A real-time monitoring method and system for mine geological drilling production

Abstract

The present invention relates to the field of drilling monitoring technology, and specifically to a real-time monitoring method and system for mining geological drilling production. Time series data of multiple operating parameters of the drilling rig, such as torque, vibration, drilling pressure and rotation speed, are obtained. In view of the persistence of drilling rig anomalies, which will cause continuous fluctuations in operating parameters, the abnormality rate of the drilling rig at the current moment is quantified based on the deviation of the drilling pressure value, rotation speed and rated value at all times, and the fluctuation of vibration value and torque value. At the same time, considering the enrichment of mineral resources and the uneven regional rock structure, which will also cause abnormal fluctuations in operating parameters, the coupling between torque and vibration is further analyzed, and the abnormality rate of the operating state of the drilling rig at the current moment is combined to determine the abnormality degree value of the operating state of the drilling rig, so as to eliminate the influence of geological factors on the real-time monitoring results. Finally, real-time monitoring is performed based on the abnormality degree value of the state of the drilling rig at the current moment to obtain more accurate monitoring results.

Description

Technical Field

[0001] The present invention relates to the technical field of drilling monitoring, and in particular to a real-time monitoring method and system for mining geological drilling production. Background Art

[0002] Mining geological drilling is primarily used in fields such as mineral exploration and geological surveys. It obtains underground geological information through drilling, providing support for these areas. With the development of modern information technology, real-time monitoring technology has been widely used in industrial production. During mining geological drilling operations, the operating status of the drill rig is directly related to drilling efficiency and safety, so real-time monitoring of the mining geological drilling process is often required.

[0003] There are many operating parameters of a drilling rig, including torque, vibration, drilling pressure, etc. When existing technologies monitor the mining geological drilling production process in real time, they usually analyze the operating parameters at the current moment and determine whether the operating status of the drilling rig is abnormal based on whether the values ​​exceed the safety range. However, in actual scenarios, the mining geological drilling operation environment is complex and changeable. For example, the rock structure is uneven. Therefore, during the operation of the drilling rig, due to the influence of geological conditions, the operating parameters will produce small normal fluctuations. Therefore, if the operating status of the drilling rig is judged to be abnormal based solely on whether the values ​​at a single moment exceed the safety range, it may lead to misjudgment, affecting the accuracy of real-time monitoring of the drilling production process, thereby increasing maintenance costs. Summary of the Invention

[0004] In order to solve the technical problem that the operating parameters of the drilling rig will produce small normal fluctuations due to the influence of geological conditions during operation, if the operating status of the drilling rig is judged to be abnormal based solely on whether the value at a single moment exceeds the safety range, it may lead to misjudgment and affect the accuracy of real-time monitoring of the drilling production process. The purpose of the present invention is to provide a real-time monitoring method and system for mining geological drilling production. The technical solutions adopted are as follows:

[0005] During mining geological drilling operations, the time series data of various operating parameters of the drilling rig are obtained, including the torque, vibration, drilling pressure, and rotation speed of the drill bit.

[0006] At any given moment, the drilling rig's abnormality rate is determined based on the deviation between the drilling pressure and rotational speed at that moment and their corresponding rated values, as well as the fluctuations in vibration and torque values ​​at previous moments in the time series. Based on the changes in the abnormality rate of the drilling rig at all moments, the abnormality rate of the drilling rig's operating status at the current moment is determined.

[0007] Analyze the coupling between the torque value in the torque time series data and the vibration value in the vibration time series data, and determine the abnormality degree value of the drilling rig's operating status at the current moment in combination with the abnormality rate of the drilling rig's operating status at the current moment;

[0008] Based on the abnormality degree value of the drilling rig status at the current moment, the drilling production operation process is monitored in real time.

[0009] Furthermore, the method for obtaining the abnormality incidence rate includes:

[0010] At any moment, the difference between the drilling pressure value at that moment and the corresponding rated value, as well as the difference between the rotation speed and the corresponding rated value, are comprehensively analyzed to determine the propulsion anomaly coefficient of the drilling rig at that moment;

[0011] According to the fluctuation of vibration value and torque value at the historical moments before the time series of the moment, the fluctuation anomaly coefficient of the drilling rig at the moment is determined;

[0012] The normalized value of the product of the drilling rig's propulsion anomaly coefficient and the fluctuation anomaly coefficient at that moment is taken as the abnormal occurrence rate of the drilling rig at that moment.

[0013] Furthermore, the method for obtaining the propulsion anomaly coefficient includes:

[0014] For any moment, the absolute value of the difference between the drilling pressure value at that moment and the corresponding rated value is calculated as the drilling pressure deviation value; the absolute value of the difference between the rotation speed at that moment and the corresponding rated value is calculated as the rotation speed deviation value;

[0015] The sum of the drilling pressure deviation value and the rotation speed deviation value at that moment is normalized and used as the propulsion anomaly coefficient of the drilling rig at that moment.

[0016] Furthermore, the method for obtaining the fluctuation anomaly coefficient includes:

[0017] For any moment, the historical moment before this moment is used as the comparison moment;

[0018] Calculate the absolute value of the difference between the vibration value at that moment and the vibration value at each comparison moment as the vibration deviation value;

[0019] Calculate the absolute value of the difference between the torque value at that moment and the torque value at each comparison moment as the torque deviation value;

[0020] The sum of the vibration deviation value and the torque deviation value at each comparison moment is used as the fluctuation factor between that moment and each comparison moment;

[0021] The normalized value of the sum of the fluctuation factors between the moment and all the comparison moments is taken as the fluctuation anomaly coefficient of the drilling rig at that moment.

[0022] Furthermore, the method for obtaining the abnormal rate of the operating status includes:

[0023] Take all moments before the current moment as reference moments;

[0024] Based on the changing trend of the abnormality occurrence rate of the drilling rig at all times, the predicted abnormality occurrence rate of the drilling rig at the next moment is determined;

[0025] The absolute value of the difference between the abnormal occurrence rate of the drilling rig at the current moment and the predicted abnormal occurrence rate of the drilling rig at the next moment is negatively correlated and normalized to obtain the similarity value;

[0026] The sum of the abnormality occurrence rate of the drilling rig at the current moment and the predicted abnormality occurrence rate of the drilling rig at the next moment is multiplied by the similarity value, and the obtained product is normalized to obtain the abnormality rate of the operating status of the drilling rig at the current moment.

[0027] Furthermore, the method for obtaining the abnormality occurrence prediction rate includes:

[0028] Among all reference moments, for any two adjacent reference moments, the difference between the abnormality occurrence rate of the drilling rig at the later reference moment in the time series and the abnormality occurrence rate of the drilling rig at the previous reference moment in the time series is used as the adjustment factor;

[0029] The sum of the mean of all adjustment factors and the abnormal occurrence rate of the drilling rig at the current moment is used as the predicted abnormal occurrence rate of the drilling rig at the next moment.

[0030] Furthermore, the method for obtaining the abnormality degree value of the operating state includes:

[0031] Analyze the coupling between the torque value in the torque time series data and the vibration value in the vibration time series data to obtain the coupling coefficient;

[0032] The product of the coupling coefficient and the abnormal rate of the drilling rig's operating state at the current moment is normalized to obtain a value which serves as the abnormal degree value of the drilling rig's operating state at the current moment.

[0033] Furthermore, the method for obtaining the coupling coefficient includes:

[0034] Calculate the DTW value between the torque value in the torque time series data and the vibration value in the vibration time series data;

[0035] Obtain a torque curve and a vibration curve based on the torque time series data and the vibration time series data, obtain the torque slope value of the torque value at each moment on the torque curve, and obtain the vibration slope value of the torque value at each moment on the vibration curve;

[0036] The absolute value of the difference between the torque slope value and the vibration slope value at each moment is used as the trend deviation factor, and the sum of the corresponding trend deviation factors at all moments and the product of the DTW value are negatively correlated and normalized to obtain the coupling coefficient.

[0037] Furthermore, the real-time monitoring of the drilling production process based on the abnormality level of the drilling rig at the current moment includes:

[0038] If the abnormality level of the drilling rig at the current moment is less than the preset abnormality threshold, it is considered that the drilling production process at the current moment is normal;

[0039] If the abnormality level of the drilling rig at the current moment is greater than or equal to the preset abnormality threshold, it is considered that the drilling production operation process at the current moment is abnormal and the drilling rig needs to be repaired.

[0040] A real-time monitoring system for mining geological drilling production includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, code set or instruction set, and when the at least one instruction, at least one program, code set or instruction set is loaded and executed by the processor, implements any one of the steps of a real-time monitoring method for mining geological drilling production.

[0041] The present invention has the following beneficial effects:

[0042] By acquiring time-series data on a variety of operating parameters of a drilling rig, the operating status of the drilling rig can be comprehensively reflected, thereby significantly improving the monitoring accuracy of the drilling production process. Operating parameters include torque, vibration, drilling pressure, and rotational speed. Given that when an abnormality occurs in a drilling rig, it is generally persistent, which will also cause continuous fluctuations in the operating parameters. To avoid the inability of single-moment data to reflect persistence, the present invention quantifies the abnormality rate of the drilling rig at each moment based on the deviation between the drilling pressure value and the rotational speed and the rated value at each moment, and combines the fluctuations in the vibration value and the torque value at the historical moments before each moment. The abnormality rate is used to characterize the abnormality of the drilling rig's operating parameters at each moment. Then, the changes in the abnormality rate of the drilling rig at all moments are combined to determine the abnormality rate of the drilling rig's operating status at the current moment. The operating status abnormality rate can more accurately represent the fluctuations in the drill rig's operating parameters at the current moment. However, in actual drilling, due to the fact that mineral resources are often enriched along fault zones and the rock formations being drilled are uneven, the drill bit will also experience abnormal fluctuations in some operating parameters during drilling, necessitating analysis of this situation. During the drilling process, the drilling pressure and rotational speed of the drill bit's operating parameters can be used to assess the drill bit's propulsion capability, while vibration and torque can more directly reflect the drill bit's operating status, such as the resistance of the drill bit during rotation and abnormal vibration. Therefore, this analysis focuses on torque and vibration time series data. Since torque comes from motor drive and mechanical transmission, if a drilling rig fails, the torque of the drill bit will fluctuate abnormally, causing vibration changes. The unevenness of the rock formation will first affect the vibration of the drill bit. Although vibration also affects the torque, it is not the main source of torque. Therefore, when the drilling rig is abnormal, the coupling between torque and vibration will be high. Therefore, the present invention further analyzes the coupling between the torque value in the torque time series data and the vibration value in the vibration time series data, and combines the abnormal rate of the drilling rig's operating status at the current moment to determine the abnormal degree value of the drilling rig's operating status at the current moment. In this way, the influence of geological factors on the real-time monitoring results of the drilling rig during the actual drilling process is eliminated. Finally, based on the abnormal degree value of the drilling rig's status at the current moment, real-time monitoring of the drilling production operation process can obtain more accurate monitoring results. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. 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 paying any creative work.

[0044] Figure 1A method flow chart of a real-time monitoring method for mining geological drilling production provided by one embodiment of the present invention;

[0045] Figure 2 A flow chart of a method for obtaining an abnormality incidence rate provided by one embodiment of the present invention;

[0046] Figure 3 A flow chart of a method for obtaining an abnormality degree value of an operating state provided by one embodiment of the present invention;

[0047] Figure 4 A system block diagram of a real-time monitoring system for mining geological drilling production provided by one embodiment of the present invention;

[0048] Figure 5 A schematic diagram of the system structure of a real-time monitoring system for mining geological drilling production provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0049] To further illustrate the technical means and effectiveness of the present invention in achieving its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail a method and system for real-time monitoring of mining geological drilling production, including its specific implementation, structure, features, and effectiveness. In the following description, references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0050] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0051] The following describes in detail a method and system for real-time monitoring of mining geological drilling production provided by the present invention with reference to the accompanying drawings.

[0052] See also Figure 1 , which shows a method flow chart of a real-time monitoring method for mining geological drilling production provided by one embodiment of the present invention, the method comprising the following steps:

[0053] Step S1: During the mining geological drilling production operation, various operating parameter time series data of the drilling rig are obtained, wherein the operating parameters include torque, vibration, drilling pressure, and rotation speed of the drill bit.

[0054] During the mining geological drilling production operation, the operating status of the drilling rig is directly related to the drilling efficiency and safety, so it is usually necessary to monitor the mining geological drilling production operation process in real time.

[0055] When a drilling rig experiences an abnormal operating state or malfunction, operating parameters may fluctuate abnormally. Therefore, in an embodiment of the present invention, time-series data of various operating parameters of the drilling rig is first acquired. These operating parameters specifically include the torque, vibration, drilling pressure, and rotational speed of the drill bit. The specific method for acquiring this operating parameter time-series data can be achieved by installing high-precision sensors at corresponding locations on the drilling rig. For example, a torque sensor can be installed between the power source (engine or motor) and the drill bit to acquire the drill bit's torque time-series data, and a vibration sensor can be installed near the bearing or bearing seat to acquire the drill bit's vibration time-series data. The sampling interval for the operating parameter time-series data is set to 1 second, and the specific length of the time-series data is set to 10 minutes from the current moment. Both the sampling interval and the specific length of the time-series data can be adjusted based on the implementation scenario and are not limited here.

[0056] Step S2: For any moment, the abnormality rate of the drilling rig at that moment is determined based on the deviation between the drilling pressure value and the rotation speed at that moment and their corresponding rated values, the fluctuation of the vibration value at the historical moments before that moment, and the fluctuation of the torque value; based on the changes in the abnormality rate of the drilling rig at all moments, the abnormality rate of the operating status of the drilling rig at the current moment is determined.

[0057] A drilling rig primarily uses a drill bit to break underground rocks and soil layers. Therefore, by analyzing the fluctuation characteristics of the drill bit's torque, vibration, drilling pressure, and rotational speed, it is possible to preliminarily determine whether the drilling rig has experienced a fault or anomaly. Given that drilling rig faults or anomalies are generally persistent, and that data fluctuations caused by noise are random, in an embodiment of the present invention, in order to analyze the persistent fluctuations in operating parameters and more accurately quantify the drilling rig's operating status anomaly rate at the current moment, the drilling rig's anomaly rate at each moment is first quantified based on the deviation between the drilling pressure value and the rotational speed at each moment and the rated value, combined with the fluctuations in vibration and torque values ​​at the historical moments preceding each moment. Then, to reduce noise interference, the changes in the drilling rig's anomaly rate at all moments are combined to determine the drilling rig's operating status anomaly rate at the current moment.

[0058] Preferably, in one embodiment of the present invention, the method for obtaining the abnormality incidence rate includes:

[0059] See also Figure 2 , which shows a flow chart of a method for obtaining an abnormality incidence rate in one embodiment of the present invention, the method includes the following steps:

[0060] Step S201: For any moment, comprehensively analyze the difference between the drilling pressure value at that moment and the corresponding rated value, as well as the difference between the rotation speed and the corresponding rated value, to determine the propulsion anomaly coefficient of the drilling rig at that moment.

[0061] During the drilling process, the drilling pressure represents the reaction force when the drill bit contacts the rock formation, which can reflect whether the drilling is smooth. If the drilling pressure changes abnormally, it may reflect a mechanical failure. Similar to the drilling pressure, abnormal changes in the rotation speed may also reflect a mechanical failure of the drilling rig. If the rotation speed is too fast, it may cause the drill bit to overheat and increase wear, while if the rotation speed is too low, it may be a failure of the transmission device.

[0062] Drilling pressure and rotation speed are directly related to the drilling rig's propulsion capacity and can instantly reflect the drilling rig's propulsion status. Therefore, at each moment, the difference between the drilling pressure value and rotation speed and the corresponding rated value can be analyzed to determine the drilling rig's propulsion anomaly coefficient at each moment.

[0063] Under normal circumstances, the drilling pressure and rotation speed should be maintained at the rated values. Therefore, for any moment, the absolute value of the difference between the drilling pressure value at that moment and the corresponding rated value is calculated as the drilling pressure deviation value. The larger the drilling pressure deviation value, the more abnormal the drilling pressure change at that moment. Similarly, the absolute value of the difference between the rotation speed at that moment and the corresponding rated value is used as the rotation speed deviation value. At this time, the larger the rotation speed deviation value, the greater the deviation between the rotation speed and the rated value at that moment, and an abnormal situation may have occurred.

[0064] Finally, the sum of the drilling pressure deviation and the rotational speed deviation at that moment is normalized and used as the drilling rig's propulsion anomaly coefficient. A larger propulsion anomaly coefficient indicates an anomaly in the drill bit's propulsion capability at that moment, and thus a higher probability of a drilling rig failure or anomaly. Normalization is a well-known technique for those skilled in the art, and the normalization function can be linear normalization or standard normalization, among others. The specific normalization method is not limited here.

[0065] It should be noted that drilling pressure generally refers to the pressure exerted by the drill string on the rock during drilling. This pressure directly affects drilling efficiency and drill bit life. The rated value for drilling pressure is typically set to 85% of the drill string weight; the rated value for rotational speed is typically set to 80 revolutions per minute. The specific values ​​can be set based on the actual drilling rig specifications, geological conditions, and drilling objectives. The specific values ​​are provided here for illustrative purposes only and can be adjusted based on the implementation scenario.

[0066] Step S202: For any moment, the fluctuation anomaly coefficient of the drilling rig at that moment is determined based on the fluctuation of the vibration value and the fluctuation of the torque value at the historical moments before that moment.

[0067] Torque reflects the resistance of the drill bit to rotation. Excessive or insufficient torque may indicate problems in the drilling process. Abnormal vibration may be caused by abnormal contact of the drill bit with the rock formation, loose equipment or other faults.

[0068] Therefore, torque and vibration are directly related to the working status of the drilling rig and are often affected by multiple factors. Therefore, for each moment, the fluctuation of the vibration value and the fluctuation of the torque value at the historical moments before the time series of that moment can be analyzed to determine the fluctuation anomaly coefficient of the drilling rig at that moment. That is, by analyzing the changes in a small section of time series data, the fluctuation anomaly coefficient of the drilling rig at each moment can be quantified.

[0069] For any moment, the historical moment before this moment is used as the comparison moment; the absolute value of the difference between the vibration value at this moment and the vibration value at each comparison moment corresponding to this moment is calculated as the vibration deviation value. The larger the vibration deviation value, the greater the difference in vibration value between this moment and the comparison moment, which is considered to be a strong degree of data fluctuation; similarly, the absolute value of the difference between the torque value at this moment and the torque value at each corresponding comparison moment is calculated as the torque deviation value. The larger the torque deviation value, the stronger the data fluctuation.

[0070] Then, the sum of the vibration deviation value and the torque deviation value at each comparison moment is used as the fluctuation factor between the moment and each corresponding comparison moment; finally, the sum of the fluctuation factors between the moment and all corresponding comparison moments is normalized and used as the fluctuation anomaly coefficient of the drilling rig at the moment. The larger the fluctuation factor, the greater the deviation between the vibration value and the torque value at the moment and the vibration value and the torque value at each comparison moment, and the greater the data fluctuation amplitude. The larger the fluctuation anomaly coefficient obtained by combining the fluctuation factors between the moment and all corresponding comparison moments, the greater the fluctuation amplitude of the data before the moment, which can be regarded as the possibility of abnormality or failure of the drilling rig at the moment. Normalization is a technical means well known to those skilled in the art. The normalization function can be linear normalization or standard normalization, etc. The specific normalization method is not limited here.

[0071] Step S203: The abnormal propulsion coefficient and the abnormal fluctuation coefficient of the drilling rig at each moment are integrated to determine the abnormal occurrence rate of the drilling rig at each moment.

[0072] Based on the above analysis, it can be seen that the larger the propulsion anomaly coefficient of the drilling rig at a certain moment, the more abnormal the propulsion ability of the drill bit at that moment is, and the higher the probability of the drilling rig failure or anomaly; the larger the fluctuation anomaly coefficient at a certain moment, the larger the fluctuation amplitude of the data in the time series before that moment, and the higher the possibility of the drilling rig failure or anomaly.

[0073] Therefore, the product of the drilling rig's propulsion anomaly coefficient and the fluctuation anomaly coefficient at each moment is normalized to obtain the value representing the drilling rig's anomaly rate at each moment. A higher anomaly rate indicates a greater degree of anomaly in the drilling rig's operating parameters at that moment, indicating poor operating conditions. Normalization is a well-known technique for those skilled in the art, and the normalization function can be linear normalization or standard normalization. The specific normalization method is not limited here.

[0074] When a component of a drilling rig fails, it is generally persistent, that is, accompanied by persistent abnormal fluctuations in some operating parameter data. However, data fluctuations caused by noise do not have persistent abnormal data fluctuations. Therefore, based on the changes in the abnormal occurrence rate of the drilling rig at all times, the abnormal rate of the drilling rig's operating status at the current moment is determined.

[0075] Preferably, in one embodiment of the present invention, the method for obtaining the abnormal rate of the operating status includes:

[0076] All moments before the current moment are used as reference moments.

[0077] In order to analyze persistence, in an embodiment of the present invention, the changing trend of the abnormality occurrence rate of the drilling rig at the reference moment is analyzed and combined with the abnormality occurrence rate of the drilling rig at the current moment, so as to predict the abnormality occurrence rate of the drilling rig at the future moment: among all reference moments, for any two adjacent reference moments, the difference between the abnormality occurrence rate of the drilling rig at the latter reference moment in time series and the abnormality occurrence rate of the drilling rig at the previous reference moment in time series is used as an adjustment factor. A positive value of the adjustment factor indicates that the abnormality occurrence rate of the drilling rig is increasing with the change of time between each two adjacent reference moments (more likely to be the real fluctuation of the operating parameter data); conversely, if the adjustment factor is a negative value, it indicates that the abnormality occurrence rate of the drilling rig is decreasing with the change of time between each two adjacent reference moments (the abnormality at this time may be caused by random noise). At this time, among all the reference moments, there is an adjustment factor between every two adjacent reference moments. The mean of all the adjustment factors and the sum of the abnormal occurrence rate of the drilling rig at the current moment can be used as the abnormal occurrence prediction rate of the drilling rig at the next moment. At this time, when the abnormal occurrence prediction rate of the drilling rig at the next moment is greater than the abnormal occurrence rate of the drilling rig at the current moment, it means that the drilling rig has experienced continuous abnormal fluctuations in operating parameters, and the possibility of a failure or abnormality in the drilling rig is higher. Conversely, if the abnormal occurrence prediction rate of the drilling rig at the next moment is less than the abnormal occurrence rate of the drilling rig at the current moment, it means that the drilling rig has experienced accidental abnormal fluctuations in operating parameters, and the possibility of a failure or abnormality in the drilling rig is lower.

[0078] Then calculate the absolute value of the difference between the abnormal occurrence rate of the drilling rig at the current moment and the predicted abnormal occurrence rate of the drilling rig at the next moment. The smaller the value, the more similar the data fluctuation of the operating parameters of the drilling rig between the two adjacent moments. Therefore, the value is negatively correlated and normalized to achieve logical relationship correction and obtain similar values. The negative correlation mapping and normalization here can be used function, where It represents the exponential function with the natural constant e as the base, and x represents the independent variable.

[0079] Finally, the sum of the drilling rig's abnormality rate at the current moment and the predicted abnormality rate at the next moment is normalized, and the product of this sum and the similarity value is normalized to obtain the drilling rig's operating status abnormality rate at the current moment. If the data fluctuations of the operating parameters between two adjacent moments are relatively similar, and the likelihood of the drilling rig experiencing an abnormality is also higher, it can be considered that the drilling rig has experienced an abnormality or failure, rather than data fluctuations caused by random noise. Therefore, a higher operating status abnormality rate indicates that the drilling rig is in poor condition at the current moment. Normalization is a technical method well known to those skilled in the art. The normalization function can be selected from linear normalization, standard normalization, etc. The specific normalization method is not limited here.

[0080] Step S3: Analyze the coupling between the torque value in the torque time series data and the vibration value in the vibration time series data, and determine the abnormality degree value of the drilling rig's operating state at the current moment in combination with the abnormality rate of the drilling rig's operating state at the current moment.

[0081] Based on the above steps, by analyzing the changes and fluctuations in the operating parameter time series data, the operating status abnormality rate of the drilling rig at the current moment is obtained. However, in the actual drilling process, since mineral resources are often enriched along the fault zone and the drilled rock structure is uneven, the drill bit will also produce abnormal fluctuations in some operating parameter time series data during the drilling process based on the above reasons. As a result, the operating status abnormality rate of the drilling rig obtained in the above steps cannot accurately reflect whether the drilling rig has actually failed. Therefore, it is necessary to eliminate the influence of geological factors based on the characteristics of the operating parameter time series data.

[0082] To determine whether the poor operating status of the drilling rig at the current moment is caused by component failure or the influence of geological factors, we can analyze the differences in the changing characteristics of the operating parameter time series data caused by the failure and the rock formation: since the operating parameters of the drilling rig are generally divided into propulsion parameters and state parameters, the propulsion parameters mainly include the drilling pressure and rotation speed of the drill bit, while the state parameters mainly include torque, vibration, etc.; among them, the state parameters can more intuitively show its operating status, so the analysis can be based on the torque time series data and vibration time series data in the operating parameters. Because the components of a drilling rig are highly coupled, torque comes from motor drive and mechanical transmission, while vibration comes from a wider range of sources. Therefore, in the event of a drilling rig failure, the torque time series data will first produce abnormal fluctuations. The periodic load changes caused by the fluctuations in the torque time series data will be directly transmitted to the mechanical system, causing fluctuations in the vibration time series data. Therefore, if a real failure occurs in the drilling rig, the coupling between the torque time series data and the vibration time series data, that is, the similarity, will be higher. However, geological factors and the uneven effects of rock formations will first affect the vibration time series data, causing the torque time series data to change due to the abnormality of the vibration time series data. However, since the main source of torque is not vibration, if the fluctuations in the operating parameter time series data are caused by geological factors, then the vibration time series data will have a smaller impact on the torque time series data. Based on the above logic, we can analyze the coupling between the torque value in the torque time series data and the vibration value in the vibration time series data, and combine it with the abnormality rate of the drilling rig's operating status at the current moment to determine the abnormality level of the drilling rig's operating status at the current moment.

[0083] Preferably, in one embodiment of the present invention, the method for obtaining the abnormality degree value of the operating status includes:

[0084] See also Figure 3, which shows a flow chart of a method for obtaining a running state abnormality degree value in one embodiment of the present invention, the method includes the following steps:

[0085] Step S301: Analyze the coupling between the torque value in the torque time series data and the vibration value in the vibration time series data to obtain a coupling coefficient.

[0086] Dynamic Time Warping (DTW) is an algorithm used to measure the similarity between two time series. In this embodiment of the present invention, the DTW value between the torque value in the torque time series data and the vibration value in the vibration time series data is calculated based on the dynamic time warping algorithm. The smaller the DTW value, the higher the similarity between the torque time series data and the vibration time series data, which can also be regarded as having more consistent changes, so the coupling will be higher.

[0087] The torque curve and vibration curve are obtained based on the torque time series data and the vibration time series data. On the torque curve, the torque slope value of the torque value at each moment is obtained. Similarly, on the vibration curve, the vibration slope value of the torque value at each moment is obtained.

[0088] When the coupling between two time series data is high, there should be a more consistent data change trend. Therefore, the absolute value of the difference between the torque slope value and the vibration slope value at each moment is used as the trend deviation factor. The larger the trend deviation factor, the more inconsistent the change. Conversely, the smaller the trend deviation factor, the more consistent the change.

[0089] Finally, the sum of the trend deviation factors at all moments is calculated. The larger the sum, the more inconsistent the changing trends between the torque time series data and the vibration time series data, so the coupling is poor. On the contrary, if the sum is smaller, the more consistent the changing trends between the torque time series data and the vibration time series data, that is, the better the coupling. Therefore, the sum is multiplied by the DTW value between the torque time series data and the vibration time series data. The smaller the product, the higher the coupling. Therefore, in order to achieve logical relationship correction, the product is negatively correlated and normalized, so that the obtained value is used as the coupling coefficient. At this time, the larger the coupling coefficient, the stronger the correlation between the torque time series data and the vibration time series data. The negative correlation mapping and normalization here can be used. function, where It represents the exponential function with the natural constant e as the base, and x represents the independent variable.

[0090] It should be noted that the calculation process of the DTW value is a well-known technology and will not be described in detail here; the method for obtaining the torque curve and the vibration curve can use the least squares method to fit the time series data, which is also a well-known technology and will not be described in detail here.

[0091] Step S302: The coupling coefficient is combined with the abnormality rate of the drilling rig's operating state at the current moment to obtain the abnormality degree value of the drilling rig's operating state at the current moment.

[0092] A larger coupling coefficient indicates a higher similarity between the torque time series data and the vibration time series data, and a greater degree of coupling. This indicates a higher likelihood of a true fault or anomaly in the drill rig itself. Therefore, the product of the coupling coefficient and the abnormality rate of the drill rig's operating state at the current moment can be normalized to obtain the value representing the degree of abnormality in the drill rig's operating state at the current moment. A larger abnormality value indicates a lower likelihood that the fluctuations and changes in the operating parameter time series data are affected by geology, and a higher probability that an abnormality or fault has occurred in the drill rig itself. Normalization is a well-known technique for those skilled in the art, and the normalization function can be linear normalization or standard normalization, among others. The specific normalization method is not limited herein.

[0093] Step S4: Based on the abnormality level of the drilling rig at the current moment, the drilling production operation process is monitored in real time.

[0094] Through the analysis of the above steps, the abnormality degree value of the drilling rig status at the current moment can be determined, which is used to characterize the operating status of the drilling rig at the current moment. Therefore, based on the abnormality degree value of the drilling rig status at the current moment, the drilling production operation process can be monitored in real time.

[0095] Preferably, in one embodiment of the present invention, real-time monitoring of the drilling production process is performed based on the abnormality level of the drilling rig at the current moment, including:

[0096] If the abnormality level of the drilling rig at the current moment is less than the preset abnormality threshold, it is considered that the drilling production operation process at the current moment is normal.

[0097] If the abnormality level of the drilling rig at the current moment is greater than or equal to the preset abnormality threshold, it is considered that the drilling production operation process at the current moment is abnormal and the drilling rig needs to be repaired.

[0098] It should be noted that the preset abnormality threshold is set to 0.75. The specific value can be adjusted according to the implementation scenario and is not limited here.

[0099] When it is determined that an abnormality has occurred in the drilling production operation process at the current moment, the drilling rig needs to be repaired. Usually, the drilling rig is shut down, and then the various structures or components are checked for abnormalities. In an embodiment of the present invention, the repair priority of each structure or component can be further determined, thereby reducing maintenance costs and improving repair efficiency.

[0100] A drilling rig primarily consists of a drilling unit, a hydraulic unit, and a power unit. The drilling unit is located at the forefront of drilling, so the drill bit has the highest maintenance priority. For the hydraulic and power units, the maintenance priority can be determined based on the performance parameters of each unit. The hydraulic unit uses liquid pressure to push an actuator (such as a hydraulic motor or hydraulic cylinder), converting hydraulic energy into mechanical energy to output torque. The power unit converts energy (chemical energy, electrical energy, etc.) into mechanical energy and drives the hydraulic unit to output torque. Therefore, the failure rate of the hydraulic unit can be determined by analyzing the correlation between the performance parameters of the hydraulic unit and the torque. For the hydraulic unit, the performance parameters are primarily the hydraulic pressure and real-time temperature of the hydraulic unit. For the power unit, the performance parameters are primarily the output power and real-time temperature of the power unit.

[0101] Taking the hydraulic device as an example, the hydraulic pressure time series data of the hydraulic device is obtained. The sampling interval is set to 1 second, and the length of the time series data is set to 10 minutes before the current moment. The sampling interval and the specific length of the time series data must be consistent with the operating parameter time series data. Then, the correlation coefficient between the hydraulic pressure value in the hydraulic pressure time series data and the torque value in the torque time series data is analyzed. The Pearson correlation coefficient between the two can be calculated. When the Pearson correlation coefficient is closer to 1, it indicates that the two are positively correlated. Conversely, when the Pearson correlation coefficient is closer to -1, it indicates that the two are negatively correlated. However, since the drilling rig has already experienced an abnormality and needs to be repaired, only the correlation analysis is required here. Therefore, the absolute value of the Pearson correlation coefficient is taken as the correlation value. The correlation value is multiplied by the real-time temperature of the hydraulic device at the current moment, and the resulting product is normalized to obtain the failure rate of the hydraulic device. The larger the value, the more likely it is that the hydraulic device in the drilling rig has an abnormality.

[0102] Based on the same method, the correlation values ​​between the output power time series data and the torque time series data of the power unit are analyzed, and the failure rate of the power unit is calculated.

[0103] If there are other devices, the same method is used to calculate and obtain the failure rates of different devices in the drilling rig. The failure rates are then sorted in descending order to obtain a descending sequence. In the descending sequence, the maintenance priorities of different devices decrease accordingly.

[0104] It should be noted that the above-mentioned judgment of maintenance priority is only an example of obtaining a maintenance priority order after determining that the drilling rig needs to be repaired in an embodiment of the invention, which can provide a reference for the maintenance order for relevant maintenance personnel. However, in actual production operations, the operation of the drilling rig is complex, and a fault may not necessarily occur at a location with a high maintenance priority. There may also be a situation where multiple faults are superimposed. Therefore, a comprehensive judgment is required based on the actual situation. If conditions permit, a full system joint inspection can be carried out to confirm the coordinated operation of various devices in the drilling rig.

[0105] In summary, by acquiring time-series data on various operating parameters of a drilling rig, the operating status of the drilling rig can be comprehensively reflected, thereby significantly improving the monitoring accuracy of the drilling production process. Operating parameters include torque, vibration, drilling pressure, and rotational speed. Given that when an abnormality occurs in a drilling rig, it is generally persistent, which will also cause continuous fluctuations in the operating parameters. To avoid the inability of single-moment data to reflect persistence, in an embodiment of the present invention, the abnormality rate of the drilling rig at each moment is quantified based on the deviation between the drilling pressure value and the rotational speed and the rated value at each moment, and combined with the fluctuations in the vibration value and torque value at the historical moments before each moment in the time series. The abnormality rate is used to characterize the abnormality of the drilling rig's operating parameters at each moment. Then, the changes in the abnormality rate of the drilling rig at all moments are combined to determine the abnormality rate of the drilling rig's operating status at the current moment. The operating status abnormality rate can more accurately represent the fluctuations in the drill rig's operating parameters at the current moment. However, in actual drilling, due to the fact that mineral resources are often enriched along fault zones and the rock formations being drilled are uneven, the drill bit will also experience abnormal fluctuations in some operating parameters during drilling, necessitating analysis of this situation. During the drilling process, the drilling pressure and rotational speed of the drill bit's operating parameters can be used to assess the drill bit's propulsion capability, while vibration and torque can more directly reflect the drill bit's operating status, such as the resistance of the drill bit during rotation and abnormal vibration. Therefore, this analysis focuses on torque and vibration time series data. Since torque comes from motor drive and mechanical transmission, if a drilling rig fails, the torque of the drill bit will fluctuate abnormally, causing vibration changes. The unevenness of the rock formation will first affect the vibration of the drill bit. Although vibration also affects the torque, it is not the main source of torque. Therefore, when the drilling rig is abnormal, the coupling between torque and vibration will be high. Therefore, the present invention further analyzes the coupling between the torque value in the torque time series data and the vibration value in the vibration time series data, and combines the abnormal rate of the drilling rig's operating status at the current moment to determine the abnormal degree value of the drilling rig's operating status at the current moment. In this way, the influence of geological factors on the real-time monitoring results of the drilling rig during the actual drilling process is eliminated. Finally, based on the abnormal degree value of the drilling rig's status at the current moment, real-time monitoring of the drilling production operation process can obtain more accurate monitoring results.

[0106] The embodiment of the present invention also provides a real-time monitoring system for mining geological drilling production, see Figure 4 , which shows a system block diagram, including: a data acquisition module 401, used to implement step S1 in the above method; a fluctuation analysis module 402, used to implement step S2 in the above method; an abnormality analysis module 403, used to implement step S3 in the above method; and a real-time monitoring module 404, used to implement step S4 in the above method.

[0107] It should be noted that the system provided in the above embodiment is merely an example of the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the computer device can be divided into different functional modules to complete all or part of the functions described above. In addition, the real-time monitoring system for mine geological drilling production and the real-time monitoring method for mine geological drilling production provided in the above embodiment are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0108] See also Figure 5 , which shows a system structure diagram of a real-time monitoring system for mining geological drilling production provided by an embodiment of the present invention, including a processor 500, a memory 501, a bus 502 and a communication interface 503, wherein the processor 500, the communication interface 503 and the memory 501 are connected via the bus 502; wherein the memory 501 may include a high-speed random access memory, the bus 502 may be an ISA bus, a PCI bus or an EISA bus, etc., and the processor 500 may be an integrated circuit chip with signal processing capabilities; the memory 501 stores at least one instruction, at least one program, a code set or an instruction set, and when the at least one instruction, at least one program, a code set or an instruction set is loaded and executed by the processor, the steps in a real-time monitoring method for mining geological drilling production are implemented.

[0109] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0110] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A real-time monitoring method for mining geological drilling production, characterized in that: The method comprises: During mining geological drilling operations, the time series data of various operating parameters of the drilling rig are obtained, including the torque, vibration, drilling pressure, and rotation speed of the drill bit. At any given moment, the drilling rig's abnormality rate is determined based on the deviation between the drilling pressure and rotational speed at that moment and their corresponding rated values, as well as the fluctuations in vibration and torque values ​​at previous moments in the time series. Based on the changes in the abnormality rate of the drilling rig at all moments, the abnormality rate of the drilling rig's operating status at the current moment is determined. Analyze the coupling between the torque value in the torque time series data and the vibration value in the vibration time series data, and determine the abnormality degree value of the drilling rig's operating status at the current moment in combination with the abnormality rate of the drilling rig's operating status at the current moment; Based on the abnormality level of the drilling rig at the current moment, the drilling production process is monitored in real time; The method for obtaining the abnormality incidence rate includes: At any moment, the difference between the drilling pressure value at that moment and the corresponding rated value, as well as the difference between the rotation speed and the corresponding rated value, are comprehensively analyzed to determine the propulsion anomaly coefficient of the drilling rig at that moment; According to the fluctuation of vibration value and torque value at the historical moments before the time series of the moment, the fluctuation anomaly coefficient of the drilling rig at the moment is determined; The product of the drilling rig's propulsion anomaly coefficient and the fluctuation anomaly coefficient at that moment is normalized to obtain the value obtained as the drilling rig's anomaly occurrence rate at that moment; The method for obtaining the abnormal rate of the operating state includes: Take all moments before the current moment as reference moments; Based on the changing trend of the abnormality occurrence rate of the drilling rig at all times, the predicted abnormality occurrence rate of the drilling rig at the next moment is determined; The absolute value of the difference between the abnormal occurrence rate of the drilling rig at the current moment and the predicted abnormal occurrence rate of the drilling rig at the next moment is negatively correlated and normalized to obtain the similarity value; The sum of the abnormality occurrence rate of the drilling rig at the current moment and the predicted abnormality occurrence rate of the drilling rig at the next moment is multiplied by the similarity value, and the obtained product is normalized to obtain the abnormality rate of the operating state of the drilling rig at the current moment; The method for obtaining the abnormality degree value of the operating state includes: Analyze the coupling between the torque value in the torque time series data and the vibration value in the vibration time series data to obtain the coupling coefficient; The product of the coupling coefficient and the abnormal rate of the drilling rig's operating state at the current moment is normalized to obtain a value which serves as the abnormal degree value of the drilling rig's operating state at the current moment.

2. A real-time monitoring method for mine geological drilling production according to claim 1, characterized in that: The method for obtaining the propulsion anomaly coefficient includes: For any moment, the absolute value of the difference between the drilling pressure value at that moment and the corresponding rated value is calculated as the drilling pressure deviation value; the absolute value of the difference between the rotation speed at that moment and the corresponding rated value is calculated as the rotation speed deviation value; The sum of the drilling pressure deviation value and the rotation speed deviation value at that moment is normalized and used as the propulsion anomaly coefficient of the drilling rig at that moment.

3. A real-time monitoring method for mine geological drilling production according to claim 1, characterized in that: The method for obtaining the fluctuation anomaly coefficient includes: For any moment, the historical moment before this moment is used as the comparison moment; Calculate the absolute value of the difference between the vibration value at that moment and the vibration value at each comparison moment as the vibration deviation value; Calculate the absolute value of the difference between the torque value at that moment and the torque value at each comparison moment as the torque deviation value; The sum of the vibration deviation value and the torque deviation value at each comparison moment is used as the fluctuation factor between that moment and each comparison moment; The normalized value of the sum of the fluctuation factors between the moment and all the comparison moments is taken as the fluctuation anomaly coefficient of the drilling rig at that moment.

4. A real-time monitoring method for mine geological drilling production according to claim 1, characterized in that: The method for obtaining the abnormality occurrence prediction rate includes: Among all reference moments, for any two adjacent reference moments, the difference between the abnormality occurrence rate of the drilling rig at the later reference moment in the time series and the abnormality occurrence rate of the drilling rig at the previous reference moment in the time series is used as the adjustment factor; The sum of the mean of all adjustment factors and the abnormal occurrence rate of the drilling rig at the current moment is used as the predicted abnormal occurrence rate of the drilling rig at the next moment.

5. The real-time monitoring method for mining geological drilling production according to claim 1, characterized in that: The method for obtaining the coupling coefficient includes: Calculate the DTW value between the torque value in the torque time series data and the vibration value in the vibration time series data; Obtain a torque curve and a vibration curve based on the torque time series data and the vibration time series data, obtain the torque slope value of the torque value at each moment on the torque curve, and obtain the vibration slope value of the torque value at each moment on the vibration curve; The absolute value of the difference between the torque slope value and the vibration slope value at each moment is used as the trend deviation factor, and the sum of the corresponding trend deviation factors at all moments and the product of the DTW value are negatively correlated and normalized to obtain the coupling coefficient.

6. A real-time monitoring method for mine geological drilling production according to claim 1, characterized in that: The real-time monitoring of the drilling production process based on the abnormality level of the drilling rig at the current moment includes: If the abnormality level of the drilling rig at the current moment is less than the preset abnormality threshold, it is considered that the drilling production process at the current moment is normal; If the abnormality level of the drilling rig at the current moment is greater than or equal to the preset abnormality threshold, it is considered that the drilling production operation process at the current moment is abnormal and the drilling rig needs to be repaired.

7. A real-time monitoring system for mining geological drilling production, characterized in that: The invention comprises a processor and a memory, wherein the memory stores at least one instruction, at least one program, code set or instruction set, and when the at least one instruction, at least one program, code set or instruction set is loaded and executed by the processor, the steps of a real-time monitoring method for mining geological drilling production as described in any one of claims 1 to 6 are implemented.

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