Multi-scale geological prediction method for risky sections of shafts and tunnels based on space-well-hole combination

Abstract

The invention discloses a multi-scale geological prediction method for risky sections of shafts and tunnels based on air-well-hole combination, which relates to the technical field of multi-scale geological prediction for risky sections of shafts and tunnels. A pre-mining geological survey is conducted on the surface of the area where two parallel mine tunnels are located, and the risky geological sections are delineated in combination with geological disaster characteristics; an aero-electromagnetic detection is conducted on the surface above the risky geological sections corresponding to the two parallel tunnels, and whether the geological body between the two tunnels has a water-containing body or a water-conducting structure is judged according to the detection result; according to the judgment result, an oblique drilling is conducted from the risk-free tunnel to the geological body behind the mining face of the high-risk tunnel, and the drilling parameters in the drilling process are obtained, and the drilling slag is collected; based on the drilling slag, the lithology of the rock mass, the type of unfavorable geological body and the degree of abnormality in the geological body between the two tunnels are judged in combination with spectral technology; an acoustic wave test is conducted in the hole, and the integrity of the rock mass is judged in combination with the drilling parameters and the acoustic wave velocity value, so as to complete the multi-scale accurate geological prediction for the risky sections of shafts and tunnels.

Description

Technical Field

[0001] This invention relates to the field of multi-scale geological prediction technology for risky sections of mine tunnels, and in particular to a multi-scale geological prediction method for risky sections of mine tunnels based on a combination of air-well-hole technology. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] Coal, as a crucial pillar of the energy industry, has been widely mined due to the dramatic increase in energy demand driven by urban modernization. Because coal is a non-renewable resource, large-scale mining has led to a dwindling number of existing coal mines, with open-pit mines becoming increasingly rare. Therefore, it is imperative for mining projects to venture underground and even deeper. However, if the geological conditions of the geological formations are not properly assessed during coal mine operations, it will directly impact the safety of the project.

[0004] Existing geological exploration techniques mainly include geological analysis, geophysical electrical methods, and advanced drilling. However, geological analysis relies on qualitative judgment based on expert experience, which is prone to misjudgment and omission, and cannot reveal the internal structure of the geological body. Moreover, considering the complex and variable geological conditions of coal-bearing strata, such as faults, fissures, folds, and magma intrusions, which can alter the thickness and hardness of coal seams, even with thorough preliminary geological exploration, it is impossible to avoid disasters such as roadway collapses, sudden water inrushes, and large deformations of surrounding rock during coal mining. When a mine roadway experiences large-scale water inrushes or collapses, geological identification cannot be directly carried out in the affected roadway. The roadway is often equipped with ventilation ducts, construction machinery, and metal structures such as steel arches, making geophysical electrical methods susceptible to strong electromagnetic interference, resulting in low detection resolution and an inability to effectively identify the internal geological body. If advanced drilling or borehole geophysical exploration is used at the working face of the mine roadway, it can easily lead to borehole collapse, or even water inrush and flooding, causing equipment damage and threats to life. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a multi-scale geological prediction method for risky sections of mine tunnels based on a combined air-well-hole approach. Addressing geological identification scenarios ahead of the tunnel face, this method employs precise geological identification of geological bodies between adjacent accident-prone tunnels. It fully integrates technologies such as airborne electromagnetics, spectral analysis, drilling parameters, and acoustic testing to comprehensively and efficiently acquire the properties of geological bodies / rock masses between parallel tunnels. This enables detailed sketching of rock mass conditions between tunnels, eliminates geological blind spots during coal mine tunnel excavation, provides a geological basis for efficiently and accurately developing on-site construction plans, and ensures safe and rapid coal mining.

[0006] In the first aspect, the present invention provides a multi-scale geological prediction method for tunnel risk sections based on the combination of air-well-hole.

[0007] A multi-scale geological prediction method for tunnel risk sections based on a combined air-well-hole approach includes:

[0008] A pre-mining geological survey was conducted on the surface of the area where the two parallel mine roadways were located, and risk geological sections were delineated based on the characteristics of geological hazards; the two roadways were designated as risk-free roadways and high-risk roadways, respectively.

[0009] Airborne electromagnetic detection was conducted on the surface above the risk geological sections corresponding to the two parallel tunnels. Based on the detection results, it was determined whether the geological body between the two tunnels contained water-bearing bodies or water-conducting structures.

[0010] Based on the assessment results, an oblique borehole was drilled from the risk-free roadway to the geological body behind the mining face of the high-risk roadway, and the drilling parameters were obtained during the drilling process, and the drilling debris was collected.

[0011] Based on the drilling debris and combined with spectral technology, the lithology of the rock mass, the type of unfavorable geological body, and the degree of anomaly in the geological body between the two tunnels were determined.

[0012] Sonic testing is conducted inside the borehole, and the integrity of the rock mass is determined by combining drilling parameters and sonic velocity values, thus completing multi-scale geological prediction of risk sections in the tunnel.

[0013] In a second aspect, the present invention also provides an electronic device, including a memory and a processor, and computer instructions stored in the memory and running on the processor, wherein the computer instructions, when executed by the processor, perform the steps of the method described in the first aspect.

[0014] Thirdly, the present invention also provides a computer-readable storage medium for storing computer instructions, which, when executed by a processor, perform the steps of the method described in the first aspect.

[0015] The above one or more technical solutions have the following beneficial effects:

[0016] 1. This invention provides a multi-scale geological prediction method for risk sections in tunnels based on a combined air-well-borehole approach. Addressing the scenario of geological identification and prediction ahead of the tunnel face, it employs a method of accurately identifying geological bodies between adjacent accident-prone tunnels. During the identification process, it fully integrates technologies such as airborne electromagnetics, spectral analysis, drilling parameters, and acoustic testing. First, it detects and determines the risk section between the two tunnels and the characteristics of the geological bodies within that section. Then, based on the detection results, it performs directional drilling to collect drilling debris, thus solving the problem of borehole collapse or water inrush caused by directly using advanced drilling or in-hole geophysical exploration, ensuring drilling safety. Finally, based on the combined analysis of the spectral data of the drilling debris from the directional borehole, drilling parameters, and acoustic testing, it comprehensively and efficiently obtains the properties of the geological bodies / rock masses between parallel tunnels, solving the problem that traditional in-tunnel geophysical exploration is easily affected by external interference factors, leading to detection failures or low detection accuracy.

[0017] 2. This invention performs geological identification from three dimensions: air (i.e., the upper part of the ground), well (i.e., coal mine tunnels), and borehole (i.e., advanced drilling). It forms a set of three-dimensional geological identification results for mine tunnels from macroscopic to microscopic perspectives, realizes accurate sketching of the rock mass inside the risk section of the mine tunnel, eliminates geological blind spots in the process of coal mine tunnel excavation, effectively improves the accuracy of geological identification, provides a geological basis for the efficient and accurate formulation of on-site construction plans, and ensures the safe and rapid mining of coal mines.

[0018] 3. In this invention, the mineral types and corresponding contents contained in the rock mass can be quickly determined through spectral similarity identification and unmixing algorithms. This can improve identification efficiency while ensuring a certain level of accuracy, avoiding a large amount of preliminary work. Based on this, elemental information is obtained by spectral measurement, and the rock mass lithology is identified by combining elemental and mineral information. This can effectively identify the type and degree of anomaly of the adverse geological body. Through the multi-source information fusion identification of drilling parameters and acoustic data, the drawbacks of misjudgment and omission in rock integrity identification based on a single technology are avoided, realizing qualitative and quantitative identification of rock mass integrity. This invention achieves accurate prediction of rock mass mechanical and geochemical properties by performing geological identification between two parallel roadways from the accident-free roadway to the adjacent accident roadway.

[0019] 4. This invention strictly controls the risk level during implementation, with rigorous logic, ensuring that disasters such as water inrush and collapse in mine tunnels will not occur during implementation. It has strong on-site applicability, can effectively reduce the risk of coal mine tunnel excavation, and reduce disaster response costs. At the same time, this solution has strong universality and is also applicable to geological identification work in industries such as tunnel engineering and urban underground engineering. Attached Figure Description

[0020] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0021] Figure 1 This is a flowchart of the multi-scale geological prediction method for tunnel risk sections based on the combination of air-well-hole system, as described in an embodiment of the present invention.

[0022] Figure 2 This is a schematic diagram illustrating the multi-scale geological survey and prediction of risky geological sections in well tunnels using a combination of air-well-hole technology in an embodiment of the present invention. Detailed Implementation

[0023] It should be noted that the following detailed descriptions are exemplary and are intended only to describe specific embodiments and to provide further explanation of the invention, and are not intended to limit the scope of exemplary embodiments of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0024] This invention provides a multi-scale geological prediction method for risky sections of mine tunnels based on a combination of air-well-borehole technology. Risky geological sections are delineated through preliminary geological exploration and disaster characteristic analysis. Precise oblique drilling is performed on the tunnel walls based on airborne electromagnetic analysis results, and acoustic testing is conducted within the boreholes. By acquiring the elemental and mineral composition of the geological body / rock mass between two tunnels, and integrating borehole propulsion parameters and acoustic frequencies, the lithology, structure, water-bearing capacity, integrity, and adverse geological types of the rock mass between the two parallel tunnels are accurately predicted. This yields multi-scale geological prediction results for risky sections of the mine tunnels, thereby guiding safe construction in coal mine tunnels and developing corresponding disaster prevention and control plans.

[0025] Example 1

[0026] Considering that geological identification cannot be directly carried out in accident-affected roadways, this embodiment provides a multi-scale geological prediction method for risky roadway sections based on a combined open-well-hole approach. This method accurately identifies geological bodies between adjacent, accident-free roadways, resulting in more accurate and reliable identification. The specific details of this method are as follows: Figure 1 As shown, it includes:

[0027] Step S1: Conduct a pre-mining geological survey of the surface of the area where the two parallel mine roadways are located, and delineate the risk geological sections based on the characteristics of geological hazards; wherein, the two roadways are respectively a risk-free roadway and a high-risk roadway;

[0028] Step S2: Conduct airborne electromagnetic surveys on the surface above the risk geological sections corresponding to the two parallel tunnels, and determine whether the geological body between the two tunnels has a water-bearing body or water-conducting structure based on the survey results.

[0029] Step S3: Based on the judgment result, drill obliquely from the risk-free roadway to the geological body behind the mining face of the high-risk roadway, obtain the drilling parameters during the drilling process, and collect the drilling debris.

[0030] Step S4: Based on the drilling debris and combined with spectral technology, determine the lithology of the rock mass, the type of unfavorable geological body, and the degree of anomaly in the geological body between the two tunnels;

[0031] Step S5: Conduct acoustic testing inside the borehole, and combine drilling parameters and acoustic velocity values ​​to determine the integrity of the rock mass, thereby completing multi-scale geological prediction of risk sections in the tunnel.

[0032] The following content provides a more detailed introduction to the multi-scale geological prediction method for tunnel risk sections based on the combination of air-well-hole system proposed in this embodiment.

[0033] In step S1, a pre-mining geological survey is conducted on the surface of the area where the two parallel mine roadways are located, and risk geological sections are delineated based on the characteristics of geological hazards. The two roadways are a risk-free roadway and a high-risk roadway, respectively. The high-risk roadway is the roadway where a water inrush accident has occurred during the excavation process, and the risk-free roadway is the roadway where no accident has occurred during the excavation process.

[0034] Specifically, a geological survey is conducted on the surface of the area where the two parallel mine roadways are located before coal mining. Based on the geological survey results and the characteristics of geological hazards that occurred during previous mining operations (these characteristics are known), risk geological sections are delineated. This provides a geological basis for the subsequent development of a plan based on advanced drilling, which involves diagonally drilling from risk-free roadways to high-risk roadways. The geological survey includes obtaining information on the surface topography along the roadway, historical geological processes, and roadway depth. The geological hazard characteristics refer to the geological features of the already mined sections of the roadway where hazards have occurred, including faults, fissures, and folds.

[0035] In this embodiment, two tunnels are excavated and tunneled in parallel towards the mining face. The mining face has a lateral width of 6m, a center-to-center distance of 30m, and a burial depth of 72m. Geological mapping and other exploration methods are used to investigate the surface corresponding to the two tunnels. Figure 2 As shown, based on the survey results, it was determined that there is a fault on the surface at the location of mileage 1+300~1+330 directly opposite the left-line tunnel, which is a typical geological hazard feature, and this section of the tunnel was determined to be a high-risk geological section.

[0036] In step S2, airborne electromagnetic detection is carried out on the surface above the risk geological sections corresponding to the two parallel tunnels. Based on the detection results, it is determined whether the geological body between the two tunnels has a water-bearing body or a water-conducting structure.

[0037] Traditional tunnel geological analysis primarily relies on drilling holes or conducting geophysical tests within the tunnel to reveal the geological conditions ahead. This method has a limited geological sensing range and strong data limitations, failing to provide a macroscopic understanding of the geological conditions along the coal mine tunnels. It is particularly unsuitable for the scenario described in this embodiment. Furthermore, the presence of metal ventilation ducts and electrical conduits on both sides of the tunnels makes geophysical methods highly susceptible to interference, leading to detection failures and an inability to clearly define the geological conditions between the two tunnels. In contrast, the method proposed in this embodiment allows for macroscopic detection of the geological conditions between the two tunnels from above the surface, thus aiding in better decisions regarding geological treatment and demonstrating a significant improvement over traditional tunnel testing.

[0038] Specifically, airborne electromagnetic surveys are conducted on the surface above the risky geological section encountered by the two parallel tunnels. This airborne electromagnetic survey refers to unmanned aerial vehicle (UAV) electromagnetic surveys conducted within a designated area above the surface above the risky geological section. The airborne electromagnetic properties map of this designated area is obtained through the airborne electromagnetic survey. Subsequently, anomaly area analysis is performed based on the airborne electromagnetic properties map to determine whether there are water-bearing bodies or water-conducting channels in the geological bodies or rock masses between the two parallel tunnels. This effectively avoids the disadvantage of electromagnetic interference when conducting geophysical exploration within the tunnels.

[0039] The aforementioned airborne electromagnetic mapping refers to airborne apparent resistivity (ps)-lithological structure mapping. It uses inversion or plate conversion techniques to convert measured airborne electromagnetic fields into ps values ​​reflecting underground geological bodies. Based on the differences and distribution trends of the ps values ​​of the geological bodies, lithological structure mapping is performed. In this embodiment, based on the ps values ​​of the geological bodies reflected in the airborne electromagnetic mapping, combined with preset ps values ​​for different geological bodies (including ps values ​​of aquifers and water-conducting channels), anomaly area analysis is performed to determine whether there are aquifers or water-conducting channels between two parallel tunnels.

[0040] In this embodiment, the test equipment is mounted on a drone. After takeoff, it maintains a certain distance from the ground and the detection signal covers the surface area of ​​the left-line tunnel from 1+290 to 1+340 (i.e., the risk geological section area). The detection reaches a depth of 80m below the surface. By analyzing the electrical mapping obtained from the detection, it is determined that there are no water-bearing bodies or water-conducting structures in the geological body between the two parallel tunnels.

[0041] In step S3, based on the judgment result, an oblique borehole is drilled from the risk-free roadway to the geological body behind the mining face of the high-risk roadway, and the drilling parameters during the drilling process are obtained and the drilling debris is collected.

[0042] Specifically, based on the airborne electromagnetic identification results obtained in step S2 above, oblique resting boreholes are drilled. If it is determined that there is no water-bearing body or water-conducting structure, oblique fine drilling is carried out from the risk-free roadway to the geological body behind the mining face of the high-risk roadway; conversely, if it is determined that there is a water-bearing body or water-conducting structure, the drilling angle and process are adjusted to avoid sudden water inrush, and then oblique fine drilling is carried out from the risk-free roadway to the geological body behind the mining face of the high-risk roadway.

[0043] Furthermore, the aforementioned oblique fine drilling from the risk-free roadway to the geological body behind the mining face of the high-risk roadway refers to drilling ahead of the high-risk roadway from the non-risk section area of ​​the risk-free roadway at a certain angle towards the already excavated direction of the high-risk roadway.

[0044] In addition, drilling parameters are collected and drilling cuttings are gathered during the drilling process. In this embodiment, the drilling parameters include drilling thrust parameters (i.e., propulsion force parameters), which are obtained by a pressure sensor installed at the end of the drill pipe during the drilling process.

[0045] In this embodiment, based on step S2 above, it has been determined through airborne electromagnetic results that there are no water-bearing bodies or water-conducting structures between the two tunnels. Based on this, as follows... Figure 2 As shown, at point 1+335 in the risk-free tunnel, drilling is carried out at an angle of 30° to the tunnel wall towards 1+290, with a drilling depth of 30m. This process is repeated four times to form a multi-hole joint identification.

[0046] In step S4, based on the drilling debris and combined with spectral technology, the lithology of the rock mass, the type of unfavorable geological body, and the degree of anomaly in the geological body between the two tunnels are determined.

[0047] Specifically, firstly, the drilling cuttings generated during drilling in step S3 are collected according to the order of their ejection. This means collecting the cuttings sequentially based on their ejection order and assigning them serial numbers, with the serial numbers indicating increasing depths. Then, based on the drilling cuttings collected during drilling, elemental and mineral analysis is performed using spectroscopic techniques to obtain the types and contents of elements and minerals in the rock mass between the two tunnels, thereby determining the lithology of the rock mass, the type of adverse geological body, and the degree of anomaly. Specifically, the use of spectroscopic techniques to obtain elemental and mineral information of the rock mass includes: using laser Raman spectroscopy, visible-near-infrared spectroscopy, and thermal infrared spectroscopy to obtain mineral information, including mineral types (i.e., composition) and contents; and using laser-induced breakdown spectroscopy and X-ray fluorescence spectroscopy to obtain elemental information, including element types (i.e., composition) and contents.

[0048] Considering that traditional techniques such as X-ray diffraction and microscopic thin section analysis are inefficient and damaging to the rock mass when measuring rock and mineral information, this embodiment adopts a method based on spectral data inversion, which can achieve rapid, in-situ, and non-destructive acquisition of rock and mineral information.

[0049] Specifically, in the above process, before using various rock slag spectral data for mineral composition inversion, the spectral data is preprocessed to improve data quality and ensure the accuracy of subsequent inversion results. In this embodiment, considering that the envelope acts as a shell enclosing the spectral data curve, removing this shell can deepen weak absorption characteristics, thereby enhancing the absorption features. Therefore, the acquired spectral data is first preprocessed by envelope removal. For each spectral data, envelope removal can be achieved using the following formula:

[0050] ;

[0051] ;

[0052] In the above formula, Indicates the first j Wavelength of the band Indicates band j Spectral reflectance after removing the envelope; Indicates band j The original spectral reflectance; and These are the original spectral reflectances at the beginning and end of the spectral curve, respectively; and These are the wavelengths at the beginning and end of the spectral curve, respectively.

[0053] Secondly, using the preprocessed spectral data as mixed spectral data, a spectral matching algorithm (i.e. SAM The algorithm identifies the mineral types contained in mixed spectral data. Specifically, it uses preprocessed spectral data (i.e., spectral reflectance) as mixed spectral data. It calculates the similarity between the mixed spectral data and the spectral data of each known end-member mineral (such as quartz, feldspar, mica, etc.), and identifies the mineral composition based on the similarity. The similarity calculation can be expressed as:

[0054] ;

[0055] In the above formula, This represents the angle between two spectral data points, i.e., the similarity between the two spectra; and These represent the mixed spectral data to be identified and the reference spectral data, respectively. The reference spectral data is the spectral data of a known end-member mineral, and the end-member spectral data can be obtained from existing public databases.

[0056] Furthermore, based on the similarity between the calculated mixed spectral data to be identified and each reference spectral data, the similarity is compared with a set threshold to determine whether the known mineral type is present. Specifically, if the similarity is greater than the set threshold, the corresponding known mineral type is considered to be present; otherwise, it is not.

[0057] Finally, based on the identified mineral types, a demixing algorithm is used to quantitatively identify the content of each mineral component. Specifically, the quantitative relationship between the mixed spectral data and the spectral data of the identified multiple minerals can be expressed as:

[0058] ;

[0059] in, For the first i The abundance of a mineral component in a mixture, i.e., the mineral content; This refers to the reference spectral data, i.e., the identified first... i Spectral reflectance of minerals; Indicates mixed spectral reflectance, Indicates the error value. n This indicates the number of mineral species identified.

[0060] Furthermore, the mixed spectral data and the spectral data of the identified end-member minerals are input into the above formula for solving to obtain the abundance value of each end-member mineral, that is, the content of each type of mineral identified. Through this similarity identification and demixing algorithm, the types of minerals contained and their corresponding contents can be quickly determined. While ensuring a certain level of accuracy, it can improve identification efficiency by directly calculating the results, avoiding a large amount of preliminary work.

[0061] As another implementation method, the types and contents of elements can be directly determined using existing equipment via laser-induced breakdown spectroscopy and X-ray fluorescence spectroscopy.

[0062] Furthermore, based on the obtained element and mineral contents and the mutual corroboration between them, the lithology of the rock mass is identified, and based on the abnormality of the types and contents of elements and minerals, the type and degree of abnormality of the adverse geological body are identified.

[0063] Specifically, identifying lithology through the types and amounts of elements and minerals, and the corroborating relationship between them, means that the lithology of each type of rock contains a relatively fixed range of element and mineral types and amounts. Elements are the most basic building blocks of rocks, while minerals are the most direct units of measurement for describing lithology. The amounts and types of elements and minerals are also closely related; for example, when the chlorite content in a rock increases, the Fe element content will also increase accordingly. Therefore, the lithology of a rock mass can be identified based on the types and amounts of elements and minerals.

[0064] Identifying the type and degree of anomalies in adverse geological bodies by observing anomalies in the types and contents of elements and minerals refers to the anomalies in the types and contents of elements and minerals that occur when tunnels are excavated into areas affected by adverse geological conditions such as faults. Different types of adverse geological conditions will exhibit corresponding anomalies; for example, when passing through granite faults, there will be enrichment in Fe and Mg, as well as chlorite and serpentine; when passing through weathered layers, there will be enrichment in Al and kaolinite, etc. Therefore, the type and degree of anomalies in adverse geological bodies can be identified based on the anomalies in the types and contents of elements and minerals.

[0065] In this embodiment, the drilling depth of 30m was spaced 1m apart, with 30 bags of samples collected from each borehole, totaling 120 bags from the four boreholes. Visible-near-infrared spectroscopy and thermal infrared spectroscopy were used for testing. Quartz, feldspar, mica, and kaolinite minerals were found between 15 and 18m drilling depths, while the mineral assemblage before 15m and after 18m consisted entirely of quartz, feldspar, and mica, indicating a mineral anomaly in this area. Similarly, X-ray fluorescence spectroscopy revealed Al enrichment in this area, further confirming the mineral anomaly.

[0066] Furthermore, elemental and mineral testing of the drill cuttings revealed that the elemental composition and content range of the rock in the normal section were: Si: 65%~80%, Na: 0~10%, K: 10%~20%, Al: 20%~30%; and the mineral composition and content range were: quartz: 20%~60%, feldspar: 40~80%, mica: 5%~10%. Through the synergistic identification of elements and minerals, the lithology of this stratum was determined to be granite. Within the drilling depth range of 15~18m, the content of Al and kaolinite increased, and the unfavorable geological type was determined to be a fault, with a moderate degree of anomaly.

[0067] In step S5, acoustic testing is conducted inside the borehole. The integrity of the rock mass is determined by combining drilling parameters and acoustic velocity values, thus completing multi-scale geological prediction of risk sections in the tunnel.

[0068] Specifically, after the drilling debris collection is completed, an acoustic wave test is conducted inside the borehole to obtain the acoustic wave velocity values ​​at different depths. This acoustic wave test involves using a transmitter and two receivers. The relevant cables for the transmitter and receivers are threaded through a metal or PVC pipe and inserted deep into the drilled borehole. The transmitter and receiver bodies are positioned outside the borehole. The transmitter emits acoustic waves, which are received by the receivers. The acoustic wave velocity value (referred to as wave velocity) is determined by dividing the distance between the two receivers by the signal reception time difference. During the test, the transmitter, receivers, and related cables are slowly and uniformly pulled out, and the change in acoustic wave velocity value is recorded as the depth of the receiver probe gradually decreases.

[0069] Based on the above tests, and considering the correlation between sound wave propagation speed and rock integrity, this embodiment determines the degree of rock fragmentation at different mileages based on changes in sound wave velocity, and identifies the integrity of the rock mass by combining drilling thrust parameters and sound wave velocity values.

[0070] Among them, the degree of rock fragmentation at different mileages is determined based on the change of sound wave velocity. That is, after obtaining the sound wave velocity value at different depths through sound wave testing, it is determined that the rock mass is fragmented if the sound wave velocity value is in the range of 1000~2000, relatively fragmented if it is in the range of 2000~3000, and intact if it is above 3000.

[0071] Furthermore, the integrity of the rock mass is determined by integrating drilling thrust parameters (i.e., propulsion force parameters) and acoustic wave velocity values. This includes extracting the range of abnormal changes in continuous data such as propulsion force parameters and acoustic wave velocity values ​​through data exploration technology (EDA) or mean-standard deviation methods, and conducting surrounding rock integrity assessment.

[0072] Specifically, the fluctuation curve of the thrust parameters with respect to time is obtained, the abrupt change point of the thrust parameters is determined by the stationary point analysis method, the abrupt change characteristics of the thrust parameters are obtained based on the abrupt change points, and the integrity of the rock mass is determined by the abrupt change characteristics and the change of acoustic wave velocity.

[0073] Among them, the abrupt change points of the propulsion parameters are determined using the stagnation point analysis method, including:

[0074] First, regarding the fluctuation curve of the thrust parameter with respect to time... Calculate the first difference of the fluctuation curve: ,in, Indicates the thrust parameter at t Let the continuous difference at point be Preliminary determination of the deployment location;

[0075] Next, calculate the second difference of the fluctuation curve: ,in, Indicates the thrust parameter at t Let the continuous difference of the continuous difference be... The final stationary point is found and determined among the initially identified stationary points, and the final identified stationary point (i.e., the maximum and minimum value) is taken as the mutation point.

[0076] Furthermore, based on the determined abrupt change point, the abnormal change characteristic range is divided. That is, the abrupt change point and the set scale range before and after it are divided into the abnormal change characteristic range. Then, based on the thrust parameter and acoustic velocity value at the current measuring point location, combined with the abnormal change characteristic range and the acoustic velocity range, the integrity of the rock mass at the current measuring point location is jointly determined. For example, when the current measuring point location is within the abnormal change characteristic range, and the acoustic velocity value is within the acoustic velocity range corresponding to broken or relatively broken rock mass, the rock is determined to be incomplete; otherwise, the rock is determined to be intact. In this embodiment, it was found that the acoustic velocity value within the range of 15-18m in the borehole was all within 1000-2000, and the thrust parameter also dropped sharply in this area (i.e., within the abnormal change characteristic range). At this time, the rock in this area was determined to be incomplete.

[0077] By using the multi-source information fusion identification based on drilling parameters (i.e. thrust parameters) and acoustic data, the drawbacks of misjudgment and omission in rock integrity identification by a single technology can be eliminated, and qualitative and quantitative identification of integrity can be achieved.

[0078] As another implementation method, step S6 involves combining the analysis results of steps S2 to S5 above to predict the rock mechanics and geochemical properties between the two parallel tunnels, including: lithology, water-conducting structures, water-bearing bodies, integrity, and adverse geological types. Based on this, corresponding disaster prevention and control measures or plans are taken.

[0079] In this embodiment, through the above steps, it is found that the strata of the high-risk roadway risk area are granite, without water-bearing bodies or water-conducting structures, with poor integrity and unfavorable geology as faults. Based on this, steel arch support can be adopted before continuing to mine forward. Conversely, if it is predicted that the high-risk roadway risk area is not risky, mining can continue directly forward, thereby achieving safe mining of coal mine roadways.

[0080] Example 2

[0081] This embodiment provides an electronic device, including a memory and a processor, as well as computer instructions stored in the memory and running on the processor. When the processor executes the computer instructions, it completes the steps in the multi-scale geological prediction method for tunnel risk segments based on the air-well-hole combination as described above.

[0082] Example 3

[0083] This embodiment also provides a computer-readable storage medium for storing computer instructions, which, when executed by a processor, complete the steps in the multi-scale geological prediction method for tunnel risk segments based on the air-well-hole combination described above.

[0084] The steps and methods involved in Embodiments 2 and 3 above correspond to those in Embodiment 1. For specific implementation details, please refer to the relevant description section of Embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood as including any medium capable of storing, encoding, or carrying an instruction set for execution by a processor and enabling the processor to perform any of the methods in this invention.

[0085] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computer devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computer device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. The present invention is not limited to any particular combination of hardware and software.

[0086] The above description is only a preferred embodiment of the present invention. Although the specific implementation of the present invention has been described in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that, based on the technical solution of the present invention, various modifications or variations that can be made by those skilled in the art without creative effort are still within the scope of protection of the present invention.

Claims

1. A multi-scale geological prediction method for risk sections of wells and tunnels based on space-well-hole combination, characterized in that: include: Conduct a pre-mining geological survey on the surface of the area where the two parallel mine tunnels are located, and delineate the risky geological sections based on the characteristics of geological hazards; the two tunnels are respectively a risk-free tunnel and a high-risk tunnel; Conduct airborne electromagnetic detection on the surface above the risky geological sections of the two parallel tunnels, and determine whether the geological body between the two tunnels has water-bearing bodies or water-conducting structures based on the detection results; According to the judgment results, oblique drilling is carried out from the risk-free tunnel to the geological body behind the mining face of the high-risk tunnel, and the drilling parameters during the drilling process are obtained and the drilling slag is collected; Based on the drilling slag, combined with spectral technology, the rock properties, unfavorable geological body types and abnormality degree in the geological body between the two tunnels are judged; wherein, the drilling slag generated during the drilling process is collected according to the flushing order, including: collecting the drilling slag according to the flushing order is to collect and mark the sequence number according to the sequence of the slag flushing out, and the slag sequence number from small to large indicates that the depth taken is gradually increasing; Based on the drilling slag collected during the drilling process, combined with spectral technology, the types and contents of elements and minerals in the rock mass between the two tunnels are obtained, and then the rock properties, the type of unfavorable geological body and the degree of abnormality of the rock mass are determined; wherein, the spectral technology is used to measure the element and mineral information of the rock mass, including: using laser Raman spectroscopy, visible light-near infrared spectroscopy, and thermal infrared spectroscopy to measure mineral information, the mineral information includes mineral types and contents; using laser induced breakdown spectroscopy and X-ray fluorescence spectroscopy to measure element information, the element information includes element types and contents; Among them, the use of spectral data to measure mineral information includes: Perform envelope removal preprocessing on the acquired spectral data; The pre-processed spectral data is used as mixed spectral data, and the spectral matching algorithm is used to identify the mineral types contained in the mixed spectral data, which is: the similarity between the mixed spectral data and the spectral data of each known end-member mineral is calculated, and according to the comparison result of the similarity with the set threshold, whether the known mineral type or composition is present, and the contained mineral type is identified; Based on the identified mineral types, a quantitative relationship between the mixed spectral data and the spectral data of the identified multiple minerals is constructed, and the content of each mineral is quantitatively identified using an unmixing algorithm; the quantitative relationship is: ； in, For the i The abundance of a mineral component in a mixture, i.e., the mineral content; Indicates the identification i Spectral reflectance of minerals; represents the mixed spectral reflectance, represents the error value, n Indicates the number of mineral species identified; Conduct sonic testing in the hole, combine drilling parameters and sonic wave velocity values ​​to identify the integrity of the rock mass, and complete multi-scale geological prediction of risk sections in the wells and tunnels; The drilling parameters include drilling thrust parameters, which are obtained by a pressure sensor installed at the end of the drill rod during the drilling process; Perform sonic wave testing in the hole to obtain sonic wave velocity values ​​at different depths in the hole. According to the change of sonic wave velocity values, the degree of rock fragmentation at different distances can be determined. The integrity of the rock mass can be determined by combining the drilling thrust parameters and sonic wave velocity values, including: Acquire the acoustic wave velocity values ​​at different depths through acoustic wave testing, and determine the degree of rock mass fragmentation according to the acoustic wave velocity range in which the acoustic wave velocity values ​​are located; Obtain the fluctuation curve of the drilling thrust parameter with respect to time, use the stationary point analysis method to determine the mutation point of the drilling thrust parameter, and divide the abnormal change characteristic range based on the mutation point; The integrity of the rock mass is determined based on the drilling thrust parameters and sonic wave velocity values ​​at the current measuring point, combined with the abnormal change characteristic range and sonic wave velocity range.

2. The multi-scale geological prediction method for risk sections of wells and tunnels based on space-well-hole combination as claimed in claim 1, characterized in that: Based on the geological survey results and the known geological hazard characteristics, the risk geological sections corresponding to the tunnels are delineated; The geological survey includes obtaining information on the surface topography along the tunnel, historical geological actions, and tunnel burial depth; The geological disaster characteristics are the geological characteristics of the disaster section in the mined part of the tunnel, and the geological disaster characteristics include faults.

3. The multi-scale geological prediction method for risk sections of wells and tunnels based on space-well-hole combination as claimed in claim 1, characterized in that: The high-risk tunnel is a tunnel where a water inrush accident occurred during the excavation process; the risk-free tunnel is a tunnel where no accident occurred during the excavation process.

4. The multi-scale geological prediction method for risk sections of wells and tunnels based on space-well-hole combination as claimed in claim 1, characterized in that: The aero-electromagnetic detection is to conduct UAV-type electromagnetic detection within a set area above the surface of the risk geological section, and obtain the aero-electromagnetic electrical mapping within the set area through the aero-electromagnetic detection; Based on the aero-electromagnetic mapping, the abnormal area analysis is carried out to determine whether the geological body between the two parallel tunnels has water-bearing bodies or water-conducting structures.

5. The multi-scale geological prediction method for risk sections of wells and tunnels based on space-well-hole combination as claimed in claim 1, characterized in that: If it is determined that there is no water-bearing body or water-conducting structure, oblique drilling is carried out from the non-risk tunnel to the geological body behind the mining face of the high-risk tunnel; On the contrary, if it is determined that there is a water-bearing body or water-conducting structure, the drilling angle and process are adjusted, and then oblique drilling is carried out from the non-risk tunnel to the geological body behind the mining face of the high-risk tunnel; Among them, oblique drilling refers to advanced drilling from the non-risk geological section area of ​​the risk-free tunnel to the excavated direction of the high-risk tunnel at a set inclination angle.

6. An electronic device, characterized in that: The method comprises a memory and a processor and computer instructions stored in the memory and executed on the processor. When the computer instructions are executed by the processor, the steps of a multi-scale geological prediction method for well and tunnel risk sections based on space-well-hole combination as described in any one of claims 1 to 5 are completed.

7. A computer-readable storage medium, characterized in that: Used to store computer instructions, which, when executed by a processor, complete the steps of a multi-scale geological prediction method for well and tunnel risk sections based on space-well-hole combination as described in any one of claims 1-5.

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