time drilling data in the drilling process, and carrying out real-time early warning on the stuck drilling accident according to the real-time drilling data and the drilling data safety range.
It should be noted that although the operations of the method of the present application are described in a particular order in the above embodiments and the accompanying drawings, this does not require or imply that the operations must be performed in the particular order or that all of the illustrated operations be performed in order to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step to perform, and/or one step decomposed into multiple steps to perform.
The real-time early warning method for stuck drilling accidents based on real drilling logging data provided by the application is simple in process and is suitable for monitoring and early warning stuck drilling in the petroleum drilling site. The whole treatment process is flexible, and each oilfield company can set parameters according to the well control requirement of the oilfield company, so that the adjustment of the alarm threshold is realized, and the universality is strong. And moreover, the real-time monitoring and prevention of the stuck drilling can be realized through the drilling acquisition parameters of the target well, so that the real-time monitoring is realized, the adjacent well data do not need to be referenced, and the early warning of the stuck drilling of the first risk exploratory well in the well region can be realized.
In order to more clearly explain the real-time early warning method of stuck drilling accidents based on real drilling logging data, each step is described in detail below.
S101, drilling data of a plurality of data points are acquired.
In one embodiment, the method comprises the following steps:
before the drilling work starts, setting initial drilling data or manually setting the initial data based on the historical data, and taking the set drilling data as an initial random variable; wherein the initial random variables are used to calculate mathematical expectations, variances, and adjust the drilling data safety range using chebyshev inequality.
Collecting drilling data in real time in the drilling process, and taking the collected drilling data as a random variable corresponding to the drilling process; the random variables corresponding to the drilling process are used for calculating mathematical expectations and variances, and adjusting the drilling data safety range by using the chebyshev inequality.
In one embodiment, the drilling data includes at least: hook load data and drilling parameter data sets; and taking hook load data acquired by a plurality of data points as random variables when the change of the drilling parameter data set is within a certain range.
Assuming that s data points are collected in the same column, note t= { T 1 ,T 2 ,...T i ,...,T s When the drilling parameter data set is not significantly changed (namely, the influence factors of the hook load meet the same conditions), the hook load is not always affected by drilling vibration, namely, T is a discrete random variable.
S102, calculating the mathematical expectation and variance of the random variable according to the drilling data of the data points.
In one embodiment, the specific method is as follows:
the mathematical expectation of the random variable T is:
the variance is: var (T) =σ 2 ＝E(T-E(T)) 2
Wherein T is a random variable;
e is a mathematical expectation;
T i is the ith random variable;
s is the number of random variables;
p is probability;
var is variance;
sigma is the standard deviation.
S103, setting a proportional relation between the first constant and the standard deviation according to the condition of the drilling site.
ε＝Aσ；
Wherein ε is a first constant;
a is a proportional relationship;
sigma is the standard deviation.
And adjusting the interval corresponding to the drilling data safety range by adjusting the proportional relation between the first constant and the standard deviation.
S104, determining the drilling data safety range by using a Chebyshev inequality according to the mathematical expectation and variance of the random variable and the proportional relation between the first constant and the standard deviation.
In one embodiment, according to the chebyshev inequality, for a first constant ε, ε >0, the following relationship exists:
the value of the random variable falls into [ E (T) -epsilon, E (T) +epsilon]Probability outside the interval
Or alternatively, the first and second heat exchangers may be,
the value of the random variable falls into [ E (T) -epsilon, E (T) +epsilon]Probability within an interval
Setting the drilling data safety range as [ E (T) -epsilon, E (T) +epsilon ];
wherein P represents probability;
t is a random variable;
e is a mathematical expectation;
epsilon is a first constant;
var is variance;
according to the analysis, the probability degree of deviation of the acceptable random variable value from the data center is given, so that whether the value of the random variable is within a reasonable interval range, namely whether the hook load is within a safe drilling range can be judged. The application can realize the drilling sticking monitoring and early warning in the whole petroleum development process.
S105, acquiring real-time drilling data in the drilling process, and carrying out real-time early warning on the stuck drilling accident according to the real-time drilling data and the drilling data safety range.
In one embodiment, referring to fig. 2, the specific method is:
s105-1, acquiring random variable data at the next moment according to the real-time drilling data;
s105-2, when the random variable data falls into the drilling data safety range, judging that the drill sticking does not occur;
s105-3, when the random variable data does not fall into the drilling data safety range, judging that the drill sticking risk occurs.
The random variable data refers to the value of a random variable corresponding to a data point which is being drilled and collected, namely, a hook load value to be judged.
Compared with the prior art, the application has at least the following advantages:
the process is simple, and is suitable for monitoring and early warning of stuck drill in petroleum drilling sites.
The method is flexible, and each oilfield company can set epsilon according to the well control requirement of the oilfield company, so that the alarm threshold value can be adjusted.
The drilling sticking early warning device has the advantages that the drilling sticking early warning device can monitor and prevent the sticking in real time through the drilling acquisition parameters of the target well, achieves real-time monitoring, does not need to reference adjacent well data, and can realize the drilling sticking early warning of the first risk exploratory well of the well region.
The real-time early warning method of stuck drilling accidents based on real drilling logging data is described in detail below with reference to specific embodiments.
Referring to FIG. 3, a process flow diagram is shown, according to an embodiment of the present application. As shown in fig. 3, the main flow includes data collection and update, data storage and processing, and data visualization.
The logging equipment continuously collects and updates hook load data, drills parameter data sets, uploads the data to the cloud platform, and the cloud platform stores, analyzes and processes the uploaded data and sends a processing result to a main control computer on site.
If the drilling parameter set is changed, sending a command for exciting the display to change the drilling parameter to the popup window to the main control computer; if the processing result is that the drill sticking risk exists, a drill sticking alarm module instruction for exciting a drill floor display is sent to the main control computer. Meanwhile, the cloud platform should draw the collected data into relevant visual images, so that operators can observe the data change trend conveniently.
The drill floor display is connected with the main control computer, and is displayed in the drill clamping alarm module on the drill floor display according to the corresponding instruction sent by the main control computer. And if the drilling parameter set changes obviously, exciting a drill floor display to drill parameter change popup instructions. If the hook load measured value falls outside the reference interval range, corresponding drill sticking alarm equipment is excited on the main control computer for 1 time, and the personnel is reminded to keep paying attention and decide whether to take corresponding measures.
In the drilling scenarios of embodiment 1 and embodiment 2, epsilon=9σ is set.
Example 1
Assuming a total number of in situ drilling columns of 185, a weight on bit of 180kN, a total of 120 data points were acquired during the drilling of the column, the mathematical expectation E (T) of the random variable T was 1000, and the variance Var was 81, i.e., σ 2 ＝81。
The value of the random variable T falls into [ E (T) -epsilon, E (T) +epsilon]＝[919，1081]The probability of (2) is greater than
If the value of the random variable T at the next moment is 1001, judging that no drill sticking risk exists;
if the value of the random variable T at the next moment is 1085, determining that the drill sticking risk exists;
and the cloud platform sends the processing result to a main control computer on site, and the main control computer excites a drill clamping alarm display module of a drill floor display.
Example 2
Assuming a total number of in situ drilled columns of 60, a weight on bit of 180kN, 120 data points were collected during the drilling of the column, the mathematical expectation E (T) of the random variable T was 400, and the variance Var was 36, i.e., σ 2 ＝36。
The value of the random variable T falls into [ E (T) -epsilon, E (T) +epsilon]＝[346，454]The probability of (2) is greater than
If the value of the random variable T at the next moment is 350, judging that no drill sticking risk exists;
if the value of the random variable T at the next moment is 474, determining that the drill sticking risk exists;
and the cloud platform sends the processing result to a main control computer on site, and the main control computer excites a drill clamping alarm display module of a drill floor display.
Having described the method of the exemplary embodiment of the present application, a real-time early warning device for stuck pipe accident based on real-time logging data of the exemplary embodiment of the present application will be described with reference to fig. 4.
The implementation of the real-time early warning device for stuck drilling accidents based on real drilling logging data can be referred to the implementation of the method, and repeated parts are not repeated. The term "module" or "unit" as used below may be a combination of software and/or hardware that implements the intended function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.
Based on the same inventive concept, the application also provides a real-time early warning device for stuck drilling accidents based on real drilling logging data, as shown in fig. 4, the device comprises:
a data acquisition module 410 for acquiring drilling data for a plurality of data points;
a data calculation module 420 for calculating a mathematical expectation and variance of the random variable based on the drilling data of the plurality of data points;
a proportional relation setting module 430, configured to set a proportional relation between the first constant and the standard deviation according to a drilling site situation;
the safety range calculation module 440 is configured to determine a drilling data safety range according to the mathematical expectation and variance of the random variable and the proportional relationship between the first constant and the standard deviation by using chebyshev inequality;
and the real-time early warning module 450 is used for acquiring real-time drilling data in the drilling process and carrying out real-time early warning on the stuck drilling accident according to the real-time drilling data and the drilling data safety range.
In one embodiment, the data acquisition module 410 acquires drilling data for a plurality of data points, including:
before the drilling work starts, setting initial drilling data or manually setting the initial data based on the historical data, and taking the set drilling data as an initial random variable; wherein the initial random variables are used to calculate mathematical expectations, variances, and adjust the drilling data safety range using chebyshev inequality.
In one embodiment, the data acquisition module 410 acquires drilling data for a plurality of data points, including:
collecting drilling data in real time in the drilling process, and taking the collected drilling data as a random variable corresponding to the drilling process; the random variables corresponding to the drilling process are used for calculating mathematical expectations and variances, and adjusting the drilling data safety range by using the chebyshev inequality.
In one embodiment, the drilling data includes at least: hook load data and drilling parameter data sets; and taking hook load data acquired by a plurality of data points as random variables when the change of the drilling parameter data set is within a certain range.
In one embodiment, the data calculation module 420 calculates mathematical expectations and variances of the random variables from the drilling data for the plurality of data points, including:
the mathematical expectation of the random variable T is:
the variance is: var (T) =σ 2 ＝E(T-E(T)) 2
Wherein T is a random variable;
e is a mathematical expectation;
T i is the ith random variable;
s is the number of random variables;
p is probability;
var is variance;
sigma is the standard deviation.
In one embodiment, the scaling relationship setting module 430 sets a scaling relationship between the first constant and the standard deviation according to the drilling site conditions, including:
ε＝Aσ；
wherein ε is a first constant;
a is a proportional relationship;
sigma is the standard deviation.
In one embodiment, the interval corresponding to the drilling data safety range is adjusted by adjusting the proportional relationship between the first constant and the standard deviation.
In one embodiment, the safety range calculation module 440 determines the safety range of drilling data using chebyshev's inequality based on the mathematical expectation and variance of the random variables and the proportional relationship of the first constant to the standard deviation, comprising:
according to the chebyshev inequality, for a first constant epsilon, epsilon >0, there is the following relationship:
the value of the random variable falls into [ E (T) -epsilon, E (T) +epsilon]Probability outside the interval
Or alternatively, the first and second heat exchangers may be,
the value of the random variable falls into [ E (T) -epsilon, E (T) +epsilon]Probability within an interval
Setting the drilling data safety range as [ E (T) -epsilon, E (T) +epsilon ];
wherein P represents probability;
t is a random variable;
e is a mathematical expectation;
epsilon is a first constant;
var is variance.
In one embodiment, the real-time early warning module 450 collects real-time drilling data during the drilling process, and performs real-time early warning on the stuck drilling accident according to the real-time drilling data and the drilling data safety range, including:
acquiring random variable data of the next moment according to the real-time drilling data;
when the random variable data falls into the drilling data safety range, judging that the drill sticking does not occur; and when the random variable data does not fall into the drilling data safety range, judging that the drilling sticking risk occurs.
It should be noted that while several modules of a real-time stuck-at warning device based on real-time logging data are mentioned in the detailed description above, this division is merely exemplary and not mandatory. Indeed, the features and functions of two or more modules described above may be embodied in one module in accordance with embodiments of the present application. Conversely, the features and functions of one module described above may be further divided into a plurality of modules to be embodied.
Based on the foregoing inventive concept, as shown in fig. 5, the present application further provides a computer device 500, including a memory 510, a processor 520, and a computer program 530 stored in the memory 510 and capable of running on the processor 520, where the processor 520 implements the foregoing real-time early warning method of stuck drilling accident based on real drilling logging data when executing the computer program 530.
Based on the foregoing inventive concept, the present application provides a computer readable storage medium, where a computer program is stored, where the computer program, when executed by a processor, implements the foregoing real-time early warning method for stuck drilling accidents based on real drilling logging data.
Based on the foregoing inventive concept, the present application provides a computer program product, which includes a computer program that, when executed by a processor, implements a real-time early warning method for stuck drilling accidents based on real drilling logging data.
The real-time early warning method and device for the stuck drill accident based on the real-time drilling logging data provided by the application are simple in process and are suitable for monitoring and early warning the stuck drill in the petroleum drilling site. The whole treatment process is flexible, and each oilfield company can set parameters according to the well control requirement of the oilfield company, so that the adjustment of the alarm threshold is realized, and the universality is strong. And moreover, the real-time monitoring and prevention of the stuck drilling can be realized through the drilling acquisition parameters of the target well, so that the real-time monitoring is realized, the adjacent well data do not need to be referenced, and the early warning of the stuck drilling of the first risk exploratory well in the well region can be realized.
According to the technical scheme, the data are acquired, stored, used and processed according with relevant regulations of laws and regulations.
It will be apparent to those skilled in the art that embodiments of the present application may be provided as a method, apparatus, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above examples are only specific embodiments of the present application, and are not intended to limit the scope of the present application, but it should be understood by those skilled in the art that the present application is not limited thereto, and that the present application is described in detail with reference to the foregoing examples: any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or perform equivalent substitution of some of the technical features, while remaining within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (13)
1. A real-time early warning method for stuck drilling accidents based on real drilling logging data is characterized by comprising the following steps:
acquiring drilling data for a plurality of data points;
calculating to obtain mathematical expectation and variance of random variables according to drilling data of the data points;
setting a proportional relation between a first constant and a standard deviation according to the condition of a drilling site;
determining the drilling data safety range by using a chebyshev inequality according to the mathematical expectation and variance of the random variable and the proportional relation between the first constant and the standard deviation;
and acquiring real-time drilling data in the drilling process, and carrying out real-time early warning on the stuck drilling accident according to the real-time drilling data and the drilling data safety range.
2. The real-time early warning method of stuck drilling accident based on real drilling logging data of claim 1, wherein obtaining drilling data of a plurality of data points comprises:
before the drilling work starts, setting initial drilling data or manually setting the initial data based on the historical data, and taking the set drilling data as an initial random variable; wherein the initial random variables are used to calculate mathematical expectations, variances, and adjust the drilling data safety range using chebyshev inequality.
3. The real-time early warning method of stuck drilling accident based on real drilling logging data of claim 1, wherein obtaining drilling data of a plurality of data points comprises:
collecting drilling data in real time in the drilling process, and taking the collected drilling data as a random variable corresponding to the drilling process; the random variables corresponding to the drilling process are used for calculating mathematical expectations and variances, and adjusting the drilling data safety range by using the chebyshev inequality.
4. The real-time early warning method of stuck drilling events based on real drilling logging data of claim 1 or claim 1, wherein the drilling data at least comprises: hook load data and drilling parameter data sets; and taking hook load data acquired by a plurality of data points as random variables when the change of the drilling parameter data set is within a certain range.
5. The real-time early warning method of stuck drilling accident based on real drilling logging data according to claim 1, wherein the calculating the mathematical expectation and variance of the random variable according to the drilling data of the plurality of data points comprises:
the mathematical expectation of the random variable T is:
the variance is: var (T) =σ 2 ＝E(T-E(T)) 2
Wherein T is a random variable;
e is a mathematical expectation;
T i is the ith random variable;
s is the number of random variables;
p is probability;
var is variance;
sigma is the standard deviation.
6. The real-time early warning method for stuck drilling accidents based on real drilling logging data according to claim 5, wherein the setting of the proportional relation between the first constant and the standard deviation according to the condition of the drilling site comprises:
ε＝Aσ；
wherein ε is a first constant;
a is a proportional relationship;
sigma is the standard deviation.
7. The real-time early warning method of stuck drilling accident based on real drilling logging data of claim 6, further comprising:
and adjusting the interval corresponding to the drilling data safety range by adjusting the proportional relation between the first constant and the standard deviation.
8. The real-time early warning method of stuck drilling accident based on real drilling logging data according to claim 6, wherein determining the drilling data safety range by using chebyshev inequality according to the mathematical expectation and variance of the random variable and the proportional relation between the first constant and the standard deviation comprises:
according to the chebyshev inequality, for a first constant epsilon, epsilon >0, there is the following relationship:
the value of the random variable falls into [ E (T) -epsilon, E (T) +epsilon]Probability outside the interval
Or alternatively, the first and second heat exchangers may be,
the value of the random variable falls into [ E (T) -epsilon, E (T) +epsilon]Probability within an interval
Setting the drilling data safety range as [ E (T) -epsilon, E (T) +epsilon ];
wherein P represents probability;
t is a random variable;
e is a mathematical expectation;
epsilon is a first constant;
var is variance.
9. The real-time early warning method for stuck drilling accidents based on real-time drilling logging data according to claim 8, wherein the real-time drilling data is collected during the drilling process, the real-time early warning for stuck drilling accidents is performed according to the real-time drilling data and the safety range of the drilling data, and the method comprises the following steps:
acquiring random variable data of the next moment according to the real-time drilling data;
when the random variable data falls into the drilling data safety range, judging that the drill sticking does not occur; and when the random variable data does not fall into the drilling data safety range, judging that the drilling sticking risk occurs.
10. Drilling sticking accident real-time early warning device based on real drilling logging data, characterized by comprising:
the data acquisition module is used for acquiring drilling data of a plurality of data points;
the data calculation module is used for calculating the mathematical expectation and variance of the random variable according to the drilling data of the data points;
the proportional relation setting module is used for setting the proportional relation between the first constant and the standard deviation according to the condition of the drilling site;
the safety range calculation module is used for determining the safety range of drilling data by using a Chebyshev inequality according to the mathematical expectation and variance of the random variable and the proportional relation between the first constant and the standard deviation;
and the real-time early warning module is used for acquiring real-time drilling data in the drilling process and carrying out real-time early warning on the stuck drilling accident according to the real-time drilling data and the drilling data safety range.
11. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method of any of claims 1 to 9 when executing the computer program.
12. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program which, when executed by a processor, implements the method of any of claims 1 to 9.
13. A computer program product, characterized in that the computer program product comprises a computer program which, when executed by a processor, implements the method of any of claims 1 to 9.
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