Well drilling engineering early warning method and system

Abstract

The invention relates to the technical field of engineering early warning, in particular to a drilling engineering early warning method and system, and the method comprises the following steps: collecting a plurality of operation parameters of drilling equipment in real time based on a drilling engineering environment, screening the data, carrying out the comparative analysis of the parameters, evaluating the deviation between the current operation parameter and the conventional operation data, and carrying out the early warning of the drilling engineering. And obtaining equipment operation deviation information. According to the method, the operation parameters of the drilling equipment are collected and processed, key parameters such as the drill bit speed and torque are monitored in real time, deviation with conventional data is found in time, the abnormal condition of the equipment can be quantitatively evaluated by analyzing the frequency and duration of the operation deviation of the equipment, and the stratum data aggregation and trend analysis are combined. The safety of drilling operation is enhanced, the stability of a drilling site can be evaluated by extracting key features such as stratum density and rock hardness, risk classification is performed accordingly, risk early warning is achieved, and potential accidents are effectively avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering early warning, and in particular to a drilling engineering early warning method and system. Background Art

[0002] The field of engineering early warning technology mainly involves the development and application of various methods and systems to predict and prevent events that may have a negative impact on engineering operations. The core of this technology field is to identify potential risks in advance through real-time monitoring, data analysis and model prediction, thereby improving engineering safety and efficiency. Engineering early warning technology is widely used in civil, petroleum, mining and other industries, including detailed analysis of structural health monitoring, environmental change impact assessment, and risk management during operations. Technological development in this field focuses on improving prediction accuracy, reducing delays and optimizing response strategies to ensure that actions can be taken quickly and effectively when potential risks arise.

[0003] Among them, the drilling engineering early warning method aims to prevent accidents and equipment failures during drilling operations by identifying potential risks and problems in advance. This method usually involves monitoring key parameters in the drilling process, such as drilling speed, pressure, temperature, etc., and analyzing these data to predict possible problems. Its main purpose is to reduce downtime, avoid expensive equipment damage, and improve drilling efficiency and safety. Through real-time data analysis, the drilling team can obtain key information in a timely manner and adjust operations when necessary, thereby optimizing resource utilization and ensuring the safety of operators and the environment.

[0004] Traditional early warning methods have certain limitations in real-time data analysis and risk prediction. In terms of data processing speed and prediction accuracy, they are not enough to cope with the rapidly changing drilling environment, resulting in insufficient response when an emergency occurs and inability to effectively prevent accidents. Traditional methods lack sufficient depth and accuracy in formation data analysis, making it difficult to achieve customized risk assessment for different formation conditions, resulting in equipment damage and personnel safety accidents caused by inaccurate risk assessment during drilling operations. For example, continuing drilling without timely identifying poor formation stability can lead to overload of drilling equipment or even accidents. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a drilling engineering early warning method and system.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: a drilling engineering early warning method, comprising the following steps: S1: Based on the drilling engineering environment, multiple operating parameters of drilling equipment are collected in real time, the data is screened and processed, and the parameters are compared and analyzed to evaluate the deviation between the current operating parameters and the conventional operating data, and obtain the equipment operation deviation information; S2: Based on the equipment operation deviation information, the abnormality degree of the drilling equipment operation is evaluated according to the size, duration and occurrence frequency of the operation deviation, and the abnormality information of the drilling equipment is obtained; S3: Based on the formation data of the drilling area, extract the formation density, rock type and drilling speed data, perform data aggregation and trend analysis, extract the core features of the data, evaluate the stability level of the current drilling formation, and obtain the formation stability index; S4: Based on the formation stability index, the identified formation data is risk-classified to identify dangerous formations that may cause drilling accidents, a corresponding risk level mark is assigned to each risk area, and a corresponding warning is issued when the formation changes to obtain a formation warning signal; S5: Based on the abnormal information of the drilling equipment and the formation warning signal, combined with historical accident data and the current operating environment, the risk level of the overall drilling operation is evaluated, corresponding warning measures are implemented according to the risk level, the warning response level is adjusted, and the drilling warning result is obtained.

[0007] As a further solution of the present invention, the equipment operation deviation information includes speed abnormality index, torque fluctuation index and flow variation index, the drilling equipment abnormality information includes torque excess warning, speed abnormality warning and pressure out of control warning, the formation stability index specifically includes formation density rating, rock hardness classification, drilling rate assessment, the formation stability index includes fault approach warning, cavity existence warning and formation slip warning, and the formation warning signal includes an overall risk score, recommended response measures and warning level.

[0008] As a further solution of the present invention, based on the drilling engineering environment, multiple operating parameters of the drilling equipment are collected in real time, the data are screened and processed, and the parameters are compared and analyzed to evaluate the deviation between the current operating parameters and the conventional operating data. The specific steps of obtaining the equipment operation deviation information are as follows: S101: Based on the drilling engineering environment, real-time monitoring and recording of the operating data of the drilling equipment, including measuring the rotation speed of the drill bit, recording the magnitude of the torque, the flow rate of the pump and the value of the drilling pressure, and obtaining the real-time monitoring equipment operating parameters; S102: Based on the real-time monitored equipment operating parameters, remove atypical operating data by comparing with preset data thresholds to obtain filtered parameter data; S103: Based on the filtered parameter data, the current operating parameters are compared with the normal operating data, and the degree of deviation is identified by calculating the difference and the ratio to obtain the equipment operation deviation information.

[0009] As a further solution of the present invention, based on the equipment operation deviation information, the abnormality degree of the drilling equipment operation is evaluated according to the size, duration and frequency of the operation deviation, and the steps of obtaining the abnormal information of the drilling equipment are specifically as follows: S201: Based on the equipment operation deviation information, detect data points where the deviation exceeds a preset threshold, record abnormal data points, record corresponding parameter values ​​and occurrence time, and obtain abnormal data information; S202: Based on the abnormal data information, statistically analyze the difference data, calculate the abnormal duration and occurrence frequency, analyze the time distribution and frequency of the differentiated abnormal parameters, and obtain deviation statistical results; S203: Based on the deviation statistical results, the abnormality of the drilling equipment is evaluated according to the size, duration and occurrence frequency of the deviation, and the abnormality information of the drilling equipment is obtained.

[0010] As a further solution of the present invention, the formula for evaluating the abnormality degree of the drilling equipment is: ; in, is the device abnormality level, Represents the size of the deviation, represents the duration of the deviation, represents the frequency of deviation, , , is the weight coefficient.

[0011] As a further solution of the present invention, based on the formation data of the drilling area, the formation density, rock type and drilling speed data are extracted, data aggregation and trend analysis are performed, core features of the data are extracted, and the stability level of the current drilling formation is evaluated. The steps of obtaining the formation stability index are specifically as follows: S301: based on the stratigraphic data of the drilling area, extracting data records of the drilling area from the geological database, including extracting density data of the stratigraphic formation, rock classification information and drilling speed, to obtain a basic stratigraphic data set; S302: Based on the basic stratigraphic data set, aggregating and trending the data, including aggregating the stratigraphic density and rock type by drilling point, calculating the average stratigraphic density and rock hardness index of each drilling point, and analyzing the data change trend to obtain stratigraphic characteristic analysis results; S303: Based on the formation characteristic analysis results, according to the trends of average formation density and rock hardness index, the formation stability is evaluated to obtain a formation stability index.

[0012] As a further solution of the present invention, based on the formation stability index, the identified formation data is risk classified, the dangerous formations that may cause drilling accidents are identified, a corresponding risk level mark is assigned to each risk area, and a corresponding warning is issued when the formation changes. The steps of obtaining the formation warning signal are specifically as follows: S401: Based on the formation stability index, risk assessment is performed on each formation data point, and formations with differentiated risk levels are identified by comparing the formation stability with a preset safety threshold, thereby obtaining a formation risk classification result; S402: Based on the formation risk classification result, extract high-risk formations from the risk classification result, analyze the types and frequencies of drilling accidents caused by the formations, assign risk level marks to high-risk areas, identify potential dangerous formations, and obtain high-risk formation marks; S403: Based on the high-risk formation marker, when a high-risk formation is monitored, an early warning signal is automatically triggered, a real-time alarm is sent to the operation team, and the risk level is displayed to obtain a formation early warning signal.

[0013] As a further solution of the present invention, based on the abnormal information of the drilling equipment and the formation warning signal, combined with the historical accident data and the current operating environment, the risk level of the overall drilling operation is evaluated, corresponding warning measures are implemented according to the risk level, and the warning response level is adjusted. The steps of obtaining the drilling warning result are specifically as follows: S501: Based on the drilling equipment abnormality information and the formation early warning signal, extract accident data associated with the current drilling equipment abnormality and formation risk from the database, identify common accident modes and frequencies, and obtain historical accident analysis results; S502: Based on the historical accident analysis results, assess the risk of the current operating environment, assess the risk level of the overall drilling operation, and obtain an operation risk assessment result; S503: Based on the operation risk assessment results, early warning measures are adjusted according to the risk level, including comparing with the preset risk response guidelines, adjusting the early warning response level, adapting to the current risk situation, implementing corresponding safety measures and early warning strategies, and obtaining drilling early warning results.

[0014] As a further solution of the present invention, the formula for evaluating the risk level of the overall drilling operation is: ; in, is the operational risk level, Represents the abnormal level of the device. Represents the formation risk level, Represents the frequency and severity scores of historical device anomalies, represents the frequency and severity scores of historical formation risks, and is the weight coefficient.

[0015] A drilling engineering early warning system, the drilling engineering early warning system is used to execute the above-mentioned drilling engineering early warning method, the system comprises: The equipment anomaly assessment module collects multiple operating parameters of drilling equipment in real time based on the drilling engineering environment, screens and processes the data, and compares and analyzes the parameters to assess the deviation between the current operating parameters and the conventional operating data. Based on the size, duration and frequency of the operating deviation, the module assesses the degree of abnormality of the drilling equipment operation and obtains abnormal information of the drilling equipment. The formation stability analysis module extracts formation density, rock type and drilling speed data based on the formation data of the drilling area, performs data aggregation and trend analysis, extracts core features of the data, evaluates the stability level of the current drilling formation, and obtains the formation stability index; The formation early warning assessment module classifies the identified formation data into risk categories based on the formation stability index, assigns a corresponding risk level mark to each risk area by comparing it with the set formation safety threshold, and issues a corresponding early warning when the formation changes, thereby obtaining a formation early warning signal; The drilling early warning implementation module evaluates the risk level of the overall drilling operation based on the abnormal information of the drilling equipment and the formation early warning signal, combined with historical accident data and the current operating environment, implements corresponding early warning measures according to the risk level, adjusts the early warning response level, and obtains the drilling early warning result.

[0016] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, by collecting and processing the operating parameters of the drilling equipment, real-time monitoring of key parameters including drill bit speed and torque can be carried out, and deviations from conventional data can be discovered immediately, so that the drilling team can intervene before the problem becomes serious. By analyzing the frequency and duration of equipment operation deviations, the abnormal condition of the equipment can be quantitatively evaluated, effectively reducing downtime and equipment failure rate. Combined with the aggregation and trend analysis of formation data, the safety of drilling operations is enhanced. By extracting key features such as formation density and rock hardness, the stability of the drilling site can be evaluated, and risk classification can be carried out accordingly to achieve risk warning and effectively avoid the occurrence of potential accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 It is a schematic diagram of the workflow of the present invention; Figure 2 This is a detailed flow chart of S1 of the present invention; Figure 3 This is a detailed flow chart of S2 of the present invention; Figure 4 This is a detailed flow chart of S3 of the present invention; Figure 5 This is a detailed flow chart of S4 of the present invention; Figure 6 This is a detailed flow chart of S5 of the present invention; Figure 7 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0019] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0020] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0021] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same. "of", "corresponding, relevant" and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same.

[0022] In the embodiments of the present invention, sometimes a subscript such as W1 may be written as a non-subscript such as W1. When the difference is not emphasized, the meanings to be expressed are the same.

[0023] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0024] See also Figure 1 The present invention provides a technical solution: a drilling engineering early warning method, comprising the following steps: S1: Based on the drilling engineering environment, multiple operating parameters of drilling equipment are collected in real time, including drill bit speed, torque, pump flow and drilling pressure, the data is screened and processed, and the parameters are compared and analyzed to evaluate the deviation between the current operating parameters and the conventional operating data, and obtain the equipment operation deviation information; S2: Based on the equipment operation deviation information, detect and record abnormal data points, count the duration of equipment operation deviation, and analyze the frequency of equipment operation deviation. According to the size, duration and frequency of operation deviation, evaluate the abnormal degree of drilling equipment operation and obtain drilling equipment abnormal information; S3: Based on the formation data of the drilling area, extract the formation density, rock type and drilling speed data, perform data aggregation and trend analysis, extract the core features of the data, including extracting the average density of the formation and the rock hardness index, evaluate the stability level of the current drilling formation, and obtain the formation stability index; S4: Based on the formation stability index, the identified formation data is classified into risk categories, and by comparing with the set formation safety threshold, the dangerous formations that may cause drilling accidents are identified, and corresponding risk level marks are assigned to each risk area. When the formation changes, corresponding warnings are issued to obtain formation warning signals; S5: Based on the abnormal information of drilling equipment and formation warning signals, combined with historical accident data and the current operating environment, the risk level of the overall drilling operation is evaluated, and corresponding warning measures are implemented according to the risk level, and the warning response level is adjusted to obtain the drilling warning results.

[0025] Equipment operation deviation information includes speed abnormality index, torque fluctuation index and flow variation index. Drilling equipment abnormality information includes torque excess warning, speed abnormality warning and pressure out of control warning. Formation stability indicators specifically include formation density rating, rock hardness classification and drilling rate assessment. Formation stability indicators include fault approach warning, cavity existence warning and formation slip warning. Formation warning signals include overall risk score, recommended response measures and warning level.

[0026] See also Figure 2 , based on the drilling engineering environment, multiple operating parameters of the drilling equipment are collected in real time, including drill bit speed, torque, pump flow and drilling pressure, the data are screened and processed, and the parameters are compared and analyzed to evaluate the deviation between the current operating parameters and the conventional operating data. The specific steps for obtaining the equipment operation deviation information are as follows: S101: Based on the drilling engineering environment, real-time monitoring and recording of the operating data of the drilling equipment, including measuring the rotation speed of the drill bit, recording the magnitude of the torque, the flow rate of the pump and the value of the drilling pressure, and obtaining the real-time monitoring equipment operating parameters; Based on the drilling engineering environment, by installing high-precision sensors on key parts of the drill bit and drilling rig, the sensors can measure and transmit dynamic parameters such as the drill bit's rotation speed and torque. The data acquisition system will collect the data from the sensors in real time. The system usually includes a data recorder and a data transmission device to ensure that all key operating data is accurately recorded and can be used for subsequent analysis. In this way, not only the drill bit's rotation speed is recorded, but also multiple important parameters such as torque, pump flow and drilling pressure are recorded. Such data collection and recording provides a complete real-time data source for subsequent data analysis, thereby achieving comprehensive control of the operating status of the drilling equipment and obtaining real-time monitoring of equipment operating parameters.

[0027] S102: Based on the real-time monitored equipment operating parameters, atypical operating data is removed by comparing with preset data thresholds to obtain filtered parameter data; Based on the real-time monitoring of equipment operating parameters, preliminary screening is performed according to preset data thresholds. The thresholds are set according to the design performance of the equipment and past operating experience. The purpose is to exclude data records that are obviously abnormal or erroneous. For example, if the reading of a parameter exceeds the upper or lower threshold, the system will automatically mark it as an abnormality and remove it from the normal data set. Subsequently, data processing includes the use of statistical methods to identify and exclude atypical data fluctuations, such as calculating the standard deviation and mean of the data to exclude data points that deviate too far from the average level. Through these steps, the screened and cleaned data is more representative and accurate, which helps to more accurately reflect the actual operating status of the equipment and obtain the screened parameter data.

[0028] S103: Based on the filtered parameter data, the current operating parameters are compared with the normal operating data, and the degree of deviation is identified by calculating the difference and the ratio to obtain the equipment operation deviation information; Based on the screened parameter data, the current operating parameters are compared and analyzed with the historical data. By loading the historical operating data set, which usually includes the historical performance data of the same equipment under similar operating conditions, the difference and ratio between the current data and the historical data are calculated. The calculation process includes the use of difference analysis and ratio calculation methods, such as calculating the deviation ratio between the current torque data and the historical average torque. This comparison can reveal the degree of deviation between the current equipment operating state and the typical operating mode, and form deviation information of equipment operation.

[0029] See also Figure 3 Based on the equipment operation deviation information, detect and record abnormal data points, count the duration of equipment operation deviation, and analyze the frequency of equipment operation deviation. According to the size, duration and frequency of operation deviation, evaluate the abnormal degree of drilling equipment operation. The specific steps for obtaining drilling equipment abnormal information are as follows: S201: Based on the equipment operation deviation information, detect the data point where the deviation exceeds the preset threshold, record the abnormal data point, record the corresponding parameter value and the occurrence time, and obtain the abnormal data information; Based on the equipment operation deviation information, the real-time monitoring module automatically detects data points in all operating parameters whose deviations exceed the preset threshold. The preset threshold is determined according to the design specifications and safe operation standards of the drilling equipment. During the detection process, whenever a data point exceeds the threshold, an alarm is triggered immediately and the specific parameter value and occurrence time of the data point are automatically recorded. These recorded data points are marked for subsequent query and analysis to obtain abnormal data information.

[0030] S202: Based on the abnormal data information, statistically analyze the difference data, calculate the abnormal duration and occurrence frequency, analyze the time distribution and frequency of the differentiated abnormal parameters, and obtain the deviation statistical results; Based on the abnormal data information, the process of statistical analysis of the data includes calculating the duration and frequency of the anomaly, sorting and classifying the timestamp marks of each recorded abnormal data point, and then calculating the duration of each abnormal event, that is, the time interval from the start to the end of the anomaly, and counting the frequency of occurrence of various types of anomalies, that is, the number of times the same type of anomaly occurs within a given time period. The statistical operation is completed through an automated data processing script to obtain the statistical results of the deviation.

[0031] S203: Based on the deviation statistical results, the abnormality of the drilling equipment is evaluated according to the size, duration and frequency of the deviation, and the abnormality information of the drilling equipment is obtained.

[0032] The formula for evaluating the abnormality of drilling equipment is: ; in, is the device abnormality level, Represents the size of the deviation, represents the duration of the deviation, represents the frequency of deviation, , , is the weight coefficient.

[0033] formula: ; Parameter details and how to obtain them: Represents the deviation size, that is, the absolute value of the difference between the current parameter and the historical average parameter. This is obtained by real-time monitoring of the equipment's operating parameters (such as drill speed, torque, etc.) and comparing them with historical data.

[0034] The duration of the deviation is the total time, in minutes, that the deviation is outside the normal range. This is measured by a real-time data analysis system that records the time from the start to the end of the deviation.

[0035] Represents the frequency of deviation, that is, the number of deviations that occur per unit time, which is usually measured in number of occurrences per hour. It is determined by counting the number of deviations that occur within a certain period of time.

[0036] , , It is the weight coefficient of each factor (deviation size, duration and frequency), which is usually set based on historical accident data and risk analysis results, and reflects the influence of different factors on the assessment of equipment operating status.

[0037] Calculation example: The following measured values ​​are set: Historical average torque value Nm, current torque value Nm, deviation size Nm, deviation duration Minutes, deviation frequency times / hour, the weight coefficient is: (weight of the deviation size), (weight of duration), (Weight of frequency).

[0038] Calculated: ; ;; Calculation results , indicating that within a given monitoring period, according to the set weight, the abnormality level of the drilling equipment is 16.9. This high value indicates that the equipment may have serious operational abnormalities and requires further inspection or maintenance. This value can be used to compare the historical abnormality level of the equipment and evaluate whether the operating condition of the equipment has improved or deteriorated.

[0039] See also Figure 4 Based on the formation data of the drilling area, the formation density, rock type and drilling speed data are extracted, data aggregation and trend analysis are performed, and core features of the data are extracted, including extracting the average density of the formation and the rock hardness index, and evaluating the stability level of the current drilling formation. The specific steps for obtaining the formation stability index are as follows: S301: based on the stratigraphic data of the drilling area, extracting data records of the drilling area from the geological database, including extracting density data of the stratigraphic formation, rock classification information and drilling speed, to obtain a basic stratigraphic data set; Based on the stratigraphic data of the drilling area, a query request is submitted to the database to extract the relevant stratigraphic data of the specific drilling area. The query process specifies in detail the type of data to be extracted, including the density data of the formation, the classification information of the rock, and the relevant drilling speed. In addition, the scope and conditions of data extraction are set to ensure that the acquired data accurately corresponds to the current drilling location. The database performs data retrieval according to the request and filters out the records that meet the conditions from the data set. The records are then summarized and organized to obtain the basic stratigraphic data set.

[0040] S302: Based on the basic stratigraphic data set, data aggregation and trend analysis are performed, including aggregating the stratigraphic density and rock type by drilling point, calculating the average stratigraphic density and rock hardness index of each drilling point, and analyzing the data change trend to obtain stratigraphic characteristic analysis results; Based on the basic stratigraphic data set, data analysis software is used to aggregate each data item in the data set, especially to classify and summarize the stratigraphic density and rock type according to different drilling points. Subsequently, the average stratigraphic density and rock hardness index of each drilling point are calculated. The calculation is completed by statistical analysis tools, which can handle complex data operations and provide accurate results. The analysis software performs trend analysis on the aggregated data and displays the changing trend of the data through graphical and numerical methods, including the use of regression analysis and time series analysis techniques to evaluate the changes of data over time. The analysis helps to determine the key characteristics of the stratigraphic data, such as the changing laws of density and hardness, and obtain the stratigraphic characteristic analysis results.

[0041] S303: Based on the formation characteristic analysis results, the formation stability is evaluated according to the trend of the average formation density and the rock hardness index to obtain a formation stability index; Based on the results of formation characteristic analysis, the average formation density and rock hardness index obtained by analysis are compared with the historical data of formation stability. The evaluation is based on the average formation density and rock hardness index in the formation characteristic analysis results. A stability evaluation model, such as a statistically based deviation analysis method, is used to evaluate the stability of the formation. The model takes into account the trends of the formation density and hardness index, including variance and standard deviation, to determine the overall stability status of the formation and generate a formation stability index.

[0042] See also Figure 5 Based on the formation stability index, the identified formation data is classified into risk categories. By comparing with the set formation safety threshold, the dangerous formations that may cause drilling accidents are identified. A corresponding risk level mark is assigned to each risk area, and a corresponding warning is issued when the formation changes. The specific steps for obtaining the formation warning signal are as follows: S401: Based on the formation stability index, risk assessment is performed on each formation data point, and formations with differentiated risk levels are identified by comparing the formation stability with a preset safety threshold, thereby obtaining a formation risk classification result; Based on the formation stability index, comparison is made through preset safety thresholds, which are set according to the historical data of formation stability and drilling safety standards. Formation data points with stability indicators lower than the safety thresholds are automatically identified and classified according to risk levels. Each category represents a different risk level, such as low risk, medium risk and high risk. The classification process is automatically executed through algorithms to ensure that all risk levels are quickly and accurately classified to obtain formation risk classification results.

[0043] S402: Based on the formation risk classification results, extract high-risk formations from the risk classification results, analyze the types and frequencies of drilling accidents caused by the formations, assign risk level marks to high-risk areas, identify potential dangerous formations, and obtain high-risk formation marks; Based on the formation risk classification results, all formation data points classified as high-risk are screened, and the specific data of these formations are analyzed, including formation stability indicators and drilling records, in order to analyze the formation characteristics that may lead to drilling accidents, such as excessive rock hardness or uneven formation density, etc., calculate the types and frequency of drilling accidents in high-risk formations, and assign corresponding risk level marks to each high-risk formation. The marks reflect the potential degree of danger of the formation, and high-risk formation marks are obtained.

[0044] S403: Based on the high-risk formation marker, when a high-risk formation is monitored, an early warning signal is automatically triggered, a real-time alarm is sent to the operation team, and the risk level is displayed to obtain a formation early warning signal; Based on high-risk formation markers, when drilling activities approach or reach these high-risk formations, early warning signals are automatically triggered. The generation of early warning signals is controlled by risk management software, which sends real-time alerts to the operating team. The alerts include detailed information on the risk level and related formations so that team members can quickly take necessary safety measures. In addition, the alarm information is also displayed directly to the operating personnel through the display screen of the control center, ensuring that all relevant personnel can understand and respond to potential risks in a timely manner and receive formation early warning signals.

[0045] See also Figure 6 Based on the abnormal information of drilling equipment and the formation warning signal, combined with the historical accident data and the current operating environment, the risk level of the overall drilling operation is evaluated, and the corresponding warning measures are implemented according to the risk level, and the warning response level is adjusted. The specific steps to obtain the drilling warning results are as follows: S501: Based on the abnormal information of drilling equipment and the formation warning signal, the accident data associated with the current abnormality of drilling equipment and the formation risk are extracted from the database, the common accident patterns and frequencies are identified, and the historical accident analysis results are obtained; Based on the abnormal information of drilling equipment and the formation warning signal, a query is initiated from the integrated database. The goal is to retrieve the historical accident data associated with the abnormal records and formation warnings of the current drilling equipment. The query process uses advanced query statements to ensure accurate matching of relevant parameters, such as equipment abnormality type, formation risk level and accident occurrence time, etc. The data is processed and analyzed to identify accident types with high frequency and consistent patterns. This analysis is achieved through data mining technology, including cluster analysis and frequency statistics, which helps to reveal common patterns and potential related factors of accidents. The analysis process ensures the comprehensiveness of the data and the accuracy of the analysis, and obtains the results of historical accident analysis.

[0046] S502: Based on the historical accident analysis results, the risk of the current operating environment is evaluated, the risk level of the overall drilling operation is evaluated, and the operation risk assessment result is obtained; The formula for assessing the risk level of the overall drilling operation is: ; in, is the operational risk level, Represents the abnormal level of the device. Represents the formation risk level, Represents the frequency and severity scores of historical device anomalies, represents the frequency and severity scores of historical formation risks, and is the weight coefficient.

[0047] The formula is: ; Parameter details and how to obtain them: Represents the abnormal level of the device, obtained through the previous steps.

[0048] It represents the level of formation risk and is determined by analyzing the formation data (such as formation density and rock type) of the drilling area.

[0049] Represents the frequency and severity score of historical equipment anomalies, which is obtained from the equipment's historical operation records and accident data, reflecting the frequency of past equipment failures and their impact on operations.

[0050] A frequency and severity score representing historical formation risk, also based on historical data analysis, indicates the frequency of unstable formation conditions and the potential impact on drilling operations.

[0051] and It is a weight coefficient, which is adjusted according to the risk management strategy and historical accident impact analysis to determine the relative importance of equipment abnormality and formation risk in the overall risk assessment.

[0052] Calculation example: Set the following parameters: Equipment abnormality level , formation risk level , historical device anomaly frequency and severity scores , Historical formation risk frequency and severity scores , weight , weight .

[0053] Substituting these values ​​into the formula we get: ; Calculation results The overall risk level of drilling operations is 126. This high value indicates that there are significant operational risks and appropriate preventive or mitigation measures need to be taken. This score helps decision makers understand how different risk factors jointly affect the safety of operations, so as to develop more effective risk management strategies.

[0054] S503: Based on the operation risk assessment results, the early warning measures are adjusted according to the risk level, including comparing with the preset risk response guidelines, adjusting the early warning response level, adapting to the current risk situation, implementing corresponding safety measures and early warning strategies, and obtaining drilling early warning results; Based on the results of the operational risk assessment, the early warning response level is adjusted according to the preset risk response guidelines, and the corresponding safety measures and early warning strategies are output according to the risk level. The strategies include equipment operation restrictions, work area restrictions and necessary safety training. The adjustment process ensures the timeliness and appropriateness of the response measures. Through these operations, the system implements specific safety measures and early warning strategies that are adapted to the current risk situation, thereby obtaining drilling early warning results.

[0055] See also Figure 7 , a drilling engineering early warning system, the drilling engineering early warning system is used to execute the above-mentioned drilling engineering early warning method, the system comprises: The equipment anomaly assessment module collects multiple operating parameters of drilling equipment in real time based on the drilling engineering environment, screens and processes the data, and compares and analyzes the parameters to assess the deviation between the current operating parameters and the conventional operating data. Based on the size, duration and frequency of the operating deviation, the module assesses the degree of abnormality of the drilling equipment operation and obtains abnormal information of the drilling equipment. The formation stability analysis module extracts formation density, rock type and drilling speed data based on the formation data of the drilling area, performs data aggregation and trend analysis, extracts core features of the data, evaluates the stability level of the current drilling formation, and obtains the formation stability index; The formation early warning assessment module classifies the identified formation data into risk categories based on the formation stability index, and assigns corresponding risk level marks to each risk area by comparing it with the set formation safety threshold. It also issues corresponding early warnings when the formation changes, and obtains formation early warning signals. The drilling early warning implementation module evaluates the risk level of the overall drilling operation based on abnormal information of drilling equipment and formation early warning signals, combined with historical accident data and the current operating environment, implements corresponding early warning measures according to the risk level, adjusts the early warning response level, and obtains drilling early warning results.

[0056] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0057] In the present invention, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0058] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0059] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0060] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described equipment, devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0061] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0062] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0063] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0064] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0065] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A drilling engineering early warning method, characterized in that: The following steps are involved: Based on the drilling engineering environment, multiple operating parameters of drilling equipment are collected in real time, the data is screened and processed, and the parameters are compared and analyzed to evaluate the deviation between the current operating parameters and the conventional operating data, and obtain the equipment operation deviation information; Based on the equipment operation deviation information, the abnormality degree of the drilling equipment operation is evaluated according to the size, duration and occurrence frequency of the operation deviation, and the drilling equipment abnormality information is obtained; Based on the formation data of the drilling area, the formation density, rock type and drilling speed data are extracted, data aggregation and trend analysis are performed, the core features of the data are extracted, the stability level of the current drilling formation is evaluated, and the formation stability index is obtained; Based on the formation stability index, the identified formation data is risk-classified to identify dangerous formations that may cause drilling accidents, a corresponding risk level mark is assigned to each risk area, and a corresponding warning is issued when the formation changes to obtain a formation warning signal; Based on the abnormal information of the drilling equipment and the formation warning signal, combined with historical accident data and the current operating environment, the risk level of the overall drilling operation is evaluated, corresponding warning measures are implemented according to the risk level, the warning response level is adjusted, and the drilling warning result is obtained.

2. The drilling engineering early warning method according to claim 1, characterized in that: The equipment operation deviation information includes speed abnormality index, torque fluctuation index and flow variation index; the drilling equipment abnormality information includes torque excess warning, speed abnormality warning and pressure out of control warning; the formation stability indicators specifically include formation density rating, rock hardness classification and drilling rate assessment; the formation stability indicators include fault approach warning, cavity existence warning and formation slip warning; the formation warning signal includes overall risk score, recommended response measures and warning level.

3. The drilling engineering early warning method according to claim 1, characterized in that: Based on the drilling engineering environment, multiple operating parameters of drilling equipment are collected in real time, the data is screened and processed, and the parameters are compared and analyzed to evaluate the deviation between the current operating parameters and the conventional operating data. The specific steps to obtain the equipment operation deviation information are as follows: Based on the drilling engineering environment, real-time monitoring and recording of drilling equipment operating data, including measuring the rotation speed of the drill bit, recording the torque, pump flow and drilling pressure values, to obtain real-time monitoring of equipment operating parameters; Based on the real-time monitored equipment operating parameters, by comparing with preset data thresholds, atypical operating data is removed to obtain filtered parameter data; Based on the filtered parameter data, the current operating parameters are compared with the conventional operating data, and the degree of deviation is identified by calculating the difference and ratio to obtain the equipment operation deviation information.

4. The drilling engineering early warning method according to claim 1, characterized in that: Based on the equipment operation deviation information, the abnormality degree of the drilling equipment operation is evaluated according to the size, duration and frequency of the operation deviation, and the steps of obtaining the abnormal information of the drilling equipment are specifically as follows: Based on the equipment operation deviation information, detect data points where the deviation exceeds a preset threshold, record abnormal data points, record corresponding parameter values ​​and occurrence time, and obtain abnormal data information; Based on the abnormal data information, statistical analysis is performed on the difference data, the abnormal duration and occurrence frequency are calculated, and the time distribution and frequency of the differentiated abnormal parameters are analyzed to obtain deviation statistical results; Based on the deviation statistical results, the abnormality degree of the drilling equipment is evaluated according to the size, duration and occurrence frequency of the deviation, and the abnormality information of the drilling equipment is obtained.

5. The drilling engineering early warning method according to claim 4, characterized in that: The formula for evaluating the abnormality of drilling equipment is: ； in, is the device abnormality level, Represents the size of the deviation, represents the duration of the deviation, represents the frequency of deviation, , , is the weight coefficient.

6. The drilling engineering early warning method according to claim 1, characterized in that: Based on the formation data of the drilling area, the formation density, rock type and drilling speed data are extracted, data aggregation and trend analysis are performed, the core features of the data are extracted, and the stability level of the current drilling formation is evaluated. The specific steps for obtaining the formation stability index are as follows: Based on the stratigraphic data of the drilling area, data records of the drilling area are extracted from the geological database, including density data of the strata, classification information of the rocks and the drilling speed, to obtain a basic stratigraphic data set; Based on the basic stratigraphic data set, data aggregation and trend analysis are performed, including aggregating stratigraphic density and rock type by drilling point, calculating the average stratigraphic density and rock hardness index of each drilling point, and analyzing the data change trend to obtain stratigraphic characteristic analysis results; Based on the formation characteristic analysis results, the stability of the formation is evaluated according to the trends of the average formation density and the rock hardness index to obtain a formation stability index.

7. The drilling engineering early warning method according to claim 1, characterized in that: Based on the formation stability index, the identified formation data is risk classified to identify dangerous formations that may cause drilling accidents, a corresponding risk level mark is assigned to each risk area, and a corresponding warning is issued when the formation changes. The specific steps of obtaining the formation warning signal are as follows: Based on the formation stability index, a risk assessment is performed on each formation data point, and formations with differentiated risk levels are identified by comparing the formation stability with a preset safety threshold, thereby obtaining a formation risk classification result; Based on the formation risk classification results, extract high-risk formations from the risk classification results, analyze the types and frequencies of drilling accidents caused by the formations, assign risk level marks to high-risk areas, identify potential dangerous formations, and obtain high-risk formation marks; Based on the high-risk formation marker, when a high-risk formation is monitored, an early warning signal is automatically triggered, a real-time alarm is sent to the operation team, and the risk level is displayed to obtain a formation early warning signal.

8. The drilling engineering early warning method according to claim 1, characterized in that: Based on the abnormal information of the drilling equipment and the formation warning signal, combined with the historical accident data and the current operating environment, the risk level of the overall drilling operation is evaluated, corresponding warning measures are implemented according to the risk level, and the warning response level is adjusted. The specific steps for obtaining the drilling warning result are: Based on the drilling equipment abnormality information and formation early warning signals, accident data associated with current drilling equipment abnormality and formation risk are extracted from the database, common accident modes and frequencies are identified, and historical accident analysis results are obtained; Based on the historical accident analysis results, the risk of the current operating environment is evaluated, the risk level of the overall drilling operation is evaluated, and the operation risk assessment result is obtained; Based on the operational risk assessment results, early warning measures are adjusted according to the risk level, including comparing with the preset risk response guidelines, adjusting the early warning response level, adapting to the current risk situation, implementing corresponding safety measures and early warning strategies, and obtaining drilling early warning results.

9. The drilling engineering early warning method according to claim 8, characterized in that: The formula for assessing the risk level of the overall drilling operation is: ； in, is the operational risk level, Represents the abnormal level of the device. Represents the formation risk level, Represents the frequency and severity scores of historical device anomalies, represents the frequency and severity scores of historical formation risks, and is the weight coefficient.

10. A drilling engineering early warning system, characterized in that: According to the drilling engineering early warning method according to any one of claims 1 to 9, the system comprises: The equipment anomaly assessment module collects multiple operating parameters of drilling equipment in real time based on the drilling engineering environment, screens and processes the data, and compares and analyzes the parameters to assess the deviation between the current operating parameters and the conventional operating data. Based on the size, duration and frequency of the operating deviation, the module assesses the degree of abnormality of the drilling equipment operation and obtains abnormal information of the drilling equipment. The formation stability analysis module extracts formation density, rock type and drilling speed data based on the formation data of the drilling area, performs data aggregation and trend analysis, extracts core features of the data, evaluates the stability level of the current drilling formation, and obtains the formation stability index; The formation early warning assessment module classifies the identified formation data into risk categories based on the formation stability index, assigns a corresponding risk level mark to each risk area by comparing it with the set formation safety threshold, and issues a corresponding early warning when the formation changes, thereby obtaining a formation early warning signal; The drilling early warning implementation module evaluates the risk level of the overall drilling operation based on the abnormal information of the drilling equipment and the formation early warning signal, combined with historical accident data and the current operating environment, implements corresponding early warning measures according to the risk level, adjusts the early warning response level, and obtains the drilling early warning result.

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