A method for determining the validity of borehole stress gauge data

Abstract

The present invention provides a method for determining the validity of borehole stress gauge data, which belongs to the technical field of borehole stress gauge data. The method determines the validity of the data by monitoring whether the value of the borehole stress gauge increases after being affected by the advanced support pressure of the mine under the influence of mining. The method of the present invention improves the accuracy of monitoring and early warning, can verify the performance of the instrument, help enterprises to manage risks, and judge the credibility of the data according to the failure rate of a specific brand of instrument, so as to manage potential risks, and can provide valuable data support to help engineers and scientists better understand the failure mechanism of the instrument, so as to improve the design and enhance the performance and reliability of future equipment.

Description

Technical Field

[0001] The invention relates to the technical field of borehole stress gauge data, and specifically provides a method for determining the validity of borehole stress gauge data. Background Art

[0002] The "borehole stress gauge" is an instrument used to monitor the relative stress changes of the surrounding rock. It has the advantages of simple installation, low production cost, wide application range, and strong scalability. Its working principle is as follows: when the stress of the surrounding rock changes, the borehole in the surrounding rock will deform. The borehole stress gauge captures this deformation information through sensors, thereby indirectly reflecting the stress changes of the surrounding rock. In order to ensure the accuracy of the borehole stress gauge, the instrument must always be in close contact with the borehole wall, which places high demands on on-site installation and subsequent work scenarios.

[0003] In underground coal mines, the surrounding rock stress in front of the working face will inevitably increase with the recovery of the working face. The stress increase part is usually called the advance support pressure influence range. If the borehole stress gauge can work normally, the value will inevitably increase after entering the advance support pressure influence range. Summary of the invention

[0004] The technical task of the present invention is to address the above-mentioned problems and provide a method for determining the validity of borehole stress gauge data. The validity of the data can be determined by monitoring whether the reading of the borehole stress gauge increases under the influence of mining. The validity of the data can be determined based on whether the value of the borehole stress gauge increases after being affected by the advance support pressure. This improves the accuracy and reliability of mine pressure monitoring and provides a scientific basis for safe mining.

[0005] The present invention provides a method for determining the validity of borehole stress gauge data. The method determines the validity of the data by monitoring whether the value of the borehole stress gauge increases under the influence of mining and the influence of the advanced support pressure of the mine. The implementation steps include:

[0006] (1) Determine the influence distance of the mine's advanced support pressure;

[0007] (2) Extracting data affected by the advance support pressure;

[0008] (3) Data resampling;

[0009] (4) Missing value processing;

[0010] (5) Linear fitting and calculation of slope;

[0011] (6) Determine effectiveness.

[0012] The influence range of the advanced support pressure of the mine can be determined by numerical simulation, historical data analysis of borehole stress gauges and mechanical modeling. Generally, the influence range is 40 to 60 meters, and in a few cases it can reach 60 to 80 meters.

[0013] The process of determining the influence distance of the mine advance support pressure in step (1) is as follows:

[0014] As the coal mining face advances, when the value of the borehole stress gauge transitions from a stable state to a continuously rising state, the shortest distance between the borehole stress gauge and the coal mining face is the distance d affected by the advance support pressure on the borehole stress gauge. By selecting the historical data of the borehole stress gauge and taking its mean value D, the distance affected by the advance support pressure on the face can be approximately obtained. The calculation formula is as follows:

[0015] ,

[0016] in, N is the number of data, d i For the i A measurement value.

[0017] Furthermore, the process of extracting the data affected by the advance support pressure in step (2) is as follows:

[0018] Through the database, find all the borehole stress gauges that are less than D / 2 away from the coal mining face and record the numbers of these stress gauges;

[0019] For each strain gauge found, the data from the time when it is D away from the working surface to the retrieval time is extracted to form a time series data set.

[0020] Furthermore, the data resampling process in step (3) is as follows:

[0021] After extracting the time series data affected by the advance support pressure, in order to better analyze and process the data, the time series data needs to be resampled. The purpose of resampling is to expose missing values.

[0022] First, determine the appropriate resampling time interval Δt. The common resampling interval for borehole stress gauge data is usually 1 hour or 1 day.

[0023] Assume that the original time series data is {( t i ,σ i )},in t i is time, σ i is the stress value;

[0024] The resampled data is {(t' j , σ' j )},in t' j is the time point after resampling, σ' j is the stress value after resampling, and the time point of resampling t' j The calculation formula is:

[0025] ,

[0026] in, t 0 is the starting time, j The index of the resampling point.

[0027] Furthermore, since there are many possibilities for the original sampling frequency and the resampling frequency, when the resampling frequency is higher than the original sampling frequency, upsampling is required. The stress value σ' after upsampling is j Calculated by linear interpolation:

[0028] ,

[0029] in, t i-1 and t i are two adjacent time points in the original data, so that t i-1 ≤ t' j < t i .

[0030] When the resampling frequency is lower than the original sampling frequency, downsampling is required; the stress value σ' after downsampling j Calculated by the mean value method:

[0031] ,

[0032] Among them, σ ik is the original data in the time interval [ t' j , t' j +Δ t ) stress value, n is the number of data points in this time interval.

[0033] Furthermore, the missing value processing process in step (4) is as follows:

[0034] If missing values ​​are found after resampling, they need to be filled to ensure data integrity and continuity. Using linear interpolation to fill missing values ​​can effectively maintain data smoothness and trend consistency. The specific steps are similar to upsampling:

[0035] For each missing value σ' j , assuming that t' j-1 and t' j+1 At two time points, the existing stress values ​​are σ' j-1 and σ' j+1 , the linear interpolation formula is:

[0036] ,

[0037] Use the above linear interpolation formula to fill in each missing value one by one to form a complete time series data set.

[0038] Furthermore, the linear fitting and slope calculation process in step (5) is as follows:

[0039] After completing the missing value processing, the method uses the least squares method to perform linear fitting on the resampled data and calculate the slope. The specific steps are as follows:

[0040] The model selected for least squares fitting is as follows, where a is the slope and b is the intercept.

[0041] ,

[0042] Using the padded time series dataset {( t' j , σ' j )}, perform the least squares fitting, and the calculation formula is:

[0043] ,

[0044] ,

[0045] in N is the number of time series data points.

[0046] Furthermore, in step (6), after linear fitting is performed on the sequence data of a borehole stress gauge affected by the advance support pressure and the slope is calculated, it can be determined whether the data of the borehole stress gauge is valid. The specific steps are as follows:

[0047] First, determine a slope threshold a based on actual conditions and experience. threshold , for example, it can be specified as 0; this threshold is used to distinguish valid and invalid data;

[0048] If the slope 𝑎 is lower than the threshold a threshold , the data of the borehole stress gauge is considered invalid;

[0049] If the slope 𝑎 is greater than or equal to the threshold a threshold , then the data of the borehole stress gauge is considered valid.

[0050] Furthermore, when the borehole stress gauge enters the advanced support pressure range of the coal mining face, its data presents a waveform rising trend, and the borehole stress gauge can effectively monitor the borehole shrinkage caused by the stress increase;

[0051] When the borehole stress gauge enters the advance support pressure range of the coal mining face, its data shows a waveform downward trend. This may be due to oil bag leakage or borehole collapse, which causes the stress gauge to be unable to effectively monitor the change in relative stress.

[0052] Compared with the prior art, the method for determining the validity of borehole stress gauge data of the present invention has the following outstanding beneficial effects:

[0053] 1. Improve the accuracy of monitoring and early warning: This method can be used to identify abnormal instruments in advance and prevent abnormal instruments from affecting monitoring and early warning results.

[0054] 2. It can verify instrument performance and help companies manage risks: based on the failure rate of a specific brand of instrument, the credibility of the data can be judged to manage potential risks.

[0055] 3. Supporting equipment performance improvement and analysis: By analyzing the state of the instrument when it is close to failure in detail, this method can provide valuable data support to help engineers and scientists better understand the failure mechanism of the instrument, thereby improving the design and enhancing the performance and reliability of future equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 This is a schematic diagram of effective judgment of the borehole stress gauge data of the present invention;

[0057] Figure 2 It is a schematic diagram for judging that the drilling stress gauge data is invalid according to the present invention. DETAILED DESCRIPTION

[0058] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0059] Example 1: Figure 1 As shown in the figure, the validity of the data of borehole stress gauge No. 1501 is determined by monitoring whether the value of the borehole stress gauge increases under the influence of mining and the advanced support pressure of the mine. The implementation steps include:

[0060] (1) Determine the influence distance of the mine's advanced support pressure

[0061] As the coal mining face advances, when the value of the borehole stress gauge transitions from a stable state to a continuously rising state, the shortest distance between the borehole stress gauge and the coal mining face is the distance d affected by the advance support pressure on the borehole stress gauge. By selecting the historical data of the borehole stress gauge and taking its mean value D, the distance affected by the advance support pressure on the face can be approximately obtained. The calculation formula is as follows:

[0062] ,

[0063] in, N is the number of data, d i For the i A measurement value.

[0064] If borehole stress gauge No. 1501 belongs to working face A, and when the value of the historical borehole stress gauge of working face A in the database transitions from a stable state to a continuously rising state, the shortest distance d between the borehole stress gauge and the coal mining working face is {60, 65, 70, 75, 80} meters. It can be approximately considered that the influence range D of the advance support pressure of working face A and working faces with similar conditions to working face A is 70 meters.

[0065] (2) Extracting data affected by advance support pressure

[0066] Through the database, find all the coal mining faces that are less than D / 2 (i.e. 35m) borehole stress gauges, record the numbers of these stress gauges;

[0067] For each strain gauge found, extract its distance from the working surface as D The data from the time (i.e. 70m) to the retrieval time forms a time series data set.

[0068] (3) Data resampling

[0069] First, the sampling method is determined according to the raw data sampling interval and the target sampling interval. Here, taking the raw data sampling interval of the borehole stress gauge as 1 minute and the target sampling interval as 24 hours as an example, the raw data needs to be processed by the downsampling method.

[0070] Assume that the original time series data is {( t i ,σ i )},in t i is time, σ i is the stress value;

[0071] The resampled data is {( t' j , σ' j )},in t' j is the time point after resampling, σ' j is the stress value after resampling, and the time point of resampling t' j The calculation formula is:

[0072] ,

[0073] in, t 0 is the starting time, j The index of the resampling point.

[0074] Since there are many possibilities for the original sampling frequency and the resampling frequency, when the resampling frequency is higher than the original sampling frequency, upsampling is required. The stress value after upsampling is σ' j Calculated by linear interpolation:

[0075] ,

[0076] in, t i-1 and t i are two adjacent time points in the original data, so that t i-1 ≤ t' j < t i .

[0077] When the resampling frequency is lower than the original sampling frequency, downsampling is performed; the stress value σ' after downsampling j Calculated by the mean value method:

[0078] ,

[0079] Among them, σ ik is the original data in the time interval [ t' j , t' j +Δ t ) stress value, n is the number of data points in this time interval.

[0080] Since the amount of original data is too large in this embodiment, only the resampled data is shown, as shown in Table 1.

[0081] Table 1

[0082] date Average stress / MPa date Average stress / MPa date Average stress / MPa 2023 / 1 / 1 5.488672 2023 / 1 / 11 5.194415 2023 / 1 / 21 6.609927 2023 / 1 / 2 5.022594 2023 / 1 / 12 5.557803 2023 / 1 / 22 Nan 2023 / 1 / 3 5.009716 2023 / 1 / 13 5.288037 2023 / 1 / 23 4.408812 2023 / 1 / 4 5.001901 2023 / 1 / 14 5.761609 2023 / 1 / 24 4.985492 2023 / 1 / 5 5.506357 2023 / 1 / 15 6.624662 2023 / 1 / 25 6.294371 2023 / 1 / 6 5.286946 2023 / 1 / 16 5.878968 2023 / 1 / 26 6.448881 2023 / 1 / 7 5.409832 2023 / 1 / 17 5.854362 2023 / 1 / 27 5.741179 2023 / 1 / 8 5.633922 2023 / 1 / 18 6.259553 2023 / 1 / 28 6.163246 2023 / 1 / 9 5.429946 2023 / 1 / 19 6.456069 2023 / 1 / 29 5.736147 2023 / 1 / 10 5.35984 2023 / 1 / 20 6.379498

[0083] (4) Missing value processing

[0084] In this example, the data for 2023 / 1 / 22 is missing, so σ' j-1 =6.609927,σ' j+1 =4.408812, t' j-1 =2023 / 1 / 21, t' j+1 =2023 / 1 / 23Substitute into the linear interpolation formula:

[0085] ,

[0086] Through calculation, the missing data of the borehole stress gauge on 2023 / 1 / 22 can be filled with 5.5093695.

[0087] (5) Linear fitting and slope calculation

[0088] After completing the missing value processing, the least squares method is used to perform linear fitting on the resampled data and calculate the slope. The specific steps are as follows:

[0089] The model selected for least squares fitting is as follows, where a is the slope and b is the intercept.

[0090] ,

[0091] Using the padded time series dataset {( t' j , σ' j )}, perform the least squares fitting, and the calculation formula is:

[0092] ,

[0093] ,

[0094] in N is the number of time series data points, in this embodiment N is 29.

[0095] The model fitted by the least squares method is:

[0096] (6) Determine effectiveness.

[0097] First, determine a slope threshold a based on actual conditions and experience. thresholdis 0, which is used to distinguish valid and invalid data; when the slope of the specific borehole stress gauge data fitting model is greater than 0, the borehole stress gauge and the data generated by it are considered valid; when the slope of the specific borehole stress gauge data fitting model is less than 0, the borehole stress gauge and the data generated by it are considered invalid.

[0098] like Figure 1 As shown, when the No. 1501 borehole stress gauge enters the advance support pressure range of the coal mining face, its data presents an upward waveform trend, and the slope of the fitting model is 0.029. Therefore, the borehole stress gauge can effectively monitor the borehole shrinkage caused by increased stress.

[0099] Example 2: Figure 2 As shown in the figure, the validity of the data of borehole stress gauge No. 1528 is determined by monitoring whether the value of the borehole stress gauge increases under the influence of mining and the advanced support pressure of the mine. The implementation steps include:

[0100] (1) Determine the influence distance of the mine's advanced support pressure

[0101] As the coal mining face advances, when the value of the borehole stress gauge transitions from a stable state to a continuously rising state, the shortest distance between the borehole stress gauge and the coal mining face is the distance d affected by the advance support pressure on the borehole stress gauge. By selecting the historical data of the borehole stress gauge and taking its mean value D, the distance affected by the advance support pressure on the face can be approximately obtained. The calculation formula is as follows:

[0102] ,

[0103] in, N is the number of data, d i For the i A measurement value.

[0104] If borehole stress gauge No. 1528 belongs to working face A, and when the value of the historical borehole stress gauge of working face A in the database transitions from a stable state to a continuously rising state, the shortest distance d between the borehole stress gauge and the coal mining working face is {60, 65, 70, 75, 80} meters. It can be approximately considered that the influence range D of the advance support pressure of working face A and working faces with similar conditions to working face A is 70 meters.

[0105] (2) Extracting data affected by advance support pressure

[0106] Through the database, find all the borehole stress gauges that are less than D / 2 (i.e. 35m) from the coal mining face and record the numbers of these stress gauges;

[0107] For each strain gauge found, the data from the time when the distance from the working surface is D (i.e. 70m) to the retrieval time is extracted to form a time series data set.

[0108] (3) Data resampling

[0109] First, the sampling method is determined according to the raw data sampling interval and the target sampling interval. Here, taking the raw data sampling interval of the borehole stress gauge as 1 minute and the target sampling interval as 24 hours as an example, the raw data needs to be processed by the downsampling method.

[0110] Assume that the original time series data is {( t i ,σ i )},in t i is time, σ i is the stress value;

[0111] The resampled data is {( t' j , σ' j )},in t' j is the time point after resampling, σ' j is the stress value after resampling, and the time point of resampling t' j The calculation formula is:

[0112] ,

[0113] in, t 0 is the starting time, j The index of the resampling point.

[0114] Since there are many possibilities for the original sampling frequency and the resampling frequency, when the resampling frequency is higher than the original sampling frequency, upsampling is required. The stress value after upsampling is σ' j Calculated by linear interpolation:

[0115] ,

[0116] in, t i-1 and t i are two adjacent time points in the original data, so that t i-1 ≤ t' j < t i .

[0117] When the resampling frequency is lower than the original sampling frequency, downsampling is performed; the stress value σ' after downsampling j Calculated by the mean value method:

[0118] ,

[0119] where σ ik is the original data in the time interval [ t' j , t' j +Δ t ) stress value, n is the number of data points in this time interval.

[0120] Since the amount of original data is too large in this embodiment, only the resampled data is shown, as shown in Table 2.

[0121] Table 2

[0122] date Average stress / MPa date Average stress / MPa date Average stress / MPa 2023 / 1 / 1 5.604416 2023 / 1 / 11 5.4968256 2023 / 1 / 21 5.047461 2023 / 1 / 2 5.725811 2023 / 1 / 12 5.6323991 2023 / 1 / 22 5.098436 2023 / 1 / 3 5.766223 2023 / 1 / 13 5.7271774 2023 / 1 / 23 5.197797 2023 / 1 / 4 5.808373 2023 / 1 / 14 5.3945859 2023 / 1 / 24 5.488677 2023 / 1 / 5 5.915642 2023 / 1 / 15 5.4875108 2023 / 1 / 25 5.599526 2023 / 1 / 6 5.967391 2023 / 1 / 16 5.6226056 2023 / 1 / 26 5.654489 2023 / 1 / 7 6.074783 2023 / 1 / 17 5.8457888 2023 / 1 / 27 5.644541 2023 / 1 / 8 5.586704 2023 / 1 / 18 5.901148 2023 / 1 / 28 5.802813 2023 / 1 / 9 5.375291 2023 / 1 / 19 5.7678766 2023 / 1 / 29 5.818179 2023 / 1 / 10 5.440352 2023 / 1 / 20 5.283898 2023 / 1 / 30 5.301048 2023 / 1 / 31 4.929543

[0123] (4) Missing value processing

[0124] In this embodiment, there are no missing values, so there is no need to perform missing value processing.

[0125] (5) Linear fitting and slope calculation

[0126] After completing the missing value processing, the least squares method is used to perform linear fitting on the resampled data and calculate the slope. The specific steps are as follows:

[0127] The model selected for least squares fitting is as follows, where a is the slope and b is the intercept.

[0128] ,

[0129] Using the time series dataset in Table 2 {( t' j , σ' j )}, perform the least squares fitting, and the calculation formula is:

[0130] ,

[0131] ,

[0132] in N is the number of time series data points, in this embodiment N is 31.

[0133] The model fitted by the least squares method is:

[0134] (6) Determine effectiveness.

[0135] First, determine a slope threshold a based on actual conditions and experience. threshold is 0, which is used to distinguish valid and invalid data; when the slope of the specific borehole stress gauge data fitting model is greater than 0, the borehole stress gauge and the data generated by it are considered valid; when the slope of the specific borehole stress gauge data fitting model is less than 0, the borehole stress gauge and the data generated by it are considered invalid.

[0136] like Figure 2 As shown, when the No. 1528 borehole stress gauge entered the advance support pressure range of the coal mining face, its data showed a waveform downward trend, and the slope of the fitting model was -0.013. Therefore, the stress gauge could not effectively monitor the change of relative stress.

[0137] The embodiments described above are only preferred specific implementations of the present invention. Common changes and substitutions made by those skilled in the art within the scope of the technical solution of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for determining the validity of borehole stress gauge data, characterized in that: The method determines the validity of data by monitoring whether the value of the borehole stress gauge increases under the influence of mining and the advanced support pressure of the mine. The implementation steps include: (1) Determine the influence distance of the mine's advanced support pressure. The determination process is as follows: As the coal mining face advances, when the value of the borehole stress gauge transitions from a stable state to a continuously rising state, the shortest distance between the borehole stress gauge and the coal mining face is the distance d affected by the advance support pressure on the borehole stress gauge. By selecting the historical data of the borehole stress gauge and taking its mean value D, the distance affected by the advance support pressure on the face can be approximately obtained. The calculation formula is as follows: Where N is the number of data, d i is the i-th measurement value; (2) Extract the data affected by the advance support pressure. The extraction process is as follows: Through the database, find all the borehole stress gauges that are less than D / 2 away from the coal mining face and record the numbers of these borehole stress gauges; For each found borehole stress gauge, extract the data from the time when the distance from the working surface is D to the retrieval time to form a time series data set; (3) Data resampling, the process is as follows: First, determine the appropriate resampling time interval Δt; Assume that the original time series data is {(t i , σ i )}, where t i is time, σ i is the stress value; The resampled data is {(t′ j ,σ′ j )}, where t′ j is the time point after resampling, σ′ j is the stress value after resampling, and the calculation formula of the resampling time point t′j is: t′ j =t0+j·Δt Where t0 is the starting time and j is the index of the resampling point; When the resampling frequency is higher than the original sampling frequency, upsampling is performed and the stress value after upsampling is σ′ j Calculated by linear interpolation; When the resampling frequency is lower than the original sampling frequency, downsampling is performed; the stress value σ′ after downsampling j Calculated by the mean value method; (4) Missing value processing: The processing process is as follows: If missing values ​​are found after resampling, linear interpolation is used to fill in the missing values. (5) Linear fitting and calculation of slope; (6) Determine the effectiveness. The process is as follows: First, determine a slope threshold value a based on actual conditions and experience. threshold , used to distinguish valid and invalid data; If the slope a is lower than the threshold a threshold , the data of the borehole stress gauge is considered invalid; If the slope a is greater than or equal to the threshold a threshold , then the data of the borehole stress gauge is considered valid.

2. A method for determining the validity of borehole stress gauge data according to claim 1, characterized in that: The stress value σ′ after upsampling j Calculated by linear interpolation: Among them, t i-1 and t i are two adjacent time points in the original data, so that t i-1 ≤t′ j <t i .

3. The method for determining the validity of borehole stress gauge data according to claim 1, characterized in that: The stress value after downsampling σ′ j Calculated by the mean value method: Among them, σ ik is the original data in the time interval [t′ j , t′ j +Δt), and n is the number of data points in this time interval.

4. A method for determining the validity of borehole stress gauge data according to claim 2 or 3, characterized in that: The missing value calculation process in step (4) is as follows: For each missing value σ′ j , assuming that at t′ j-1 and t′ j+1 At two time points, the existing stress values ​​are σ′ j-1 and σ′ j+1 , the linear interpolation formula is: Use the above linear interpolation formula to fill in each missing value one by one to form a complete time series data set.

5. A method for determining the validity of borehole stress gauge data according to claim 4, characterized in that: The linear fitting and slope calculation process in step (5) is as follows: The model selected for least squares fitting is as follows, where a is the slope and b is the intercept. σ(t)=at+b Use the filled time series data set {(t′j, σ′j)} to perform least squares fitting, and the calculation formula is: Where N is the number of time series data points.

6. A method for determining the validity of borehole stress gauge data according to claim 5, characterized in that: When the borehole stress gauge enters the advanced support pressure range of the coal mining face, its data presents a waveform rising trend. The borehole stress gauge can effectively monitor the borehole shrinkage caused by the stress increase. When the borehole stress gauge enters the advance support pressure range of the coal mining face, its data presents a waveform downward trend, and the borehole stress gauge cannot effectively monitor the change of relative stress.

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