A crawler-type fully hydraulic directional drilling rig life prediction method and system

Abstract

The present invention relates to the technical field of drilling rig life prediction, and in particular to a crawler-type fully hydraulic directional drilling rig life prediction method and system. The method comprises: analyzing the correlation between environmental indicators and drilling rig life, calculating the environmental impact factor of the drilling rig, obtaining a fitting curve of the environmental impact factor and life of historical drilling rigs, taking the life corresponding to the environmental impact factor of the drilling rig to be predicted on the fitting curve as its initial predicted life, selecting a plurality of historical drilling rigs that are closest to the environmental impact factor of the drilling rig to be predicted as reference drilling rigs, determining the proximity between the drilling rig to be predicted and the reference drilling rig according to the difference in environmental impact factor and the difference in loss degree between the drilling rig to be predicted and the reference drilling rig, calculating the error value of the initial predicted life according to the proximity and the fitting error of the life of the reference drilling rig, and using the error value to correct the initial predicted life to the final predicted life, thereby improving the accuracy of the drilling rig life prediction.

Description

Technical Field

[0001] The present invention relates to the technical field of drilling rig life prediction, and in particular to a crawler-type fully hydraulic directional drilling rig life prediction method and system. Background Art

[0002] Drilling rigs are essential key equipment in construction and resource extraction. In the drilling process, reasonable prediction of the service life of the drilling rig and preventive maintenance are of great significance to reducing drilling accidents, ensuring safe drilling and optimizing drilling operations. If the drilling rig reaches its service life and fails during use, it will not only lead to a decrease in productivity, but may also cause serious safety accidents, seriously affecting the smooth progress of normal mining or construction. Therefore, timely and accurate prediction of the life of the drilling rig so that maintenance or replacement can be carried out in advance is crucial to ensure operational safety and improve production efficiency.

[0003] In the prior art, statistical analysis methods are usually used to collect the external environmental conditions (such as temperature, humidity, geological conditions, etc.) of the drilling rig during use and their corresponding service life data, and use these data for fitting to establish a life prediction model. For example, the existing Chinese patent application document with application publication number CN111667198A discloses a remote online monitoring and predictive maintenance evaluation method for oil drilling rigs. The method includes collecting equipment data and comprehensively evaluating the equipment through single parameter monitoring analysis, multi-parameter logic analysis and historical data comparison analysis. Among them, the multi-parameter logic analysis determines whether the alarm condition is met according to the multi-parameter judgment criteria based on the real-time monitoring data, and compensates for the parameters related to the ambient temperature. The historical data comparison analysis draws a trend curve by calling the historical data of the equipment or the historical data of the same type of equipment and compares it with the existing trend curve to determine whether the equipment is operating normally. Another Chinese patent document with authorization announcement number CN102900372B provides a method for predicting the reasonable service life of a PDC drill bit. This method establishes a PDC drill bit life calculation model based on rock abrasiveness, drilling pressure and rotation speed, and combines the linear cumulative damage theory of mechanical parts to establish a PDC drill bit residual newness prediction model under dynamic load. This solution uses a large amount of actual PDC drill bit usage data and applies statistical analysis theory to systematically study the influence of rock internal friction angle and drilling operation parameters on drill bit life, establishes a PDC drill bit life calculation model, and thus predicts the drill bit life.

[0004] When analyzing the relationship between various environmental conditions and the life of the drilling rig, the above technical solution performs curve fitting on the values ​​of various environmental conditions and the life of the drilling rig, finds the relationship curve between the environmental conditions and the life of the drilling rig, and establishes a life prediction model based on the relationship curve to predict the life of the drilling rig. Although this method can reflect the relationship between the life of the drilling rig and environmental conditions to a certain extent, due to the limited amount of historical data, when the data samples are small or the data distribution is uneven, the fitted relationship curve is prone to under-fitting and cannot accurately capture the real change trend of the life of the drilling rig with the environmental conditions, which will lead to inaccurate prediction results of the life of the drilling rig, thereby increasing the risk of failure and affecting production efficiency and operation safety. Summary of the invention

[0005] In order to solve the problem that the relationship curve between the curve fitting environmental conditions and the life of the drilling rig is under-fitted due to the small number of samples or uneven distribution, which affects the accuracy of the prediction of the life of the drilling rig, the present invention proposes a crawler-type fully hydraulic directional drilling rig life prediction method and system, which specifically adopts the following scheme:

[0006] In one aspect, the present invention provides a method for predicting the life of a crawler-type fully hydraulic directional drilling rig, comprising:

[0007] The lifespans of multiple historical drilling rigs and multiple environmental indicators that affect the lifespans are obtained, and the correlation between each environmental indicator and the lifespan of the drilling rig is obtained through correlation analysis. According to the correlation between each environmental indicator of any drilling rig and the lifespan of the drilling rig, and the difference between the environmental indicator and the mean value of the environmental indicator of all drilling rigs, the environmental impact factor of the drilling rig is calculated, and the environmental impact factor is positively correlated with the correlation and the difference; wherein any drilling rig is a historical drilling rig / a drilling rig to be predicted;

[0008] Obtain the fitting curve of the environmental impact factor and life of all historical drilling rigs, take the life of the environmental impact factor of the drilling rig to be predicted corresponding to the fitting curve as its initial predicted life, select multiple historical drilling rigs with the environmental impact factor closest to the drilling rig to be predicted as reference drilling rigs, and determine the proximity between the drilling rig to be predicted and the reference drilling rig according to the difference in environmental impact factor and the difference in loss degree between the drilling rig to be predicted and the reference drilling rig, and the proximity is negatively correlated with the difference in environmental impact factor and the difference in loss degree between the two.

[0009] According to the proximity between the drilling rig to be predicted and all reference drilling rigs and the fitting errors of the lifespans of all reference drilling rigs, the error value of the initial predicted lifespan is calculated, and the error value is positively correlated with the proximity and the fitting error. The initial predicted lifespan is corrected to the final predicted lifespan using the error value.

[0010] The above technical solution ensures the comprehensiveness and diversity of data by collecting a large amount of historical data. Correlation analysis can help identify which environmental indicators have the greatest impact on the life of the drilling rig, thereby providing an important basis for the subsequent model establishment. This data-driven method can more accurately reflect the trend of changes in the life of the drilling rig under actual working conditions. By introducing environmental impact factors, the specific impact of each environmental indicator on the life of the drilling rig can be quantified. The environmental impact factor not only considers the correlation between the environmental indicator and the life of the drilling rig, but also considers the distribution of the environmental indicator in all drilling rigs. This comprehensive consideration makes the environmental impact factor more accurate and can better reflect the changes in the life of the drilling rig under specific environmental conditions. Through the fitting curve, the relationship between the environmental impact factor and the life of the drilling rig can be intuitively seen. The environmental impact factor of the drilling rig to be predicted is substituted into the fitting curve to obtain a preliminary life prediction value, which provides a basic prediction value. By selecting the historical rigs with the closest environmental impact factors to the rig to be predicted as references, the data of these reference rigs can be used to correct the preliminary prediction values. The calculation of proximity takes into account the differences in environmental impact factors and loss, ensuring that the selection of reference rigs is highly representative. This can reduce the underfitting problem caused by insufficient data or uneven distribution and improve the accuracy of the prediction. By calculating the error value, the deviation between the preliminary prediction value and the actual value can be evaluated. The calculation of the error value takes into account the proximity and fitting error of the reference rig, making the error estimate more accurate. This method can better capture the trend of rig life changes under current operating conditions, thereby improving the reliability of the prediction results. By correcting the error of the preliminary prediction value, a more accurate final prediction life can be obtained. This method combines a large amount of historical data and error analysis of similar cases to improve the accuracy and reliability of the prediction results. The final predicted life is closer to the actual situation, which helps to formulate a more reasonable maintenance plan, reduce the risk of failure, and improve production efficiency and operation safety.

[0011] Furthermore, the calculation formula of the error value of the initial predicted life is:

[0012]

[0013] In the formula, is the error value of the initial predicted life of the drilling rig to be predicted, is the number of reference rigs, is the serial number of the reference rig, For the The fitting error of the life of the reference rigs, and , For the The actual value of the life of a reference rig, is the first The fitted value of the life of the reference rigs, The predicted drilling rigs and The proximity of a reference rig, For the predicted drilling rigs and The technical solution calculates the error value by weighted average method. All based on actual values and the fitted values This method can effectively reflect the prediction deviation of the model under different environmental conditions. Through weighted averaging, the influence of individual extreme errors can be smoothed out, making the final error estimate more stable and reliable.

[0014] Furthermore, the calculation method of the proximity between the drilling rig to be predicted and the reference drilling rig is:

[0015]

[0016] In the formula, For the drilling rig to be predicted and the The proximity of a reference rig, and Respectively Environmental impact factors and loss of reference drilling rigs, and are the environmental impact factor and loss degree of the drilling rig to be predicted, The technical solution uses an exponential function to calculate the proximity, ensuring that when the difference in environmental impact factors and loss between the predicted rig and the reference rig increases, the proximity between the two decreases rapidly. The formula takes into account the difference in environmental impact factors and loss at the same time, making the calculation of proximity more comprehensive.

[0017] Furthermore, the final predicted lifespan is the sum of the error value and the initial predicted lifespan.

[0018] Furthermore, the calculation formula of the environmental impact factor of any drilling rig is:

[0019]

[0020] In the formula, For the Environmental impact factors of each drilling rig, is the total number of drilling rigs, is the serial number of the environmental indicator. For the Drilling rig No. environmental indicators, For all drilling rigs The mean value of environmental indicators, For the The correlation between environmental indicators and rig life, Represents a normalization operation. This technical solution calculates the degree of deviation of each rig on a specific environmental indicator through a normalization operation, ensuring that environmental indicators of different dimensions can be compared. By multiplying the normalized difference by the correlation between the environmental indicator and the rig life and performing a weighted sum, the environmental indicator that has a greater impact on the rig life has a greater weight in the environmental impact factor. By comprehensively considering the impact of multiple environmental indicators and through normalization and weighting processing, the environmental impact factor can more accurately reflect the overall impact of each rig under specific environmental conditions.

[0021] Furthermore, the calculation formula of the loss degree is:

[0022]

[0023] In the formula, For the The loss of a drilling rig, and Respectively The maintenance frequency and usage frequency of each drilling rig, and The average maintenance frequency and average usage frequency of all drilling rigs, For normalization operation, It is a natural exponential function. This technical solution calculates the loss degree by comprehensively considering the maintenance frequency and the use frequency, reflecting the positive impact of maintenance on the equipment life and the negative impact of the use frequency on the equipment life. The natural exponential function is used to represent the impact of the maintenance frequency, so that the higher the maintenance frequency, the lower the loss degree, and this impact decays exponentially. Through the normalization operation, the loss degree value is ensured to be within a reasonable range, which is convenient for comparison and subsequent processing, and improves the standardization and interpretability of the results.

[0024] Furthermore, before calculating the environmental impact factor of any drilling rig, the following screening operation is performed on all environmental indicators: a correlation threshold is preset, and if the correlation between a certain environmental indicator and the life of the drilling rig is greater than or equal to the correlation threshold, the environmental indicator is used to calculate the environmental impact factor of the drilling rig; if the correlation between a certain environmental indicator and the life of the drilling rig is less than the correlation threshold, the environmental indicator is not used to calculate the environmental impact factor of the drilling rig. This technical solution can more accurately capture the impact of these key factors on the life of the drilling rig by screening and using only environmental indicators that are highly correlated with the life of the drilling rig for subsequent calculations, thereby improving the accuracy and reliability of the prediction model.

[0025] Furthermore, the horizontal axis of the fitting curve is the environmental impact factor of all historical drilling rigs, and the vertical axis is the life span of all historical drilling rigs.

[0026] Furthermore, the multiple environmental indicators include: a temperature indicator, a humidity indicator, a soil hardness indicator, and a particle concentration indicator, and each environmental indicator is an average value of environmental parameters corresponding to the environmental indicator during use of the drilling rig.

[0027] On the other hand, the present invention also provides a life prediction system for a crawler-type fully hydraulic directional drilling rig, the life prediction system comprising a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of any monitoring and early warning method as described in any one of the items.

[0028] The present invention has the following effects:

[0029] The present invention proposes an improved rig life prediction method. Through in-depth analysis, the specific influence of various environmental factors on the rig life is determined. On this basis, historical cases similar to the current rig working environment are selected to evaluate the error between the actual life of the rig and the predicted value of the fitting curve in these cases. By analyzing the difference between the current rig and these historical cases in terms of wear and tear and environmental factors, and performing weighted processing, a more accurate life prediction value is obtained. It not only overcomes the underfitting problem caused by limited data volume, but also better adapts to complex and changeable working environments, improves the accuracy and reliability of rig life prediction, optimizes maintenance strategies, reduces the probability of failures, and ensures the safety of the operation process to a certain extent. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] By reading the following detailed description with reference to the accompanying drawings, the above and other objects, features and advantages of the exemplary embodiments of the present invention will become readily understood. In the accompanying drawings, several embodiments of the present invention are shown in an exemplary and non-limiting manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein:

[0031] Figure 1 It is a schematic flow chart of the method of the present invention. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0033] The specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0034] Reference Figure 1A crawler-type fully hydraulic directional drilling rig life prediction method includes steps S1 to S4, which are specifically as follows:

[0035] S1: Obtain the lifespans of multiple historical drilling rigs and multiple environmental indicators that affect the lifespans, and calculate the environmental impact factor of the drilling rig based on the correlation between each environmental indicator of any drilling rig and the lifespan of the drilling rig, and the difference between the environmental indicator and the mean value of the environmental indicator in all drilling rigs.

[0036] The main purpose of this plan is to collect and analyze various factors that affect the life of the drilling rig, mainly including the impact of different external environmental conditions on the life of the drilling rig and the impact of usage on the life of the drilling rig.

[0037] Regarding the impact of external environmental conditions on the life of drilling rigs, firstly, the environmental indicators of multiple drilling rigs (including the drilling rig to be predicted and multiple historical drilling rigs obtained using big data) are obtained. The environmental indicator of each drilling rig is the mean value of the parameter corresponding to the environmental indicator during the use of the drilling rig. The drilling rig to be predicted is the drilling rig to be analyzed currently. For any drilling rig, its environmental indicators include temperature index, humidity index, soil hardness index, and particle concentration index, and each environmental indicator is the mean value of the environmental parameter corresponding to the environmental indicator during the use of the drilling rig, that is, the drilling rig will collect the environmental parameter corresponding to the environmental indicator every time it is used. Specifically, a temperature sensor is used to measure the temperature of the working environment of the drilling rig, a humidity sensor is used to measure the humidity of the working environment of the drilling rig, a soil hardness meter is used to measure the soil hardness of the working environment of the drilling rig, and an air particle monitor is used to measure the particle concentration in the working environment of the drilling rig. The mean value of the environmental parameter corresponding to the environmental indicator collected during the use of the drilling rig is used as the environmental indicator of the drilling rig. For example, a drilling rig is used 5 times during its use, and the collected temperatures are 20, 25, 30, 32, and 28 respectively. The temperature index of the drilling rig is the average of these temperatures, 27, and the other environmental indicators of the drilling rig are obtained in the same way. For the drilling rig to be predicted, its use process is the use from the beginning of use to the current analysis time. For the historical drilling rig, its use process is the use in the time period corresponding to its life. Whether it is a historical drilling rig or a drilling rig to be predicted, the calculation method of its environmental indicators is the same.

[0038] The impact of usage on the life of the drilling rig is mainly reflected by the maintenance frequency and usage frequency of the drilling rig. The maintenance records and usage records of the drilling rig (including the drilling rig to be predicted and the historical drilling rig) during its use are obtained to obtain the maintenance frequency and usage frequency.

[0039] In addition, the difference between historical drilling rigs and drilling rigs to be predicted is that the historical drilling rigs were once in normal use but are now scrapped. That is to say, the life of the historical drilling rigs is known, while the drilling rigs to be predicted are still in use and their life is unknown. In order to perform preventive maintenance on them and ensure construction safety and operating efficiency, it is necessary to predict the life of the drilling rigs to be predicted.

[0040] Next, after obtaining multiple environmental indicators of each drilling rig, a correlation analysis needs to be performed to obtain the correlation between each environmental indicator and the life of the drilling rig. Since the present invention is to predict the life of the drilling rig to be predicted, the life of the drilling rig to be predicted is unknown. Although the above steps have collected various environmental indicators of the drilling rig to be predicted, since its life is unknown, the drilling rig to be predicted does not participate in the correlation analysis between the environmental indicator and the life. Here, the life of the historical drilling rig and the environmental indicators of the historical drilling rig are used for correlation analysis to obtain the correlation between the environmental indicator and the life of the drilling rig. And the correlation analysis specifically uses the Pearson correlation coefficient, that is, each environmental indicator of all historical drilling rigs is a group of data, and the life of all historical drilling rigs is a group of data. The Pearson correlation coefficient between each environmental indicator and the life of the drilling rig is calculated, and the Pearson correlation coefficient is used as the correlation between the environmental indicator and the life of the drilling rig. For example, first obtain all temperature indicators of all historical drilling rigs to obtain a group of temperature indicators, obtain the life of all historical drilling rigs to obtain a group of life, calculate the Pearson correlation coefficient between the two groups of data, and use the Pearson correlation coefficient as the correlation between the temperature and the life of the drilling rig.

[0041] After obtaining the correlation between each environmental indicator and the life of the drilling rig, all environmental indicators are screened to obtain environmental indicators with greater correlation with the life of the drilling rig. These environmental indicators are closely related to the life of the drilling rig and are involved in subsequent calculations. Therefore, a correlation threshold is preset here, and the empirical value is 0.3. If the correlation between an environmental indicator and the life of the drilling rig is greater than or equal to 0.3, the environmental indicator is used to calculate the environmental impact factor of the drilling rig. If the correlation between an environmental indicator and the life of the drilling rig is less than 0.3, the environmental indicator is not used to calculate the environmental impact factor of the drilling rig.

[0042] Finally, according to the correlation between the selected environmental indicators and the life of the drilling rig, the degree of comprehensive influence of the external environmental conditions on the drilling rig during use is analyzed, that is, the environmental impact factor of the drilling rig. The larger the environmental impact factor, the greater the impact of the environmental indicators on the life of the drilling rig during use. On the contrary, it indicates that the environmental indicators on the life of the drilling rig during use have a smaller impact on its life. At this time, although the life of the drilling rig to be predicted is unknown, it is also possible to analyze the degree of comprehensive influence of external conditions on its use. Therefore, the drilling rig to be predicted and the historical drilling rig are put together, and the calculation formula for the environmental impact factor of any drilling rig (historical drilling rig or drilling rig to be predicted) is given as:

[0043]

[0044] In the formula, For the Environmental impact factors of each drilling rig, is the total number of rigs (the total number is equal to all historical rigs plus the rigs to be predicted), is the serial number of the environmental indicator. For the Drilling rig No. environmental indicators, For all drilling rigs The mean value of environmental indicators, For the The correlation between environmental indicators and rig life, Represents a normalization operation.

[0045] The formula calculates the environmental impact factor by summing up the impact of each environmental indicator. This ensures that all relevant environmental indicators are taken into account, rather than relying on just a single indicator. The contribution of each environmental indicator is based on its relevance to the rig life. It is certain that if the correlation between a certain environmental indicator and the life of the drilling rig is greater, it means that the change between the environmental indicator and the life of the drilling rig is closer, and the weight of the environmental indicator will be greater when weighted, so that the environmental indicator with a greater impact on the life can be highlighted.

[0046] The normalization operation can standardize the value of each environmental indicator so that it can be compared on the same scale, which helps to eliminate the impact of different dimensions and ranges and make the calculation results comparable. The normalized value It indicates the degree of deviation between the environmental index of a drilling rig and its mean, thus reflecting the deviation of the drilling rig in the environmental index. To determine the weight, the more relevant the environmental indicator is, the greater the weight is when calculating the environmental impact factor. This weight allocation method ensures that the environmental indicator with a greater impact on the life of the drilling rig occupies a more important position in the final environmental impact factor.

[0047] In summary, the formula calculates the total environmental impact factor by comprehensively considering multiple environmental indicators and weighting them based on their correlation with the rig life, ensuring that all key factors are fully considered. The normalization operation eliminates the influence of different dimensions and ranges, making the calculation results comparable, while highlighting the deviation of each rig in each environmental indicator. Through weight distribution, the formula gives higher weights to environmental indicators that have a greater impact on the rig life, improving the accuracy and reliability of the environmental impact factor. It is suitable for the unified evaluation of historical rigs and rigs to be predicted. This formula is not only applicable to historical rigs, but also to rigs to be predicted. Even if the life of the rig to be predicted is unknown, its environmental impact factor can be calculated through its environmental indicators, so as to be compared and analyzed with other historical rigs.

[0048] S2: Obtain the fitting curve of the environmental impact factor and life of all historical drilling rigs, and take the life corresponding to the environmental impact factor of the drilling rig to be predicted on the fitting curve as its initial predicted life.

[0049] Through the previous steps, the environmental impact factor of each drilling rig has been calculated. In order to analyze the relationship between the environmental impact factor and the life of the drilling rig, these data need to be fitted, including the following steps:

[0050] First, by collecting the environmental impact factors and lifespans of all historical drilling rigs and fitting them using the least squares method, a numerical change curve describing the relationship between environmental impact factors and drilling rig lifespan is obtained. The specific analysis is as follows:

[0051] The environmental impact factors and corresponding lifespans of all historical drilling rigs are collected. Since the lifespan of the drilling rig to be predicted is unknown, only the environmental impact factors and corresponding lifespans of the historical drilling rigs are used for fitting. Specifically, the least squares method is used for fitting. The least squares method is a commonly used statistical method that can find a best fitting curve so that the sum of squared errors between this curve and the actual data points is minimized. In the fitting process, the environmental impact factors of all historical drilling rigs are used as independent variables (horizontal axis), and the lifespans of all historical drilling rigs are used as dependent variables (vertical axis). Through the least squares method fitting, a numerical change curve describing the relationship between environmental impact factors and drilling rig lifespan is obtained. This fitting curve can intuitively show the changing trends of environmental impact factors and drilling rig lifespans, providing a preliminary basis for subsequent predictions.

[0052] Then, the environmental impact factors of the drilling rig to be predicted are substituted into the fitting curve to find the corresponding life value as the initial predicted life of the drilling rig to be predicted. Through this method, a preliminary life estimate can be provided for the drilling rig to be predicted based on the life of historical drilling rigs. This method not only utilizes the laws in historical data, but also provides intuitive visualization results, which helps to improve the accuracy and reliability of the prediction.

[0053] S3: Select multiple historical drilling rigs whose environmental impact factors are closest to the drilling rig to be predicted as reference drilling rigs, and determine the proximity between the drilling rig to be predicted and the reference drilling rig according to the difference in environmental impact factors and the difference in loss degree between the drilling rig to be predicted and the reference drilling rig.

[0054] In the process of predicting the life of drilling rigs, traditional curve fitting is prone to underfitting problems due to insufficient historical data, that is, the model is too simplified and cannot capture the complex changes in the data well, thus affecting the accuracy of life prediction. To solve this problem, this step finds multiple drilling rigs in the historical drilling rigs that have similar working environments (such as temperature, humidity and other environmental conditions) to the drilling rigs to be predicted as reference samples. Then, the actual service life of these reference drilling rigs is compared with the difference (i.e., error) between the life values ​​predicted by the model. By analyzing the prediction error of the life of these reference drilling rigs, a more accurate error range estimate can be provided for the life prediction of the drilling rig to be predicted.

[0055] First, select from all historical rigs The historical rigs with the closest environmental impact factors to the rig to be predicted are used as reference rigs for the rig to be predicted. Specifically, the differences (absolute values ​​of the differences) between the environmental impact factors of all historical rigs and the impact factors of the rig to be predicted are calculated, and then the differences are sorted from small to large, and the top rigs are selected. The historical drilling rigs are used as reference rigs for the drilling rigs to be predicted. is a preset value, and the present invention sets The experience value is 10.

[0056] Then, in order to more accurately predict the life of the rig to be predicted, only analyzing the environmental impact factors may not be comprehensive enough, because the maintenance frequency and use frequency of the rig are also important factors affecting its life. These factors together reflect the wear degree of the rig. Therefore, we need to further analyze the difference in wear degree between the reference rig and the rig to be predicted, and combine them with the difference in environmental impact factors to determine the degree of closeness between the two. This degree of closeness comprehensively reflects the overall similarity between the reference rig and the rig to be predicted. And in the subsequent process, these influencing factors are processed by using weighted analysis methods, and different weights are assigned according to the importance of each factor on the life of the rig, so as to ensure that the prediction model is closer to the actual situation and improve the accuracy of the prediction.

[0057] Specifically, calculate the loss degree (historical rigs and rigs to be predicted):

[0058]

[0059] In the formula, For the The loss of a drilling rig, and Respectively The maintenance frequency and usage frequency of each drilling rig, and The average maintenance frequency and average usage frequency of all drilling rigs ， For normalization operation, is a natural exponential function. This formula combines the maintenance frequency and frequency of use The calculation of the wear rate reflects the impact of these two factors on the life of the drilling rig. The higher the maintenance frequency, the smaller the wear of the drilling rig, and the higher the use frequency, the greater the wear of the drilling rig. This comprehensive consideration makes the calculation of the wear rate more comprehensive and accurate. The ratio to the average usage frequency reflects the current usage intensity of the drilling rig relative to the average level. The higher the usage intensity, the greater the wear and tear. This proportional relationship can better reflect the impact of actual usage on the wear and tear, and the same applies to maintenance frequency.

[0060] Specifically, calculate the proximity between the predicted rig and the reference rig:

[0061]

[0062] In the formula, For the drilling rig to be predicted and the The proximity of a reference rig, and Respectively Environmental impact factors and loss of reference drilling rigs, and are the environmental impact factor and loss degree of the drilling rig to be predicted, is a preset hyperparameter used to prevent the situation where the wear rates of two drilling rigs are the same. The empirical value of is 0.001. Indicates The absolute difference in environmental impact factors between the reference rig and the rig to be predicted. The smaller this value is, the more similar the environmental conditions of the two rigs are. The number indicates The absolute difference in the loss degree between the reference rig and the rig to be predicted is smaller, indicating that the use and maintenance of the two rigs are more similar. This formula combines the difference in environmental impact factors and loss degree, and attenuates it through an exponential function, which ensures that when the reference rig and the rig to be predicted are very close in environmental impact factors and loss degree, that is, and The smaller the value of , the closer the closeness between the reference rig and the predicted rig is to 1. On the contrary, if the difference is large, the closeness will decrease rapidly.

[0063] S4: Calculate the error value of the initial predicted life according to the proximity between the drilling rig to be predicted and all reference drilling rigs and the fitting errors of the lifespans of all reference drilling rigs, and use the error value to correct the initial predicted life to the final predicted life.

[0064] If the life of the drilling rig to be predicted is known, when fitting the curve, the environmental impact factor and life of the drilling rig to be predicted are also added to the fitting curve, and the fitting error of the life of the drilling rig to be predicted is calculated. In the fitting curve, the reference rig that is closer to the drilling rig to be predicted has a more similar fitting error of its life to the fitting error of the life of the drilling rig to be predicted. Therefore, in this step, when the life of the drilling rig to be predicted is unknown, the fitting error of the life of the reference rig is obtained and weighted according to the size of the proximity between the reference rig and the drilling rig to be predicted, and the error value of the initial predicted life of the drilling rig to be predicted is comprehensively estimated, and then the initial predicted life is corrected by using the fitting error to obtain the final predicted life of the drilling rig to be predicted.

[0065] Specifically, the calculation formula for the error value of the initial predicted life of the drilling rig to be predicted is:

[0066]

[0067] In the formula, is the error value of the initial predicted life of the drilling rig to be predicted, is the number of reference rigs, is the serial number of the reference rig, For the The fitting error of the life of the reference rigs, and , For the The actual value of the life of a reference rig, is the first The fitted value of the life of the reference rigs, The predicted drilling rigs and The proximity of a reference rig, For the predicted drilling rigs and The sum of the proximity of the reference rigs is As a weight pair A weighted calculation is performed, and the reference rig that is closer to the rig to be predicted has a greater weight in the weighting, which means that the fitting error of the life of the reference rig is more similar to the fitting error of the life of the rig to be predicted.

[0068] Then, the initial predicted life of the drilling rig to be predicted is corrected using the error value of the initial predicted life to obtain the final predicted life of the drilling rig to be predicted. The specific correction method is: adding the initial predicted life of the drilling rig to be predicted and the error value, and using the added value as the final predicted life of the drilling rig to be predicted.

[0069] The present invention also provides a crawler-type fully hydraulic directional drilling rig life prediction system, which includes a memory and a processor, wherein a computer program is stored in the memory, and the processor executes the computer program to implement the steps of any one of the detection methods.

[0070] In the description of this specification, "plurality" or "several" means at least two, such as two, three or more, etc., unless otherwise clearly and specifically defined.

[0071] Although this specification has shown and described a number of embodiments of the present invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Those skilled in the art will conceive of many modifications, changes and alternatives without departing from the ideas and spirit of the present invention. It should be understood that in the practice of the present invention, various alternatives to the embodiments of the present invention described herein may be employed.

Claims

1. A crawler-type fully hydraulic directional drilling rig life prediction method, characterized in that: include: The lifespans of multiple historical drilling rigs and multiple environmental indicators that affect the lifespans are obtained, and the correlation between each environmental indicator and the lifespan of the drilling rig is obtained through correlation analysis. According to the correlation between each environmental indicator of any drilling rig and the lifespan of the drilling rig, and the difference between the environmental indicator and the mean value of the environmental indicator of all drilling rigs, the environmental impact factor of the drilling rig is calculated, and the environmental impact factor is positively correlated with the correlation and the difference; wherein any drilling rig is a historical drilling rig / a drilling rig to be predicted; Obtain the fitting curve of the environmental impact factor and life of all historical drilling rigs, take the life of the environmental impact factor of the drilling rig to be predicted corresponding to the fitting curve as its initial predicted life, select multiple historical drilling rigs with the environmental impact factor closest to the drilling rig to be predicted as reference drilling rigs, and determine the proximity between the drilling rig to be predicted and the reference drilling rig according to the difference in environmental impact factor and the difference in loss degree between the drilling rig to be predicted and the reference drilling rig, and the proximity is negatively correlated with the difference in environmental impact factor and the difference in loss degree between the two. The calculation method of the proximity between the predicted rig and the reference rig is: , where For the drilling rig to be predicted and the The proximity of a reference rig, and Respectively Environmental impact factors and loss of reference drilling rigs, and are the environmental impact factor and loss degree of the drilling rig to be predicted, are the preset hyperparameters; According to the proximity between the drilling rig to be predicted and all reference drilling rigs and the fitting errors of the lifespans of all reference drilling rigs, an error value of the initial predicted lifespan is calculated, wherein the error value is positively correlated with the proximity and the fitting error, and the initial predicted lifespan is corrected to the final predicted lifespan using the error value; The calculation formula for the error value of the initial predicted life is: , where is the error value of the initial predicted life of the drilling rig to be predicted, is the number of reference rigs, is the serial number of the reference rig, For the The fitting error of the life of the reference rigs, and , For the The actual value of the life of a reference rig, is the first The fitted value of the life of the reference rigs, For the predicted drilling rigs and The sum of the proximity of the reference rigs.

2. The crawler-type fully hydraulic directional drilling rig life prediction method according to claim 1 is characterized in that: The final predicted lifespan is the sum of the error value and the initial predicted lifespan.

3. The life prediction method of crawler-type fully hydraulic directional drilling rig according to claim 1 is characterized in that: The calculation formula of the environmental impact factor of any drilling rig is: , where For the Environmental impact factors of each drilling rig, is the total number of drilling rigs, is the serial number of the environmental indicator. For the Drilling rig No. environmental indicators, For all drilling rigs The mean value of environmental indicators, For the The correlation between environmental indicators and rig life, Represents a normalization operation.

4. The crawler-type fully hydraulic directional drilling rig life prediction method according to claim 1 is characterized in that: The calculation formula of the loss degree is: , where For the The loss of a drilling rig, and Respectively The maintenance frequency and usage frequency of each drilling rig, and The average maintenance frequency and average usage frequency of all drilling rigs, For normalization operation, is a natural exponential function.

5. The crawler-type fully hydraulic directional drilling rig life prediction method according to claim 3 is characterized in that: Before calculating the environmental impact factor of any drilling rig, the following screening operations are performed on all environmental indicators: A correlation threshold is preset. If the correlation between a certain environmental indicator and the life of the drilling rig is greater than or equal to the correlation threshold, the environmental indicator is used to calculate the environmental impact factor of the drilling rig. If the correlation between a certain environmental indicator and the life of the drilling rig is less than the correlation threshold, the environmental indicator is not used to calculate the environmental impact factor of the drilling rig.

6. The crawler-type fully hydraulic directional drilling rig life prediction method according to claim 1 is characterized in that: The horizontal axis of the fitting curve is the environmental impact factor of all historical drilling rigs, and the vertical axis is the life span of all historical drilling rigs.

7. The crawler-type fully hydraulic directional drilling rig life prediction method according to claim 1 is characterized in that: The multiple environmental indicators include: a temperature indicator, a humidity indicator, a soil hardness indicator, and a particle concentration indicator, and each environmental indicator is an average value of environmental parameters corresponding to the environmental indicator during the use of the drilling rig.

8. A crawler-type fully hydraulic directional drilling rig life prediction system, characterized in that: The life prediction system comprises a memory and a processor, wherein a computer program is stored in the memory, and the processor executes the computer program to implement the steps of the life prediction method according to any one of claims 1 to 7.

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