CN-122018378-A - Intelligent regulation and control technology for emergency stop

CN122018378ACN 122018378 ACN122018378 ACN 122018378ACN-122018378-A

Abstract

The invention relates to the field of oil and gas field production, in particular to an intelligent emergency stop regulation and control technology; the technical scheme includes that the emergency stop intelligent regulation technology comprises a data acquisition module, a data preprocessing module, a model construction module, a data analysis module and a control module, original data are projected to a low-dimensional space through positive-negative transformation, main characteristics in the data are extracted, in fault detection, distribution differences of normal data and fault data in the low-dimensional space can be identified through PCA, so that faults can be detected and early warned in time, and the timeliness and accuracy of the emergency stop intelligent regulation technology are improved.

Inventors

REN YANBING
XU WENLONG
REN XIAORONG
SHI MINGXIA
MA SHIQING
ZHANG RUI
ZHAO QIUHUA
HUANG BIN
ZHANG JINSUO
HUANG TIANHU
TIAN TAO
XU ZIQIANG

Assignees

中国石油天然气股份有限公司

Dates

Publication Date: 20260512
Application Date: 20241112

Claims (10)

1. The intelligent regulation and control technology for emergency stop is characterized by comprising the following steps: The data acquisition module is used for acquiring various parameter data in the production process of the oil and gas field in real time by adopting a plurality of groups of sensing equipment; The data preprocessing module is used for preprocessing the data acquired by the data acquisition module, preprocessing the data by adopting data cleaning, denoising and normalization, and normalizing the data; The model construction module is used for carrying out dimension reduction on the preprocessed data by adopting a PCA algorithm, constructing a PCA model, extracting main characteristic variables in the data, and calculating statistics of the variables; The data analysis module is used for projecting the data acquired in real time into a low-dimensional space constructed by the PCA model, calculating statistics of the projected data, comparing the statistics with the statistics of normal data, and judging whether the current data belongs to fault data or not; and the control module is used for triggering the emergency stop instruction when detecting the fault data or detecting that the fault data possibly exist, and cutting off the power supply or the air source of the related equipment through the automatic control equipment so as to prevent the fault from expanding and accidents from happening.
2. The intelligent emergency stop regulation and control technology according to claim 1, wherein the data acquisition module comprises sensor equipment and a data transmission unit, the sensor equipment is used for being installed at a key position of an oil-gas field to monitor parameters to be monitored, and the data transmission unit door is used for transmitting parameter data acquired by the sensor equipment to the data preprocessing module by adopting the Zigbee technology of the Internet of things.
3. The intelligent emergency stop regulation and control technology according to claim 2, wherein the data preprocessing module identifies and deletes or corrects error data, such as numerical values which deviate from a normal range obviously, removes or corrects errors, abnormal values, repeated records and the like in the data through data cleaning, ensures the accuracy and consistency of the data, reduces random errors and noise in the data through data denoising, improves the signal-to-noise ratio of the data, converts the data to the same scale through normalization processing, and eliminates the influence of different scales on an analysis result.
4. The intelligent regulation and control technique for emergency stop according to claim 3, wherein the data preprocessing module comprises the following steps: S101, checking data integrity, identifying and processing missing values, and filling the missing values by using methods such as mean, median, mode or interpolation; s102, identifying, deleting or correcting error data, setting a threshold value, and deleting or correcting data which obviously deviate from a normal range; S103, identifying and deleting the repeated records by using the unique identifier and the data content comparison; s104, selecting a time sequence denoising technology, and removing noise by using a time sequence decomposition method; s106, selecting a Z-score standardization method to perform normalization treatment so that the mean value of each characteristic variable is 0 and the variance is 1, wherein the standardization formula is as follows: ; where X is raw data, μ is mean, σ is standard deviation.
5. The intelligent emergency stop regulation and control technology of claim 4 wherein the model building module performs dimension reduction on the preprocessed data, calculates a covariance matrix of the standardized data, reflects correlation among variables, performs eigenvalue decomposition on the covariance matrix to obtain eigenvalues and eigenvectors, builds a PCA model, extracts main eigenvalues in the data, and calculates statistics of the variables.
6. The intelligent regulation and control technique for emergency stop according to claim 5, wherein the model building module comprises the following steps: s201, presetting m characteristic variables and n samples, and organizing data into an n multiplied by m matrix X; s202, calculating a covariance matrix sigma according to a formula, wherein the calculation formula is as follows: Wherein Is the transposed matrix of X, and the covariance matrix is an m×m symmetric matrix, reflecting the correlation between the feature variables; s203, carrying out feature decomposition on the covariance matrix sigma, and solving a feature value and a corresponding feature vector, wherein the feature value represents the importance of each principal component, namely the variance contribution rate, and the feature vector is the direction of each principal component; S204, selecting the first k principal components according to the magnitude of the characteristic value through a cumulative contribution rate method, namely selecting the first k principal components so that the cumulative variance contribution rate of the first k principal components reaches a certain threshold value; S205, arranging the selected k eigenvectors in columns to form a principal component matrix P, wherein each column of the principal component matrix is a principal component direction vector.
7. The intelligent emergency stop regulation and control technology of claim 6 wherein the data analysis module projects data acquired in real time into a low-dimensional space constructed by the PCA model, main features of the data are reserved, noise and redundant information are effectively removed, the projected data are further used for calculating statistics, such as mean, variance, covariance and the like, the statistics reflect the distribution characteristics and the variation trend of the data, and the statistics are compared with the statistics of normal data to judge whether the current data belongs to fault data.
8. The intelligent regulation and control technique for emergency stop according to claim 7, wherein the data analysis module comprises the following steps: s301, projecting original data X onto a principal component matrix P to obtain dimension-reduced data T=XP; S302, calculating statistics by using the dimension-reduced data T; S303, calculating T2 statistic of the reduced-dimension data T, wherein the statistic reflects the overall change of the data in a principal component space, and the calculation formula is T2=T' T/(n-1), wherein n is the number of samples; S304, calculating SPE statistics which reflect the change of the data in a residual space, namely a part which is not interpreted by a principal component, wherein the calculation formula is SPE=e' e, and e is a residual vector, and e=X-PT; S305, respectively calculating control limits, namely threshold values, of the T2 statistic and the SPE statistic according to the historical normal data, wherein the control limits are determined by setting a certain confidence level; s306, calculating T2 statistic and SPE statistic of the current data in real time, comparing the T2 statistic and SPE statistic with a control limit, and if any statistic exceeds the control limit, considering that the system is likely to be faulty.
9. The intelligent emergency stop regulation and control technology according to claim 8, wherein the control module confirms the authenticity of the fault signal after detecting the fault, eliminates possible false alarm, analyzes the fault characteristics, finds out the variable or principal component which has the greatest contribution to the fault by using a contribution graph and other methods, determines the type and possible reason of the fault by combining the fault characteristics and the analysis result of the contribution graph, immediately starts an emergency stop program after confirming the fault, closes or isolates the fault equipment, and prevents the fault from further expanding.
10. The intelligent regulation and control technique for emergency stop according to claim 9, wherein the control module comprises the following steps: S401, receiving a fault detection signal; s402, verifying the authenticity of a fault signal by comparing historical data with a system log, and eliminating possible false alarms; s403, if the fault signal is confirmed to be true, entering a fault identification and diagnosis process, and if the fault signal is false, recording and notifying related personnel; s404, collecting data before and after the occurrence of faults, including real-time data, historical data and possible system logs; S405, analyzing time sequence characteristics of fault data, such as trend, periodicity and mutation points; s406, converting the fault data into a frequency domain, and analyzing the distribution and the change of each frequency component to identify the characteristic frequency of the fault; S407, extracting fault characteristics such as amplitude change of specific frequency and abnormal modes in time sequence from analysis results; S408, calculating the contribution degree of each variable or principal component to the T2 statistic or SPE statistic according to the PCA model; S409, displaying the contribution degree in a graph form, and using a bar graph or a pie graph to represent the contribution proportion of each variable or main component; S410, identifying the variable or principal component with the largest contribution to the fault according to the contribution graph; S411, matching the extracted fault characteristics with a known fault mode library to identify the type of the fault; S412, deducing possible reasons of the fault by combining fault types, contribution graph analysis and system knowledge; S413, sorting fault types, reasons and analysis processes into diagnostic reports; S414, confirming the fault and diagnosing the potential hazard thereof, and immediately sending an emergency stop instruction to related equipment or systems; S415, according to the instruction, closing or isolating the fault equipment, cutting off the related energy supply, and ensuring that the fault is not further expanded; And S416, monitoring the parking process in real time, ensuring that all equipment is safely stopped, and recording key parameters and states in the parking process.

Description

Intelligent regulation and control technology for emergency stop Technical Field The invention relates to the field of oil and gas field production, in particular to an intelligent emergency stop regulation and control technology. Background The emergency stop control technology for oil and gas field production is an important safety protection measure, aims to cut off the production flow rapidly under emergency conditions and protect production equipment, personnel and environment from damage, and is used for realizing real-time monitoring and quick response to the production process by integrating a Safety Instrument System (SIS) and an emergency stop system (ESD), when the system detects abnormal conditions such as overpressure, overtemperature, leakage, fire and the like, the emergency stop system can be automatically or manually triggered to execute preset cut-off logic and cut off power supply, air source or material supply of related equipment or process flow, so that accidents are prevented from being enlarged, but the data transmission delay and equipment fault reasons of the emergency stop control technology for oil and gas field production under the technology are difficult to acquire and process production data in real time, the timeliness and accuracy of emergency stop are affected, certain limitation exists on the breadth and depth of data analysis, the non-occurrence fault is difficult to be predicted, and partial data under complex working conditions can not be accurately identified and processed, and the system is caused to be misreported or leaked. Disclosure of Invention In order to overcome the problems that in the prior art, the oil-gas field production emergency stop regulation technology has data transmission delay and equipment fault reasons, production data are difficult to acquire and process in real time, timeliness and accuracy of emergency stop are affected, certain limitations exist on the breadth and depth of data analysis, non-occurrence faults are difficult to predict, and data under partial complex working conditions can not be accurately identified and processed, so that system false alarm or missing alarm is caused. The technical scheme of the invention is that the intelligent regulation and control technology for emergency stop comprises the following steps: The data acquisition module is used for acquiring various parameter data in the production process of the oil and gas field in real time by adopting a plurality of groups of sensing equipment; The data preprocessing module is used for preprocessing the data acquired by the data acquisition module, preprocessing the data by adopting data cleaning, denoising and normalization, and normalizing the data; The model construction module is used for carrying out dimension reduction on the preprocessed data by adopting a PCA algorithm, constructing a PCA model, extracting main characteristic variables in the data, and calculating statistics of the variables; The data analysis module is used for projecting the data acquired in real time into a low-dimensional space constructed by the PCA model, calculating statistics of the projected data, comparing the statistics with the statistics of normal data, and judging whether the current data belongs to fault data or not; and the control module is used for triggering the emergency stop instruction when detecting the fault data or detecting that the fault data possibly exist, and cutting off the power supply or the air source of the related equipment through the automatic control equipment so as to prevent the fault from expanding and accidents from happening. Preferably, each item of parameter data in the oil and gas field production process is acquired in real time through a data acquisition module by adopting a plurality of groups of sensing equipment, the data acquired by the data acquisition module is preprocessed through a data preprocessing module, the data is preprocessed through data cleaning, denoising and normalization, the data is standardized, the preprocessed data is subjected to dimension reduction processing through a model construction module by adopting a PCA algorithm, a PCA model is constructed, main characteristic variables in the data are extracted, statistics of the variables are calculated, the data acquired in real time are projected into a low-dimensional space constructed by the PCA model through a data analysis module, the statistics of the projected data are calculated and compared with the statistics of normal data, whether the current data belongs to fault data is judged, an emergency stop instruction is triggered when the fault data is detected or possible fault data is detected through a control module, and the power supply or the air source of related equipment is cut off through an automatic control device, so that fault expansion and accident are prevented. Preferably, the data acquisition module comprises a sensor device and a data transmission uni