Method for measuring drilling dust index of wet drilling operation in mine

Abstract

The application discloses a drilling dust index measurement construction method for mine wet drilling operation and belongs to the technical field of coal mine gas outburst prediction. The method comprises the following steps: wet drilling is adopted in the rock section of the coal uncovering working face of the vertical shaft well shaft; after the drilling reaches coal, air pressure is used to blow mud, and the drilling is carried out in the mode of air pressure slag discharge; the air flow of air pressure slag discharge is used to cooperate with a hole mouth sample separation screen to separate coal samples; a closed fixed-point coring device is used to obtain coal samples and record exposure time; a drilling dust gas desorption index value is measured, is corrected into an equivalent dry coal sample index value through a grading correction coefficient, and is combined with a three-dimensional geological model, stress field monitoring data and an LSTM neural network algorithm to dynamically evaluate outburst danger. The application further discloses a close-distance coal seam group vertical shaft coal uncovering intelligent management and control system. The application solves the problem of drilling dust gas desorption index distortion under the condition of wet drilling, realizes the collaborative optimization of coal uncovering construction safety and dust prevention and treatment, and improves the accuracy and construction safety of the close-distance coal seam group vertical shaft coal uncovering gas outburst prediction.

Description

Technical Field

[0001] This invention belongs to the field of coal mine gas outburst prediction technology, specifically relating to a construction method for measuring drill cuttings index in wet drilling operations in mines. Background Technology

[0002] Coal and gas outbursts are one of the most serious hazards in underground coal mines. Especially during the process of exposing outburst-prone coal seams in vertical shafts, the probability of a gas outburst increases significantly due to severe damage to the geological structure and increased fissures in the surrounding rock strata. The drill cuttings gas desorption index method (including K1 and Δh2 indices) is currently one of the main methods for predicting the risk of coal and gas outbursts, characterized by its simplicity, speed, and intuitiveness.

[0003] According to the "Method for Determination of Gas Desorption Index in Drill Cuttings" (AQ / T 1065-20) issued in 2008, the gas desorption index in drill cuttings can be determined using either dry or wet drilling methods. However, in deep working environments such as coal seam exposure in vertical shafts, wet drilling is typically used for dust suppression and construction safety considerations. During wet drilling, the contact between water and the coal sample alters the gas desorption characteristics of the coal, leading to a significant difference between the measured gas desorption index in drill cuttings and that in dry coal samples, directly affecting the accuracy of outburst risk prediction.

[0004] The existing technology has the following problems: First, the moisture content of coal samples is unstable under wet drilling conditions, the gas desorption law is complex, and there is a lack of a unified index correction method; Second, wet coal sample screening is difficult, and traditional sampling methods take too long, resulting in excessive exposure time of coal samples; Third, there is a lack of coordination with three-dimensional geological modeling and stress field monitoring, making it difficult to achieve dynamic early warning of prominent hazards; Fourth, the layout and construction of multiple predictive boreholes during the coal exposure process in vertical shafts lack a systematic and standardized operation process.

[0005] Therefore, there is an urgent need for a construction method for measuring drill cuttings indicators suitable for wet drilling operations in mines, which can solve the problem of distorted indicators in wet coal samples, improve prediction accuracy, and be integrated with modern intelligent mining technology to achieve full-process safety control of coal uncovering projects. Summary of the Invention

[0006] The main objective of this invention is to overcome the shortcomings of existing methods for measuring drill cuttings parameters in wet drilling operations in mines, and to provide a new method for measuring drill cuttings parameters in wet drilling operations in mines. The technical problem to be solved is to achieve accurate measurement of drill cuttings gas desorption parameters while maintaining the dust reduction advantages of wet drilling, thus making it more practical and having industrial application value.

[0007] Another objective of this invention is to provide a method for measuring drill cuttings index in wet drilling operations in mines. The technical problem to be solved is to establish an equivalent conversion relationship between the gas desorption index of wet coal samples and dry coal samples, eliminate the influence of moisture on the measurement results, and thus make it more suitable for practical use.

[0008] Another objective of this invention is to provide a method for measuring drill cuttings parameters in wet drilling operations in mines. The technical problem to be solved is to standardize the coal sample collection, exposure time control, and parameter measurement, thereby improving the reliability and repeatability of the measurement results and making them more suitable for practical use.

[0009] Another objective of this invention is to provide a method for measuring drill cuttings index in wet drilling operations in mining. The technical problem to be solved is to integrate three-dimensional geological modeling, stress field monitoring and intelligent algorithms to achieve dynamic and accurate prediction of prominent hazards, thereby making it more suitable for practical use.

[0010] This invention provides a method for measuring drill cuttings parameters in wet drilling operations in mining, characterized by comprising the following steps:

[0011] Wet drilling operations are carried out at the coal uncovering face of the vertical shaft, with a borehole diameter of 50mm to 75mm. Wet drilling is used in rock sections to reduce dust.

[0012] After drilling through coal, the drill rod is withdrawn, and compressed air is used to blow away the mud in the hole. Then, the compressed air slag removal method is switched to drilling until the top or bottom of the coal seam is reached.

[0013] After drilling into the coal seam, at a depth of 0.2m to 0.3m before the predetermined sampling depth, the coal sample is screened using the impact force of the compressed air slag discharge flow and the orifice sieve to obtain a coal sample with a particle size of 1mm to 3mm.

[0014] A closed-loop fixed-point coring device was used to collect coal samples, and a timing device was started simultaneously to record the coal sample exposure time t0. When measuring the K1 index, t0 ≤ 2 min, and when measuring the Δh2 index, t0 = 3 min.

[0015] The sieved coal sample was loaded into a gas desorption instrument, and the gas desorption index value of the drill cuttings was measured.

[0016] Based on the pre-established correction coefficients for gas desorption indices in dry and wet coal samples, the measured index values ​​are corrected to equivalent dry coal sample index values.

[0017] Based on the corrected gas desorption index value of drill cuttings, combined with a three-dimensional geological model, stress field monitoring data, and LSTM neural network algorithm, a dynamic assessment of prominent hazards is conducted.

[0018] Preferably, the compressed air slag removal method uses a gas-water mixture for slag removal, wherein the gas volume ratio is ≥80% and the liquid volume ratio is ≤20%, which ensures both slag removal efficiency and controls the moisture content of the coal sample.

[0019] Preferably, the coal sample screening using the impact force of the compressed air slag discharge flow in conjunction with the orifice-type sampling sieve includes:

[0020] Install a double-layer sieve at the borehole opening, with the upper sieve having a 3mm aperture and the lower sieve having a 1mm aperture.

[0021] The coal sample is screened in real time using the impact force of the compressed air slag discharge flow, with the airflow velocity controlled between 8m / s and 15m / s.

[0022] Alternatively, the impact force of the air-water mixed slag discharge medium can be used for screening, with the medium flow rate controlled at 3m / s to 6m / s;

[0023] Collect coal samples with a particle size of 1mm to 3mm from the lower sieve, and after dehumidification for no more than 10 seconds, transfer them to a closed-type fixed-point coring device.

[0024] Preferably, the closed-loop fixed-point coring device includes:

[0025] The coal sample cup has a volume of 8.6 cm³, a wall thickness of 1.5 mm to 3.0 mm, and is made of 316L stainless steel or high-strength aluminum alloy. The cup mouth is equipped with a sealing cap, which is connected to the cup body by thread or snap-fit. The sealing ring is made of fluororubber.

[0026] The coal sample container has a volume of 300 cm³ and can withstand a gas pressure of ≥6 MPa. The container is equipped with an inlet valve, an exhaust valve, and a pressure measuring interface.

[0027] The quick-connect mechanism enables a rapid sealing connection between the coal sample cup and the coal sample container, with the connection time controlled within 10 seconds.

[0028] Preferably, the method for establishing the correction coefficients for the gas desorption index of the dry and wet coal samples includes:

[0029] Under laboratory conditions, dry and wet coal samples with the same gas adsorption equilibrium pressure were prepared. The moisture content of the wet coal sample was simulated under the on-site compressed gas discharge conditions.

[0030] The desorption indices K1 and Δh2 of drill cuttings gas were measured for dry and wet coal samples, respectively.

[0031] Establish the mapping relationship between the index values ​​of wet coal samples and the index values ​​of dry coal samples, and determine the correction coefficient K, where K1(dry) = K1(wet) × Kcorrection1, Δh2(dry) = Δh2(wet) × Kcorrection2;

[0032] The correction factor is determined according to the following classification criteria:

[0033] When the coal seam gas pressure P < 1.0 MPa, K correction 1 = 1.20 ~ 1.30, K correction 2 = 1.15 ~ 1.25;

[0034] When 1.0MPa≤P<2.0MPa, Kcorrection 1=1.30~1.45, Kcorrection 2=1.25~1.40;

[0035] When P ≥ 2.0 MPa, K correction 1 = 1.45~1.60, K correction 2 = 1.40~1.55;

[0036] The above coefficients are finely adjusted based on the coal quality characteristic firmness coefficient f and the coal sample moisture content w: the upper limit is taken when f < 0.5, and the lower limit is taken when f > 0.8; when w > 15%, K correction increases by 0.05 to 0.10, and when w < 8%, K correction decreases by 0.05 to 0.10.

[0037] Preferably, the construction of the three-dimensional geological model includes:

[0038] It integrates multi-source data from geological exploration, logging, and well inspection, and applies geostatistical theory and machine learning algorithms.

[0039] High-precision three-dimensional geological models are established using the Petrel platform or similar geological modeling software to reveal stratigraphic interfaces, structural features, and the evolution of coal and rock strata parameters.

[0040] The model accuracy meets the following requirements: coal seam thickness error ≤ 0.3m, coal seam dip angle error ≤ 3°, and fault location error ≤ 5m.

[0041] Preferably, the stress field monitoring data includes:

[0042] Stress monitoring boreholes were drilled around the coal face and stress sensors were installed.

[0043] Real-time monitoring of coal seam stress changes, surrounding rock deformation, and gas pressure dynamics;

[0044] The monitoring data is transmitted via wired or wireless means to the safety management and control system for coal uncovering operations in the shaft.

[0045] Preferably, the dynamic assessment of prominent hazards includes:

[0046] A prominent hazard prediction model based on LSTM neural network is established. The LSTM network includes an input layer, two hidden layers and an output layer. The input parameters include the corrected drill cuttings gas desorption index, three-dimensional geological model parameters, stress field monitoring data and borehole layout parameters. The output results are four levels: no prominent hazard, prominent threat, prominent hazard and severe prominent hazard.

[0047] The evaluation cycle is synchronized with the drilling construction progress, enabling accurate prediction of the entire coal uncovering project process.

[0048] Preferably, the drilling arrangement for the wet drilling operation includes:

[0049] The first round of predictive boreholes: When the working face is excavated to a distance of 5m to 6m from the normal of the coal seam, the number of boreholes shall not be less than 3. One borehole shall be located in the middle of the working face and arranged slightly above the working face in the direction of advance. The other two boreholes shall be located in the upper left corner and the upper right corner respectively. The final borehole point shall be located 5m above the working face outline and 3m to the sides.

[0050] Second round of predictive drilling: When the first round of prediction indicates no outburst risk, the drilling will be arranged when the working face has been excavated to a distance of 3m to 4m from the normal of the coal seam. The drilling method is the same as the first round, and the final drilling point is located 3m above the working face outline and 2.5m to the sides.

[0051] The third round of predictive drilling: When the second round predicts no outburst danger, the drilling will be arranged when the working face is excavated to a distance of 1.5m to 2m from the normal of the coal seam. The drilling method is the same as the first round, and the final drilling point is located 2m above the working face outline and 1.5m to the sides.

[0052] The method for measuring drill cuttings parameters in wet drilling operations in mining provided by this invention is characterized by further including intelligent control measures:

[0053] A blowout preventer is installed at the borehole opening of a gas extraction borehole. The blowout preventer includes a borehole sealer, a gas extraction pipe, and a pressure relief valve, with a pressure-bearing capacity of ≥2MPa.

[0054] An automatic waterproof slag removal device is adopted to achieve automatic separation and treatment of drilling slag, with a separation efficiency of ≥95%;

[0055] Infrared thermal imaging technology is used to monitor gas extraction pipelines in real time with an accuracy of ±0.5℃, and an automatic alarm is triggered when a leak is detected.

[0056] Establish an intelligent management and control system for the entire lifecycle of coal uncovering construction in the shaft, integrating the aforementioned monitoring data to achieve dynamic collaborative management and control of construction through multi-source data fusion.

[0057] This invention also provides an intelligent control system for coal seam group vertical shaft coal exposure in close proximity, characterized in that it includes:

[0058] Blowout prevention device at the orifice of gas extraction borehole, with a pressure resistance capacity of ≥2MPa;

[0059] Automatic waterproof slag discharge equipment with a slag discharge capacity of ≥5m³ / h and a separation efficiency of ≥95%;

[0060] The infrared thermal imaging monitoring module performs real-time temperature monitoring of the gas extraction pipeline with a temperature resolution of ≤0.1℃.

[0061] The central control platform integrates data from the aforementioned devices to achieve intelligent control of the entire extraction system throughout its lifecycle, with an early warning response time of ≤10s.

[0062] The objective of this invention and the technical problem it solves are achieved through the following technical solution. A method for measuring drill cuttings parameters in wet drilling operations in mining, according to this invention, includes the following steps:

[0063] Wet drilling operations are conducted at the coal seam face of the vertical shaft, with borehole diameters ranging from 50mm to 75mm. Wet drilling is used in rock sections. After coal is encountered, the drill rod is withdrawn, and compressed air is used to blow away the mud in the borehole. Drilling is then switched to compressed air slag removal until the top or bottom of the coal seam is reached. After the borehole enters the coal seam, 0.2m to 0.3m before the predetermined sampling depth, the impact force of the compressed air slag removal airflow is used in conjunction with the borehole sampling sieve to screen coal samples, obtaining coal samples with a particle size of 1mm to 3mm. A closed-loop fixed-point coring device is used to collect coal samples, and the process is synchronized with the operation of the core sampling device. A timing device records the coal sample exposure time t0, where t0 ≤ 2 min when measuring K1 index and t0 = 3 min when measuring Δh2 index; the sieved coal sample is loaded into a gas desorption instrument to measure the gas desorption index value of the drill cuttings; based on the pre-established correction coefficients for the gas desorption index of dry and wet coal samples, the measured index values ​​are corrected to the equivalent dry coal sample index values; based on the corrected gas desorption index values ​​of the drill cuttings, combined with a three-dimensional geological model, stress field monitoring data, and LSTM neural network algorithm, a dynamic assessment of outburst risk is conducted.

[0064] The objectives of this invention and the technical problems it addresses can be further achieved by the following technical measures.

[0065] The aforementioned method for measuring drill cuttings index in wet drilling operations for mining uses a gas-water mixture for slag removal, wherein the gas volume ratio is ≥80% and the liquid volume ratio is ≤20%, which ensures slag removal efficiency while controlling the moisture content of the coal sample.

[0066] The aforementioned method for measuring drill cuttings index in wet drilling operations in mines, wherein the coal sample screening using the impact force of compressed air slag discharge airflow in conjunction with the borehole sampling screen includes: installing a double-layer sampling screen at the borehole opening, with the upper screen having a 3mm aperture and the lower screen having a 1mm aperture; using the impact force of compressed air slag discharge airflow to screen the coal sample in real time, with the airflow velocity controlled at 8m / s to 15m / s; or using the impact force of a gas-water mixed slag discharge medium for screening, with the medium flow velocity controlled at 3m / s to 6m / s; collecting coal samples with a particle size of 1mm to 3mm from the lower screen, and transferring them to a closed-type fixed-point coring device after dehumidification for no more than 10 seconds.

[0067] The aforementioned method for measuring drill cuttings index in wet drilling operations in mines includes a closed-type fixed-point coring device comprising: a coal sample cup with a volume of 8.6 cm³, a wall thickness of 1.5 mm to 3.0 mm, made of 316L stainless steel or high-strength aluminum alloy, with a sealing cap at the mouth of the cup, the sealing cap being connected to the cup body by a threaded or snap-fit ​​connection, and the sealing ring being made of fluororubber; a coal sample container with a volume of 300 cm³, capable of withstanding a gas pressure of ≥6 MPa, the container being equipped with an inlet valve, an exhaust valve, and a pressure measuring interface; and a quick-connect mechanism to achieve a quick sealing connection between the coal sample cup and the coal sample container, with the connection time controlled within 10 seconds.

[0068] The objective of this invention and the solution to its technical problem are further achieved by the following technical solution. The method for establishing correction coefficients for gas desorption indices in dry and wet coal samples, as proposed in this invention, includes: preparing dry and wet coal samples with the same gas adsorption equilibrium pressure under laboratory conditions; simulating the moisture content of the wet coal sample under on-site compressed air slag discharge conditions; measuring the gas desorption indices K1 and Δh2 of the drill cuttings in the dry and wet coal samples respectively; establishing a mapping relationship between the index values ​​of the wet and dry coal samples, and determining the correction coefficient Kcorrection, where K1(dry) = K1(wet) × Kcorrection1, Δh2(dry) = Δh2(wet) × Kcorrection2; the correction coefficient is determined according to the following grading standard: when the coal seam gas pressure P < 1.0 MPa... When 'a', K correction 1 = 1.20–1.30, K correction 2 = 1.15–1.25; when 1.0 MPa ≤ P < 2.0 MPa, K correction 1 = 1.30–1.45, K correction 2 = 1.25–1.40; when P ≥ 2.0 MPa, K correction 1 = 1.45–1.60, K correction 2 = 1.40–1.55; the above coefficients are finely adjusted according to the coal quality characteristic firmness coefficient f and the coal sample moisture content w: when f < 0.5, the upper limit is taken, and when f > 0.8, the lower limit is taken; when w > 15%, K correction increases by 0.05–0.10, and when w < 8%, K correction decreases by 0.05–0.10.

[0069] The objectives of this invention and the technical problems it addresses can be further achieved by the following technical measures.

[0070] The aforementioned method for measuring drill cuttings in wet drilling operations in mining includes the following three-dimensional geological model construction: integrating multi-source data from geological exploration, logging, and well inspection; applying geostatistical theory and machine learning algorithms; establishing a high-precision three-dimensional geological model using the Petrel platform or similar geological modeling software to reveal stratigraphic interfaces, structural features, and the evolution of coal and rock strata parameters; the model accuracy meets the following requirements: coal seam thickness error ≤ 0.3m, coal seam dip angle error ≤ 3°, and fault location error ≤ 5m.

[0071] The aforementioned method for measuring drill cuttings in wet drilling operations in mines includes the following stress field monitoring data: stress monitoring boreholes are arranged around the coal seam and stress sensors are installed; coal seam stress changes, surrounding rock deformation and gas pressure dynamics are monitored in real time; and the monitoring data is transmitted to the mine shaft coal seam exposure construction safety management and control system via wired or wireless transmission.

[0072] The aforementioned method for measuring drill cuttings in wet drilling operations in mines includes a dynamic evaluation of outburst risk, which comprises: establishing an outburst risk prediction model based on an LSTM neural network. The LSTM network includes an input layer, two hidden layers, and an output layer. The input parameters include corrected drill cuttings gas desorption indices, three-dimensional geological model parameters, stress field monitoring data, and borehole layout parameters. The output results are categorized into four levels: no outburst risk, outburst threat, outburst risk, and severe outburst risk. The evaluation cycle is synchronized with the drilling progress, enabling accurate prediction of the entire coal seam exposure process.

[0073] Compared with the prior art, the present invention has significant advantages and beneficial effects. As can be seen from the above technical solution, in order to achieve the aforementioned objectives, the main technical contents of the present invention are as follows:

[0074] This invention proposes a construction method for measuring drill cuttings indicators in wet drilling operations in mines. By using a composite drilling process of "wet pressure-reduced slag removal", airflow screening technology, closed-loop fixed-point coring device, dry and wet coal sample indicator correction system, and dynamic evaluation method of multi-source data fusion, it solves the technical problem that traditional wet drilling cannot accurately measure the gas desorption index of drill cuttings. It achieves accurate prediction of coal and gas outburst risk while maintaining the dust reduction advantages of wet drilling.

[0075] As can be seen from the above, this invention innovatively proposes an accurate method for measuring the gas desorption index of drill cuttings under compressed air discharge conditions for coal uncovering faces in vertical shafts. It establishes a complete technical system from coal sample collection and index measurement to hazard assessment, and realizes the synergistic optimization of coal uncovering construction safety and dust control.

[0076] By employing the above technical solution, the method for measuring drill cuttings index in wet drilling operations of the present invention has at least the following advantages:

[0077] The contradiction between wet drilling and the measurement of drill cuttings index has been resolved: by switching between "compressed air purging + compressed air slag removal", the dust reduction effect of wet drilling is maintained, while the low moisture content requirement for the measurement of drill cuttings index is met, thus achieving a balance between safety and measurement.

[0078] A scientific index correction system was established: through laboratory research, the mapping relationship and graded correction coefficient of gas desorption index of dry and wet coal samples were established, so that the measurement results of wet coal samples can be equivalently converted into dry coal sample indexes, thus ensuring the uniformity of evaluation standards.

[0079] The standardization and quantification of coal sample collection have been achieved: real-time sieving with compressed air slag discharge and double-layer sieve, combined with a closed-loop fixed-point core sampling device and timing control, ensures precise control of key parameters such as coal sample particle size and exposure time, and improves the reliability of the measurement results.

[0080] A multi-source data fusion intelligent prediction system was constructed: combining drill cuttings indicators, three-dimensional geological models, stress field monitoring data and LSTM neural networks, it achieved dynamic, accurate and full-process prediction of prominent hazards, significantly improving the safety level of coal seam uncovering construction.

[0081] A systematic three-level predictive borehole system has been formed: predictive boreholes are arranged in stages according to the vertical distance from the coal seam, and the final borehole control standard is tightened step by step, which not only ensures the comprehensiveness of the prediction, but also avoids over-drilling, resulting in significant economic benefits.

[0082] In summary, the unique method for measuring drill cuttings indicators in wet drilling operations of this invention effectively overcomes the dual shortcomings of existing technologies, namely, the inability to measure drill cuttings indicators in wet drilling and the significant dust hazards of dry drilling. It achieves safe, environmentally friendly, and accurate prediction of coal and gas outbursts. It possesses numerous advantages and practical value, and is truly innovative as no similar design has been publicly disclosed or used in similar methods. It represents a significant improvement in both method and function, a substantial technological advancement, and produces user-friendly and practical results. Compared to existing methods for measuring drill cuttings indicators in wet drilling operations, it offers several enhanced functions, making it more suitable for practical application and possessing broad industrial value. It is indeed a novel, progressive, and practical new design.

[0083] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, the preferred embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0084] The specific methods and structures of the present invention are given in detail in the following embodiments and accompanying drawings. Attached Figure Description

[0085] Figure 1 Comparison and correction diagram of gas desorption curves of dry and wet coal samples;

[0086] Figure 2 Flowchart of the construction method for measuring drill cuttings index in wet drilling operations in mining;

[0087] Figure 3 Schematic diagram of a closed-loop coring device;

[0088] In the picture:

[0089] 1. Outer cylinder, 2. Inner cylinder, 3. Sealed core sampling device, 4. Sealing device, 5. Core drill bit, 6. Positioning mechanism. Detailed Implementation

[0090] To further illustrate the technical means and effects adopted by the present invention to achieve the intended purpose, the following detailed description, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation method, method, steps, structure, features, and effects of the drilling cuttings index measurement construction method for wet drilling operations in mining based on the present invention.

[0091] Please see Figure 1 As shown in the preferred embodiment of the present invention, the method for measuring drill cuttings parameters in wet drilling operations in mining mainly includes the following steps:

[0092] S1: Wet drilling and hole cleaning

[0093] Wet drilling operations are conducted at the coal seam face of the vertical shaft, with borehole diameters ranging from 50mm to 75mm. Wet drilling is used in rock sections to reduce dust. After coal is encountered, the drill rod is withdrawn, and compressed air is used to blow away the mud in the hole. Drilling is then switched to compressed air slag removal until the roof or floor of the coal seam is reached. The compressed air slag removal uses compressed air or a gas-water mixture (gas-water volume ratio 8:2 to 9:1) as the slag removal medium, ensuring both slag removal efficiency and controlling the moisture content of the coal sample within the range of 8% to 15%, meeting the accuracy requirements for measuring the gas desorption index of drill cuttings. The compressed air parameters are controlled at 0.4MPa to 0.6MPa, and the purging time is no less than 30 seconds per meter of hole depth until the moisture content of the gas returning from the borehole is <5% or no obvious water mist is visually observed.

[0094] S2: Airflow sieving and coal sampling

[0095] After drilling into the coal seam, at a depth of 0.2m to 0.3m before the predetermined sampling depth, coal samples are screened using the impact force of compressed air slag discharge combined with a double-layer sampling screen at the borehole opening. The upper screen has a 3mm aperture, and the lower screen has a 1mm aperture. The airflow velocity is controlled at 8m / s to 15m / s (pure compressed air) or 3m / s to 6m / s (air-water mixture) to achieve rapid separation of coal samples with a particle size of 1mm to 3mm. The coal sample on the lower screen is collected, dehumidified for no more than 10 seconds, and then quickly transferred to a closed-loop fixed-point coring device.

[0096] S3: Measurement of gas desorption index

[0097] A closed-loop, fixed-point coring device was used to collect coal samples, and a timing device was simultaneously started to record the exposure time t0 of the coal samples. When measuring the K1 index, t0 ≤ 2 min was required; when measuring the Δh2 index, t0 = 3 min was required. The sieved coal samples were then loaded into a gas desorption analyzer, and the values ​​of the drill cuttings gas desorption index were determined according to the method specified in AQ / T 1065-2008.

[0098] S4: Index Correction and Equivalent Conversion

[0099] Based on pre-established correction coefficients for gas desorption indices in dry and wet coal samples, the measured index values ​​are corrected to equivalent dry coal sample index values. The correction coefficients are determined through laboratory comparative experiments, and a graded correction system is established considering factors such as coal seam gas pressure, coal quality characteristics, and moisture content.

[0100] S5: Dynamic Evaluation and Security Management

[0101] Based on the corrected gas desorption index value of drill cuttings, combined with the three-dimensional geological model and stress field monitoring data, the LSTM neural network algorithm is used to conduct dynamic evaluation of the outburst risk, so as to realize accurate prediction and safety control of the entire process of coal uncovering project.

[0102] Example 1:

[0103] Taking the coal uncovering project of the vertical shaft of the Beishan Central Coal Mine of Kailuan Kuche High-tech Energy Co., Ltd. as an example, the specific implementation process of the present invention is explained.

[0104] The mine has a cluster of closely spaced coal seams, and the main shaft needs to penetrate multiple outburst-prone coal seams with a spacing of 2m to 8m and a coal seam gas pressure of 1.2MPa to 2.5MPa, posing a serious risk of outbursts.

[0105] 3D geological model construction:

[0106] A high-precision 3D geological model was established using the Petrel platform, integrating geological exploration, logging, and well inspection data. The model shows a target coal seam thickness of 2.3m, a dip angle of 12°, and a distance of 5.6m from the centerline of the wellbore. A small fault with a 3m drop exists above it. Model accuracy verification shows the actual exposed coal seam thickness is 2.1m, with an error of 0.2m, meeting engineering requirements.

[0107] First round of predictive drilling:

[0108] When the working face has advanced to a depth of 5.6m from the normal of the coal seam, three predictive boreholes are set up in the first round:

[0109] Hole No. 1: Located in the middle of the working face, slightly upward along the shaft axis (elevation angle 5°), with a depth of 6.2m;

[0110] Hole No. 2: Located at the upper left corner of the working face, with an azimuth of -15°, an elevation of 8°, a hole depth of 6.5m, and the final hole point is located 5.2m above the outline and 3.2m to the left.

[0111] Hole No. 3: Located at the upper right corner of the working face, with an azimuth of +15°, an elevation of 8°, a hole depth of 6.5m, and the final hole point is located 5.1m above the outline and 3.1m to the right.

[0112] The borehole was drilled using a φ75mm PDC drill bit with wet drilling. The drill rod was withdrawn 0.3m before entering the coal seam, and the borehole was purged with 0.5MPa compressed air for 3 minutes. The drilling was then switched to compressed air slag removal mode (air-water ratio 85:15) to drill into the coal seam.

[0113] Coal sample collection and analysis:

[0114] Sampling was performed at a depth of 5.8m (middle of the coal seam). The samples were sieved using an airflow sieve at the orifice to obtain approximately 15g of coal samples with a diameter of 1mm to 3mm and a measured moisture content of 11%. A closed-loop fixed-point coring device was used, and the time from sample collection to sealing was 45 seconds (t0=0.75min). The K1 value was determined using an isochoric gas desorption instrument.

[0115] Coal sample test results: K1(measured) = 0.42 cm³ / (g·min¹ / ²).

[0116] Indicator Correction:

[0117] Based on the correction factors established in the laboratory (for this coal seam, P=1.5MPa, f=0.6, w=11%, and Kcorrection1=1.35 from the table), the equivalent dry coal sample parameters are calculated as follows:

[0118] K1(dry) = 0.42 × 1.35 = 0.57 cm³ / (g·min¹ / ²)

[0119] Based on the critical value of 0.5 cm³ / (g·min¹ / ²), the hole was determined to be at risk of protrusion.

[0120] Anti-surgical measures and effectiveness verification:

[0121] A pre-gas extraction measure involving drilling through layers was adopted, with a borehole spacing of 1.5m × 1.5m. The effectiveness was verified after 45 days of extraction. The verification borehole was located in the middle of the control boreholes, and the same compressed air slag removal measurement method was used. The measured value K1 was 0.28 cm³ / (g·min¹ / ²), and after correction, K1(dry) was 0.38 cm³ / (g·min¹ / ²) < 0.5, indicating the measure was effective.

[0122] Multi-round forecasting and dynamic early warning:

[0123] The first round of predictions indicated a risk of outburst at borehole No. 1, which proved effective after implementing anti-outburst measures. The second round of predictions (3.2m from the coal seam) showed no outburst risk at any of the three boreholes. The third round of predictions (1.8m from the coal seam) also showed no outburst risk at any of the three boreholes. Stress monitoring data throughout the process showed that the coal seam stress decreased from 12.5MPa to 8.3MPa, consistent with the trend of drill cuttings indices, verifying the effectiveness of the early warning system.

[0124] Example 2:

[0125] A comparative experiment of dry and wet coal samples was conducted in the laboratory of North China University of Technology to determine the correction coefficient.

[0126] Coal sample preparation:

[0127] Take raw coal samples from the target coal seam, crush and screen them to obtain particles with a diameter of 1mm to 3mm, and divide them into three groups:

[0128] Dry coal samples: air-dried until moisture content <3%;

[0129] Wet coal sample (simulating wet drilling): add water to a moisture content of 25%;

[0130] Compressed air slag coal sample (simulating this invention): add water to a moisture content of 12%, then purge with compressed air (0.5MPa) for 30 seconds to control the moisture content to 8% to 15%.

[0131] Gas adsorption equilibrium:

[0132] The three coal samples were placed into coal sample containers, degassed, and then filled with methane (concentration 99.9%). The samples were then subjected to adsorption equilibrium at a pressure of 1.5 MPa for 24 hours.

[0133] Desorption index determination:

[0134] According to the method specified in AQ / T 1065-2008, the K1 and Δh2 indices were measured respectively:

[0135] Table 1. Results of gas desorption index determination in coal samples with different moisture contents.

[0136] Coal sample type Moisture content (%) <![CDATA[K1(cm³ / (g·min¹ / ²))]]> <![CDATA[Δh2(Pa)]]> dry coal sample <3 0.65 180 Compressed gas discharge coal sample 8～15 0.48 135 wet coal sample 25 0.32 95

[0137] Correction factor calculation:

[0138] Under compressed air slag discharge conditions (in this invention): K Correction 1 = 0.65 / 0.48 = 1.35 K Correction 2 = 180 / 135 = 1.33

[0139] Multi-pressure point calibration:

[0140] The experiment was repeated at adsorption pressures of 1.0 MPa, 1.5 MPa, 2.0 MPa, and 2.5 MPa to establish the functional relationship between the correction factor and the gas pressure.

[0141] Table 2 Recommended values ​​of correction factors under different gas pressures

[0142] Gas pressure P (MPa) Strength factor f Moisture content w (%) <![CDATA[K correction 1]]> <![CDATA[K correction 2]]> <1.0 <0.5 >15 1.30 1.25 <1.0 0.5-0.8 8-15 1.25 1.20 1.0-2.0 <0.5 >15 1.45 1.40 1.0-2.0 0.5-0.8 8-15 1.35 1.33 ≥2.0 <0.5 >15 1.60 1.55 ≥2.0 >0.8 <8 1.45 1.40

[0143] Note: When f < 0.5, the upper limit is taken; when f > 0.8, the lower limit is taken; when w > 15%, K correction increases by 0.05 to 0.10; when w < 8%, K correction decreases by 0.05 to 0.10.

[0144] Example 3: Application of Intelligent Control System

[0145] Establish an intelligent management and control system for the entire lifecycle of coal uncovering operations in shafts to achieve multi-source data fusion.

[0146] System Architecture:

[0147] Data acquisition layer: stress sensor, gas sensor, drill cuttings index analyzer, infrared thermal imager;

[0148] Data transmission layer: Industrial Ethernet + wireless transmission;

[0149] Data processing layer: 3D geological model, LSTM prediction algorithm, correction coefficient database;

[0150] Application presentation layer: 3D visualization, real-time early warning, construction progress management.

[0151] LSTM Neural Network Construction:

[0152] LSTM networks are built using the TensorFlow framework:

[0153] Input layer: 7 neurons (K1, Δh2, coal seam thickness, dip angle, stress value, gas pressure, vertical distance from coal seam)

[0154] Hidden layers: 2-layer LSTM, 64 units per layer, dropout rate 0.2

[0155] Output layer: 4 neurons (4 danger levels), Softmax activation

[0156] Optimizer: Adam, learning rate 0.001

[0157] Loss function: Weighted cross-entropy loss (with 3x weighting for highlighted cases)

[0158] Training data: Coal uncovering project data from 5 mines including Kailuan Group from 2015 to 2023, totaling 236 sets (78 sets of outstanding cases and 158 sets of no outstanding cases).

[0159] Training iterations: 200 epochs, test set accuracy: 92.3%

[0160] Dynamic early warning process:

[0161] (1) Real-time acquisition of drill cuttings index measurement data and automatic index correction;

[0162] (2) Integrate structural information from the three-dimensional geological model to identify dangerous areas such as faults and folds;

[0163] (3) Determine the degree of stress concentration by combining stress field monitoring data;

[0164] (4) The LSTM algorithm outputs a high level of danger, triggering a corresponding warning:

[0165] Green: No major hazards, normal construction;

[0166] Yellow: Highlight threats, strengthen monitoring;

[0167] Orange: Highlighting danger; take preventative measures.

[0168] Red: Serious danger looms. Stop work immediately and evacuate personnel.

[0169] Application effect:

[0170] After the system was applied in the Beishan Central Coal Mine, the coal uncovering period was shortened by 65%, no gas outburst accidents occurred, and the level of safety was improved by 200%.

[0171] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the methods and techniques disclosed above without departing from the scope of the present invention to create equivalent embodiments. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for measuring drill cuttings parameters in wet drilling operations for mining, characterized in that, Includes the following steps: Wet drilling operations are carried out at the coal uncovering face of the vertical shaft, with a borehole diameter of 50mm to 75mm. Wet drilling is used in rock sections. After drilling through coal, the drill rod is withdrawn, and compressed air is used to blow away the mud in the hole. Then, the compressed air slag removal method is switched to drilling until the top or bottom of the coal seam is reached. After the borehole enters the coal seam, at a depth of 0.2m to 0.3m before the predetermined sampling depth, the coal sample is screened using the impact force of the compressed air slag discharge flow and the orifice sampling sieve to obtain a coal sample with a particle size of 1mm to 3mm. A closed-loop fixed-point coring device was used to collect coal samples, and a timing device was started simultaneously to record the coal sample exposure time t0. When measuring the K1 index, t0 ≤ 2 min, and when measuring the Δh2 index, t0 = 3 min. The sieved coal sample was loaded into a gas desorption instrument to determine the value of the drill cuttings gas desorption index of the coal sample. Based on the pre-established correction coefficients for gas desorption indices in dry and wet coal samples, the measured index values ​​are corrected to equivalent dry coal sample index values. Based on the corrected gas desorption index value of drill cuttings, combined with a three-dimensional geological model, stress field monitoring data, and LSTM neural network algorithm, a dynamic assessment of prominent hazards is conducted.

2. The method according to claim 1, characterized in that, The compressed air slag removal method uses a gas-water mixture for slag removal, wherein the gas volume ratio is ≥80% and the liquid volume ratio is ≤20%; the coal sample screening is carried out by the impact force of the compressed air slag removal airflow or the impact force of the gas-water mixture slag removal medium, with the airflow velocity controlled at 8m / s~15m / s, or the medium flow velocity controlled at 3m / s~6m / s.

3. The method according to claim 1, characterized in that, The correction coefficients for the gas desorption index of the dry and wet coal samples were determined according to the following grading standards: When the coal seam gas pressure P < 1.0 MPa, K correction 1 = 1.20 ~ 1.30, K correction 2 = 1.15 ~ 1.25; When 1.0MPa≤P<2.0MPa, Kcorrection 1=1.30~1.45, Kcorrection 2=1.25~1.40; When P ≥ 2.0 MPa, K correction 1 = 1.45~1.60, K correction 2 = 1.40~1.55; The above coefficients are finely adjusted based on the coal quality characteristic firmness coefficient f and the coal sample moisture content w: the upper limit is taken when f < 0.5, and the lower limit is taken when f > 0.8; when w > 15%, K correction increases by 0.05 to 0.10, and when w < 8%, K correction decreases by 0.05 to 0.

10.

4. The method according to claim 1, characterized in that, The LSTM neural network consists of an input layer, two hidden layers, and an output layer. The input parameters include the corrected drill cuttings gas desorption index, three-dimensional geological model parameters, stress field monitoring data, and borehole layout parameters. The output results are categorized into four levels: no outburst hazard, outburst threat, outburst hazard, and severe outburst hazard.

5. The method according to claim 1, characterized in that, The drilling arrangement for the wet drilling operation includes: The first round of predictive drilling: When the working face is excavated to a distance of 5m to 6m from the normal of the coal seam, the number of drilling holes shall not be less than 3, and the final hole point shall be located 5m above the working face outline and 3m to the sides. Second round of predictive drilling: When the first round of prediction indicates no outburst risk, the drilling is arranged when the working face has been excavated to a distance of 3m to 4m from the normal of the coal seam. The final hole is located 3m above the working face outline and 2.5m to the sides. The third round of predictive drilling: When the second round of prediction indicates no outburst risk, the drilling will be arranged when the working face has been excavated to a distance of 1.5m to 2m from the normal of the coal seam. The final drilling point will be located 2m above the working face outline and 1.5m to the sides.

6. The method according to any one of claims 1-5, characterized in that, It also includes intelligent management and control measures: installing blowout preventers at the borehole openings of gas drainage boreholes, using automatic waterproof slag removal equipment, applying infrared thermal imaging technology to monitor gas drainage pipelines in real time, and establishing an intelligent management and control system for the entire cycle of coal uncovering construction in the shaft to achieve dynamic collaborative management and control of construction through the fusion of multi-source data.

7. A smart control system for coal seam exposure in vertical shafts of near-distance coal seams based on a drilling cuttings index measurement method using wet drilling operations in mines, characterized in that, include: Blowout prevention device at the orifice of gas extraction borehole, with a pressure bearing capacity of ≥2MPa; Automatic waterproof slag discharge equipment with a slag discharge capacity of ≥5m³ / h and a separation efficiency of ≥95%; The infrared thermal imaging monitoring module performs real-time temperature monitoring of the gas extraction pipeline with a temperature resolution of ≤0.1℃. The central control platform integrates data from the aforementioned devices to achieve intelligent control of the entire extraction system throughout its lifecycle, with an early warning response time of ≤10s.

8. The system according to claim 7, characterized in that, The central control platform includes: The data acquisition layer includes stress sensors, gas sensors, drill cuttings index measuring instruments, and infrared thermal imagers; The data transmission layer adopts a combination of industrial Ethernet and wireless transmission; The data processing layer includes a 3D geological model, an LSTM prediction algorithm, and a correction coefficient database. The application presentation layer includes 3D visualization, real-time early warning, and construction progress management.

9. The method according to claim 1, characterized in that, The closed-type fixed-point coring device includes: a coal sample cup with a volume of 8.6 cm³, a wall thickness of 1.5 mm to 3.0 mm, and made of 316L stainless steel or high-strength aluminum alloy; a coal sample container with a volume of 300 cm³, capable of withstanding a gas pressure of ≥6 MPa; and a quick-connect mechanism with a connection time controlled within 10 seconds.

10. The method according to claim 1, characterized in that, The three-dimensional geological model is established using the Petrel platform or similar geological modeling software, and the accuracy meets the following requirements: coal seam thickness error ≤ 0.3m, coal seam dip angle error ≤ 3°, and fault location error ≤ 5m; the stress field monitoring data is connected to the shaft coal uncovering construction safety management and control system via wired or wireless transmission.

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