WO2024083262A1 - 天-空-地-隧-孔一体化不良地质识别方法及系统 - Google Patents

天-空-地-隧-孔一体化不良地质识别方法及系统 Download PDF

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WO2024083262A1
WO2024083262A1 PCT/CN2023/128811 CN2023128811W WO2024083262A1 WO 2024083262 A1 WO2024083262 A1 WO 2024083262A1 CN 2023128811 W CN2023128811 W CN 2023128811W WO 2024083262 A1 WO2024083262 A1 WO 2024083262A1
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tunnel
geological
information
site
spectral
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许振浩
李术才
林鹏
向航
刘福民
邵瑞琦
谢辉辉
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Shandong University
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/10—Terrestrial scenes
    • G06V20/17—Terrestrial scenes taken from planes or by drones
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three-dimensional [3D] modelling for computer graphics
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three-dimensional [3D] modelling for computer graphics
    • G06T17/05—Geographic models

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  • the present invention belongs to the technical field of tunnel exploration, and in particular relates to a sky-air-ground-tunnel-hole integrated adverse geological identification method and system.
  • Tunnel construction often encounters geological disasters such as sudden water and mud, landslides, and large deformations, causing heavy casualties, serious economic losses, and adverse social impacts.
  • Unfavorable geology such as faults and karsts are the biggest culprits and challenges for tunnel disasters.
  • Advanced geological prediction is the most direct and effective means to accurately explore unfavorable geology such as faults and karsts, and has become an indispensable part of tunnel survey and construction.
  • the advanced geological prediction in the tunnel is carried out, the properties and location information of the unfavorable geological bodies in front of the tunnel face can be identified and predicted from the tunnel and borehole scales, the unfavorable geological bodies can be identified more comprehensively, and at the same time, there will be a clearer understanding of whether geological disasters will occur after the tunnel excavation is exposed and the severity of the geological disasters.
  • the advanced horizontal drilling method can directly reveal the changes in rock mass quality and stratum information in front of the tunnel face through coring or intuitively perceive the changes in the drilling parameters through drilling parameters.
  • results of mineral analysis can be integrated into drilling and geophysical exploration, it can not only give play to the advantages of mineral analysis in identifying the types and properties of unfavorable geological bodies, but also give play to the advantages of drilling and geophysical exploration in identifying the locations, shapes and sizes of unfavorable geological bodies.
  • the inventors found that for the investigation of tunnels in complex mountainous areas, geological surveys of tunnel sites are conducted only based on a single data source, and the identification of adverse geological bodies in the tunnel is not comprehensive enough.
  • Different investigation methods have their own limitations, and there is an unclear understanding of whether geological disasters will occur after tunnel excavation and the severity of the geological disasters, making it difficult to provide effective reference for advanced geological forecasting of tunnels.
  • the present invention provides a sky-air-ground-tunnel-hole integrated adverse geological identification method and system, which innovatively integrates image spectroscopy technology with traditional geological prediction methods such as drilling method and geophysical prospecting method, and proposes a set of multi-source and three-dimensional survey methods from macro to micro, which can realize the accurate identification of the adverse geological shape (location, shape and scale) and nature (type and nature) in the tunnel, and provide useful reference for advanced geological prediction of tunnels.
  • Image spectroscopy technology can achieve non-contact measurement of surface minerals in the tunnel site area and surface minerals of surrounding rocks in the tunnel.
  • Remote sensing image analysis can identify lithological information of a large range of regional geology and predict regional fracture zones.
  • Push-broom spectral imaging can classify the mineral composition and types of rocks in the tunnel. Therefore, if image spectroscopy technology is introduced into tunnel geological survey, the efficiency of tunnel geological survey can be greatly improved, and multi-scale identification and prediction of adverse geological bodies can be achieved.
  • the present invention adopts the following technical solution:
  • the first aspect of the present invention provides a sky-air-ground-tunnel-hole integrated adverse geological identification method, which comprises:
  • the corresponding geological structure information and lithology information are extracted to identify the possible adverse geological types in the key survey areas;
  • the image spectrum information of the geological body around the tunnel face is obtained at the tunnel face to identify the mineral and lithology information inside the tunnel. Then, combined with the geophysical test inside the tunnel and the three-dimensional geological model of the tunnel site, the The relative position of the good geological body and the tunnel face;
  • the drilling location is determined based on the three-dimensional geological model of the tunnel site and the relative positions of the unfavorable geological body and the tunnel face. Based on the results of the on-site drilling test, the type and nature of the unfavorable geological body are finally confirmed.
  • a three-dimensional geological model of the tunnel site is constructed based on the preliminary tunnel survey data.
  • radar data is acquired at the tunnel site using a synthetic aperture radar interferometry method, and a high-resolution digital elevation model is generated by processing the radar data.
  • spectral features, texture features, and geometric feature information are extracted based on remote sensing image data of the tunnel site, and based on their correspondence with minerals and lithology, stratigraphic lithology and mineral information of the tunnel site is inverted;
  • spectral imaging work is carried out in determined key survey areas using drones equipped with spectral cameras.
  • a push-broom spectral imager is used at the tunnel face to identify the mineral and lithology information inside the tunnel.
  • a second aspect of the present invention provides a sky-air-ground-tunnel-hole integrated adverse geological identification system, comprising:
  • the key survey area determination module is used to obtain satellite remote sensing image data and digital elevation models along the tunnel site area, and determine the key survey area through geological analysis;
  • the unfavorable geological type prediction module is used to extract the corresponding geological structure information and lithology information based on the UAV remote sensing spectral images of the key survey area, and identify the unfavorable geological types that may exist in the key survey area;
  • the module for determining the distribution of unfavorable geological bodies is used to obtain the corresponding mineral and lithological information based on the spectral test of the key exploration area where unfavorable geological bodies may exist, and then determine the location, scope and scale of the distribution of unfavorable geological bodies in combination with the surface geophysical exploration results;
  • the relative position determination module is used to obtain the image spectrum information of the geological body around the tunnel face at the tunnel face, identify the mineral and lithology information inside the tunnel, and then determine the relative position of the unfavorable geological body and the tunnel face in combination with the geophysical exploration test inside the tunnel and the three-dimensional geological model of the tunnel site;
  • the anomaly verification module is used to determine the drilling location based on the three-dimensional geological model of the tunnel site and the relative position of the unfavorable geological body and the tunnel face, and finally confirm the type and nature of the unfavorable geological body based on the results of the on-site drilling test.
  • a three-dimensional geological model of the tunnel site is constructed based on the preliminary survey data of the tunnel;
  • radar data is acquired in the tunnel site area using a synthetic aperture radar interferometry method, and a high-resolution digital elevation model is generated by processing the radar data;
  • spectral features, texture features, and geometric feature information are extracted based on remote sensing image data of the tunnel site, and based on their correspondence with minerals and lithology, stratigraphic lithology and mineral information of the tunnel site is inverted;
  • the key survey area determination module is further used for:
  • a third aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the above-mentioned integrated sky-air-ground-tunnel-hole adverse geological identification method.
  • the fourth aspect of the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps in the sky-air-ground-tunnel-hole integrated poor geological identification method as described above are implemented.
  • the present invention has the following beneficial effects:
  • the present invention uses satellite remote sensing technology to identify regional long fault zones, which has macroscopic characteristics; UAV remote sensing has higher resolution than satellite remote sensing, better image data quality, and is more convenient to obtain; ground spectral tests can directly obtain accurate spectral information on site and verify the accuracy of remote sensing images.
  • satellite remote sensing technology is used to delineate key exploration areas, then UAV remote sensing is used for detailed exploration, and finally ground spectral tests are used for verification, which can more quickly and accurately identify the adverse geological types that may exist in the key exploration areas.
  • the present invention utilizes the advantages of long-range prediction of geophysical exploration technology to identify the location of unfavorable geological bodies, Scope and scale, namely "shape"; drilling technology can directly obtain the lithology and mineral information of the adverse geological section, identify the type and nature of the adverse geological body, namely "property”, and the combination of the two can realize the comprehensive judgment of the "shape” and "property” of the adverse geological body.
  • the present invention uses image spectral analysis to identify and predict unfavorable geological conditions at multiple scales, including sky, air, ground, tunnel and borehole.
  • image spectral analysis uses image spectral analysis to identify and predict unfavorable geological conditions at multiple scales, including sky, air, ground, tunnel and borehole.
  • FIG1 is a flow chart of a method for identifying adverse geological conditions in an integrated manner of sky, space, ground, tunnel and hole according to an embodiment of the present invention.
  • this embodiment provides a sky-air-ground-tunnel-hole integrated bad geological identification method, which specifically includes the following steps:
  • Step 1 Obtain satellite remote sensing image data and digital elevation models along the tunnel site, and determine the key survey areas through geological analysis.
  • satellite optical remote sensing imaging is carried out in the tunnel site to obtain remote sensing image data;
  • radar data is obtained by synthetic aperture radar interferometry in the tunnel site, and a high-resolution digital elevation model is generated by processing the radar data;
  • spectral characteristic information of the tunnel site is extracted through the acquired remote sensing image data, and stratigraphic lithology and mineral information of the tunnel site is inverted based on the correspondence between spectral characteristics and minerals and lithologies;
  • terrain characteristic information of the tunnel site is extracted through the digital elevation model; areas in the tunnel site where the geological environment is fragile and stability does not meet the set requirements are inferred through stratigraphic lithology and mineral information and terrain characteristic information, and these areas are designated as potential geological disaster risk areas, i.e., key exploration areas.
  • the radar data processing flow is as follows:
  • the flat ground phase is removed. After image registration and extraction of the flat ground phase, the terrain phase information in the image interferometer phase map can be obtained;
  • h is the elevation information
  • L is the slant range of the radar satellite when taking the main image to observe the earth
  • ⁇ is the radar side viewing angle
  • ⁇ is the baseline inclination
  • S is the spatial baseline.
  • Step 2 Based on the UAV remote sensing spectral images of the key survey area, extract the corresponding geological structure information and lithology and mineral information to identify the possible adverse geological types in the key survey area;
  • step 2 according to the satellite survey data and digital elevation model of the key exploration area, the matching UAV model and the spectral imager are selected, and the corresponding flight route is planned; the UAV flies along the designated route and obtains aerial images of the key exploration area; the aerial images are processed to obtain a three-dimensional geological model of the key exploration area; on-site surveys and sampling of typical minerals are carried out to assist in verifying the accuracy of the UAV aerial images; geological interpretation work is carried out on the three-dimensional geological model, and the possible adverse geological types in the area are predicted.
  • a fixed-wing drone equipped with a high-resolution spectral camera can be used to conduct large-scale surface scanning in key survey areas;
  • Preprocessing of spectral images is used to eliminate background noise generated during data acquisition and transmission, and to eliminate the influence of factors such as atmosphere and water vapor;
  • Step 3 Based on the spectral test of the key exploration area where unfavorable geological bodies may exist, obtain the corresponding mineral and lithology information, and then combine the surface geophysical exploration results to determine the location, scope and scale of the distribution of unfavorable geological bodies;
  • Step 4 Obtain image spectral information of the geological body around the tunnel face at the tunnel face, identify the mineral and lithology information inside the tunnel, and then determine the relative position of the unfavorable geological body and the tunnel face by combining the geophysical exploration test inside the tunnel and the three-dimensional geological model of the tunnel site.
  • the push-broom spectral imager was installed and debugged at the tunnel face; spectral imaging tests were carried out at the face to obtain image spectral information of the face and its surrounding rock mass; the image spectral information was preprocessed and then inverted to obtain the mineral and lithology information of the face and its surrounding rock mass; on-site geophysical tests were carried out to obtain the location, scope and scale of the unfavorable geological body in front of the tunnel face; the results of the tunnel geophysical inversion were comprehensively analyzed with the results of surface geophysical exploration to further confirm the location, scope and scale of the unfavorable geological body; with the tunnel axis as the reference line and a range of 50m on both sides of the circumference, a three-dimensional geological model of the tunnel site area was established using the digital elevation model data of the tunnel site area to determine the relative positions of the unfavorable geological body and the tunnel face.
  • Spectral image preprocessing including radiation correction and dark field correction, is used to eliminate background noise generated during data acquisition and transmission;
  • the unfavorable geological body is marked on the three-dimensional geological section;
  • Step 5 Determine the location of the holes to be drilled based on the 3D geological model of the tunnel site and the relative positions of the unfavorable geological bodies and the tunnel face. Finally, confirm the type and nature of the unfavorable geological bodies based on the results of the on-site drilling tests.
  • the drilling location is selected according to the location of the poor geological body determined by the geophysical prospecting method, and an on-site advance drilling test is carried out to analyze the drilling parameters obtained during the drilling process to obtain the lithology and mineral information of the poor geological section; after the drilling is completed, the core removed by the drill bit is spectrally scanned to identify its lithology and mineral information, and compared with the lithology and mineral information inverted by the drilling parameters to comprehensively analyze the accurate lithology and mineral information of the poor geological section; the scope of the obtained poor geological body is combined with the lithology and mineral type of the poor geological body obtained in the next step to realize the identification of the "shape" and "nature” of the poor geological body; the three-dimensional geological model of the tunnel site is used to arrange the tunnel construction plan to prevent possible geological disasters.
  • the drilling parameters include drilling speed V, drilling thrust F, drill bit speed N, drilling torque M, and drilling depth D.
  • This embodiment provides a sky-air-ground-tunnel-hole integrated bad geological identification system, which includes:
  • the key survey area determination module is used to obtain satellite remote sensing image data and digital elevation models along the tunnel site area, and determine the key survey area through geological analysis;
  • the unfavorable geological type prediction module is used to extract the corresponding geological structure information and lithology information based on the UAV remote sensing spectral images of the key survey area, and identify the unfavorable geological types that may exist in the key survey area;
  • the module for determining the distribution of unfavorable geological bodies is used to obtain the corresponding mineral and lithology information based on the spectral test of the key exploration area where unfavorable geological bodies may exist, and then determine the location, scope and scale of the distribution of unfavorable geological bodies in combination with the surface geophysical exploration results;
  • the relative position determination module is used to obtain the image spectrum information of the geological body around the tunnel face at the tunnel face, identify the mineral and lithology information inside the tunnel, and then combine the geophysical exploration test inside the tunnel and the tunnel site
  • the three-dimensional geological model of the area is used to determine the relative position of the unfavorable geological body and the tunnel face;
  • the anomaly verification module is used to determine the drilling location based on the three-dimensional geological model of the tunnel site and the relative position of the unfavorable geological body and the tunnel face, and finally confirm the type and nature of the unfavorable geological body based on the results of the on-site drilling test.
  • a three-dimensional geological model of the tunnel is constructed based on the survey data of the tunnel site area;
  • radar data is acquired in the tunnel site area using a synthetic aperture radar interferometry method, and a high-resolution digital elevation model is generated by processing the radar data;
  • spectral features, texture features, and geometric feature information are extracted based on remote sensing image data of the tunnel site, and based on their correspondence with minerals and lithology, stratigraphic lithology and mineral information of the tunnel site is inverted;
  • the key survey area determination module is further used for:
  • each module in this implementation corresponds one-to-one to each step in Example 1, and the specific implementation process is the same, which will not be repeated here.
  • This embodiment provides a computer-readable storage medium on which a computer program is stored.
  • the program is executed by a processor, the steps in the above-mentioned sky-air-ground-tunnel-hole integrated adverse geological identification method are implemented.
  • This embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor.
  • the processor executes the program, the steps in the above-described integrated method for identifying adverse geological conditions in the sky, space, ground, tunnel and hole are implemented.

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Abstract

本发明属于隧道勘察技术领域，为了解决现有技术对隧道内不良地质体判识不够全面的问题，提供天-空-地-隧-孔一体化不良地质识别方法及系统。该方法包括获取沿隧址区的遥感影像数据以及数字高程模型，确定出重点勘察区域；预测出该区域可能存在的不良地质类型；获取可能存在不良地质体的重点勘探区域经光谱试验而获得的矿物及岩性信息，再结合地表地球物理勘探结果，确定不良地质体分布的位置、范围及规模；确定不良地质体和隧道的相对位置；根据隧址区三维地质模型及不良地质体和掌子面相对位置，选择相应钻孔位置，最终确认不良地质体的种类及性质，为隧道超前地质预报提供有益借鉴。

Description

天-空-地-隧-孔一体化不良地质识别方法及系统
本发明要求于2022年10月19日提交中国专利局、申请号为202211276244.3、发明名称为“天-空-地-隧-孔一体化不良地质识别方法及系统”的中国专利申请的优先权，其全部内容通过引用结合在本发明中。
技术领域
本发明属于隧道勘察技术领域，尤其涉及一种天-空-地-隧-孔一体化不良地质识别方法及系统。
背景技术
本部分的陈述仅仅是提供了与本发明相关的背景技术信息，不必然构成在先技术。
隧道建设经常遭遇突水突泥、塌方、大变形等地质灾害，造成重大人员伤亡、严重经济损失和恶劣社会影响。断层、岩溶等不良地质是隧道灾害发生的最大元凶和挑战，超前地质预报是准确探明断层、岩溶等不良地质最直接、有效的手段，已经成为隧道勘察与建设中必不可少的环节。
目前在隧道建设中，钻探法、物探法等传统超前地质预报方法可以对隧道掌子面前方不良地质体进行较为准确的识别与定位，不过现有的技术大多数都聚焦于对不良地质体性质和位置的精确判识，没有先从宏观层次把握隧址区地质构造。若先从宏观层次对隧址区地表矿物、地质构造信息进行分析，再开展隧道内超前地质预报，从隧道及钻孔尺度对掌子面前方不良地质体的性质、位置信息进行识别和预报，就能更加全面地对不良地质体进行判识，同时对隧道开挖揭露后是否会形成地质灾害以及地质灾害的严重程度有更加清晰的认知。具体地，在隧道内不良地质体的识别与预报方面，超前水平钻探法可以通过取芯直接揭露或通过随钻参数直观感知隧道掌子面前方的岩体质量和地层信息的变化，是最直接有效的超前地质预报方法之一，但其具有“一孔之见”的局限，对于孔间地质体无法识别，易导致不良地质体的漏报漏探；物探法可以较准确地探测不良地质体的位置、形状和规模，但物探反演存在多解性难题，并且难以直接定义不良地质体的类型和性质。在传统地质勘察中，矿物分析在不良地质类型和性质判识方面独 具优势，若能将矿物分析的结果融入到钻探法、物探法中，既可以发挥矿物分析在识别不良地质体类型和性质方面的优势，又可以发挥钻探法、物探法在不良地质体位置、形状和规模识别方面的优势。
综上所述，发明人发现，对于复杂山区隧道的勘察，仅依靠单一数据源开展隧址区地质勘察，对隧道内不良地质体判识不够全面，不同的勘察方法具有各自的局限性，对隧道开挖揭露后是否会形成地质灾害以及地质灾害的严重程度认知不够清晰，难以为隧道超前地质预报提供有效借鉴。
发明内容
为了解决上述背景技术中存在的技术问题，本发明提供一种天-空-地-隧-孔一体化不良地质识别方法及系统，创新性地将图像光谱技术与钻探法、物探法等传统地质预报方法相融合，提出了一套从宏观到细观的多源、立体勘察方法，实现隧道内不良地质体形(位置、形状和规模)与性(类型和性质)的精确判识，为隧道超前地质预报提供有益借鉴。
图像光谱技术可以实现隧址区地表矿物和隧道内围岩表面矿物的非接触式测量，遥感影像分析可以识别大范围的区域地质的岩性信息，预测区域断裂破碎带；推扫式光谱成像仪可以对隧道内岩石矿物成分及种类进行划分。因此，若将图像光谱技术引入到隧道地质勘察中，可以大大提高隧道地质勘察的效率，实现对不良地质体的多尺度的识别与预报。
为了实现上述目的，本发明采用如下技术方案：
本发明的第一个方面提供一种天-空-地-隧-孔一体化不良地质识别方法，其包括：
获取沿隧址区的卫星遥感影像数据以及数字高程模型，经地质分析确定出重点勘察区域；
基于重点勘察区域的无人机遥感光谱图像，提取相应地质构造信息及岩性信息，识别出重点勘察区域可能存在的不良地质类型；
基于可能存在不良地质体的重点勘探区域的光谱试验，获取相应矿物及岩性信息，再结合地表地球物理勘探结果，确定不良地质体分布的位置、范围及规模；
在掌子面处获取隧道内部掌子面周围地质体的图像光谱信息，识别隧道内部矿物及岩性信息，再结合隧道内部物探试验以及隧址区的三维地质模型，确定不 良地质体和隧道掌子面的相对位置；
根据隧址区三维地质模型及不良地质体和掌子面相对位置，确定出钻孔位置，基于现场钻进试验结果，最终确认不良地质体的种类及性质。
作为一种实施方式，根据隧道前期勘察资料，构建隧址区的三维地质模型。
作为一种实施方式，在隧址区利用合成孔径雷达干涉测量方法获取雷达数据，通过处理雷达数据生成高分辨率的数字高程模型。
作为一种实施方式，根据隧址区的遥感影像数据，提取光谱特征、纹理特征、几何特征信息，根据其与矿物及岩性的对应关系，反演出隧址区地层岩性与矿物信息；
通过数字高程模型，提取隧址区的地形特征信息；
通过地层岩性与矿物信息和地形特征，推测隧址区中地质环境脆弱和稳定性未达到设定要求的区域，并划定为潜在的地质灾害隐患区，即重点勘查区域。
作为一种实施方式，利用无人机搭载光谱相机，在确定的重点勘察区域开展光谱成像工作。
作为一种实施方式，在掌子面处利用推扫式光谱成像仪识别隧道内部矿物和岩性信息。
本发明的第二个方面提供一种天-空-地-隧-孔一体化不良地质识别系统，其包括：
重点勘察区域确定模块，其用于获取沿隧址区的卫星遥感影像数据以及数字高程模型，经地质分析确定出重点勘察区域；
不良地质类型预测模块，其用于基于重点勘察区域的无人机遥感光谱图像，提取相应地质构造信息及岩性信息，识别出重点勘察区域可能存在的不良地质类型；
不良地质体分布确定模块，其用于基于可能存在不良地质体的重点勘探区域的光谱试验，获取相应矿物及岩性信息，再结合地表地球物理勘探结果，确定不良地质体分布的位置、范围及规模；
相对位置确定模块，其用于在掌子面处获取隧道内部掌子面周围地质体的图像光谱信息，识别隧道内部矿物及岩性信息，再结合隧道内部物探试验以及隧址区的三维地质模型，确定不良地质体和隧道掌子面的相对位置；
异常验证模块，其用于根据隧址区三维地质模型及不良地质体和掌子面相对位置，确定出钻孔位置，基于现场钻进试验结果，最终确认不良地质体的种类及性质。
作为一种实施方式，在所述相对位置确定模块中，根据隧道前期勘察资料，构建隧址区的三维地质模型；
作为一种实施方式，在所述重点勘察区域确定模块中，在隧址区利用合成孔径雷达干涉测量方法获取雷达数据，通过处理雷达数据生成高分辨率的数字高程模型；
作为一种实施方式，根据隧址区的遥感影像数据，提取光谱特征、纹理特征、几何特征信息，根据其与矿物及岩性的对应关系，反演出隧址区地层岩性与矿物信息；
作为一种实施方式，所述重点勘察区域确定模块还用于：
通过数字高程模型，提取隧址区的地形特征信息；
通过地层岩性与矿物信息和地形特征，推测隧址区中地质环境脆弱和稳定性未达到设定要求的区域，并划定为潜在的地质灾害隐患区，即重点勘查区域。
本发明的第三个方面提供一种计算机可读存储介质，其上存储有计算机程序，该程序被处理器执行时实现如上述所述的天-空-地-隧-孔一体化不良地质识别方法中的步骤。
本发明的第四个方面提供一种计算机设备，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，所述处理器执行所述程序时实现如上述所述的天-空-地-隧-孔一体化不良地质识别方法中的步骤。
与现有技术相比，本发明的有益效果是：
(1)本发明利用卫星遥感技术识别区域性长大断裂带，具有宏观的特点；无人机遥感相对于卫星遥感分辨率高、影像的数据质量更好，获取更方便；地面光谱试验可以直接获取现场精确的光谱信息，验证遥感影像的准确性。先利用卫星遥感技术划定重点勘探区域，再利用无人机遥感做精细化勘探，最后利用地面光谱试验进行验证，可以更加快速、精准地识别重点勘查区可能存在的不良地质类型。
(2)本发明利用物探技术的远程预报的优点，可以识别不良地质体的位置、 范围及规模，即“形”；钻探技术可以直接获取不良地质段的岩性与矿物信息，识别不良地质体的种类及性质，即“性”，二者结合实现不良地质体“形”与“性”的综合判识。
(3)本发明基于图像光谱分析进行天-空-地-隧-孔不良地质多尺度的识别预报，通过卫星遥感与无人机遥感影像从宏观到微观，逐步缩小不良地质体的探测范围，再使用物探方法、钻探方法识别不良地质体的范围及种类，形成一套从宏观到细观的多源、立体勘察方法，实现隧道内不良地质体“形”与“性”的精确判识。
本发明附加方面的优点将在下面的描述中部分给出，部分将从下面的描述中变得明显，或通过本发明的实践了解到。
附图说明
构成本发明的一部分的说明书附图用来提供对本发明的进一步理解，本发明的示意性实施例及其说明用于解释本发明，并不构成对本发明的不当限定。
图1是本发明实施例的天-空-地-隧-孔一体化不良地质识别方法流程图。
具体实施方式
下面结合附图与实施例对本发明作进一步说明。
应该指出，以下详细说明都是例示性的，旨在对本发明提供进一步的说明。除非另有指明，本文使用的所有技术和科学术语具有与本发明所属技术领域的普通技术人员通常理解的相同含义。
需要注意的是，这里所使用的术语仅是为了描述具体实施方式，而非意图限制根据本发明的示例性实施方式。如在这里所使用的，除非上下文另外明确指出，否则单数形式也意图包括复数形式，此外，还应当理解的是，当在本说明书中使用术语“包含”和/或“包括”时，其指明存在特征、步骤、操作、器件、组件和/或它们的组合。
实施例一
参照图1，本实施例提供一种天-空-地-隧-孔一体化不良地质识别方法，其具体包括如下步骤：
步骤1：获取沿隧址区的卫星遥感影像数据以及数字高程模型，经地质分析确定出重点勘察区域。
在步骤1的具体实施过程中，在隧址区开展卫星光学遥感成像，获取遥感影像数据；在隧址区利用合成孔径雷达干涉测量方法获取雷达数据，通过处理雷达数据生成高分辨率的数字高程模型；通过获取的遥感影像数据，提取隧址区的光谱特征信息，根据光谱特征与矿物、岩性对应关系，反演获取隧址区地层岩性与矿物信息；通过数字高程模型，提取隧址区的地形特征信息；通过地层岩性与矿物信息、地形特征信息推测隧址区中地质环境脆弱和稳定性未达到设定要求的区域，将这些区域划定为潜在的地质灾害隐患区，即重点勘查区域。
具体地，雷达数据的处理流程如下：
(1)对不同时段覆盖同一地区的重复影像进行配准；
(2)通过图像滤波生成干涉相位图；
(3)基于轨道参数和成像区域中心点位置信息，去除平地相位，经过图像配准及取出平地相位处理后，就可以获取影像干涉相位图中的地形相位信息；
(4)对影像干涉相位图中的地形相位信息进行解缠处理，获得地形相位的真实值；
(5)通过相位到高程的转换处公式，获得数字高程模型。
上式中，h是高程信息，是地形相位的真实值，L为雷达卫星在拍摄主影像对地观测的斜距，θ为雷达侧视角，α为基线倾角，S为空间基线。
遥感影像数据的分析流程如下：
(1)对获取的卫星遥感影像数据进行预处理，包括辐射校正、大气校正、几何校正，以消除影像背景噪声；
(2)对预处理后的卫星遥感影像，通过光谱角匹配的方法，提取隧址区各点位的光谱特征信息；
(3)进行野外现场踏勘，采集隧址区典型岩石、矿物，建立岩性光谱库；
(4)利用光谱特征信息，结合已有的光谱数据库，匹配隧址区的岩性与矿物信息。
步骤2：基于重点勘察区域的无人机遥感光谱图像，提取相应地质构造信息及岩性与矿物信息，识别出重点勘察区域可能存在的不良地质类型；
在步骤2的具体实施过程中，根据重点勘查区域的卫星勘察资料及数字高程模型，选用相匹配的无人机机型及搭载的光谱成像仪，并规划相应飞行路线；无人机沿指定路线飞行并获取重点勘查区航拍影像；对航拍影像进行处理，获得重点勘察区三维地质模型；对典型矿物进行现场勘察取样，辅助验证无人机航拍影像的准确性；针对三维地质模型开展地质解译工作，并预测该区域可能存在的不良地质类型。
其中，无人机的选取要求如下：
(1)若隧址区，气候良好，无大风天气，可以使用固定翼无人机，搭载高分辨率光谱相机，在重点勘查区开展大面积的地表扫描工作；
(2)若隧址区位于山区，地势起伏超过设定阈值，有明显山体遮挡物时，固定翼无人机起降困难，则使用旋翼无人机，该无人机适合在山区复杂条件勘察。
具体地，航拍影像的处理流程如下：
(1)对光谱图像进行预处理，包括辐射校正、大气校正，用来消除数据获取和传输过程中产生的背景噪音，并排除大气和水汽等因素的影响；
(2)对预处理后的光谱图像，通过光谱角匹配的方法，提取重点勘查区各点位的光谱特征信息；
(3)进行野外现场踏勘，采集隧址区典型岩石、矿物，建立岩性光谱库；
(4)利用光谱特征信息，结合已有的光谱数据库，匹配重点勘查区的岩性与矿物信息，构建重点勘查区的三维地质模型。
步骤3：基于可能存在不良地质体的重点勘探区域的光谱试验，获取相应矿物及岩性信息，再结合地表地球物理勘探结果，确定不良地质体分布的位置、范围及规模；
在具体实施过程中，首先开展现场光谱试验，利用非成像光谱仪器，获取该区域的矿物及岩性信息，与无人机遥感图像获取的矿物及岩性信息进行对比分析，进一步确定该区域可能存在的不良地质类型；针对不良地质体的类型选取相匹配的地球物理勘探方法；在可能存在不良地质体的重点勘查区开展地球物理勘探，获取现场物探数据；对物探数据进行反演，获取重点勘查区下方地层模型；根据反演获取的地质模型，开展地质解译，确定不良地质体(断层、破碎岩体或者含水体)赋存的位置、范围及规模。
其中，地球物理勘探方法的选择要求如下：
(1)若要对具有弹性差异的异常体进行探测，例如断层破碎带、破碎岩体等，则采用地震波反射法；
(2)若要对含水体进行定位，则采用电阻率法或者激发极化法。
步骤4：在掌子面处获取隧道内部掌子面周围地质体的图像光谱信息，识别隧道内部矿物及岩性信息，再结合隧道内部物探试验以及隧址区的三维地质模型，确定不良地质体和隧道掌子面的相对位置。
在具体实施过程中，在隧道掌子面处，对推扫式光谱成像仪进行安装调试；在掌子面处开展光谱成像试验，获取掌子面及其周围岩体的图像光谱信息；对图像光谱信息进行预处理，然后反演获取掌子面及其周围岩体的矿物及岩性信息；开展现场物探试验，获取隧道掌子面前方不良地质体的位置、范围及规模；将隧道物探反演的结果与地表地球物理勘探的结果进行综合分析，进一步确认不良地质体的位置、范围及规模；以隧道轴线为基准线，取周线两侧50m范围，采用隧址区数字高程模型数据，建立隧址区三维地质模型，确定不良地质体和隧道掌子面的相对位置。
其中，光谱数据的预处理及反演流程如下：
(1)光谱图像进行预处理，包括辐射校正、暗场校正，用来消除数据获取和传输过程中产生的背景噪音；
(2)将于处理后的高光谱数据读入ENVI软件，显示灰度图像和彩色合成图像；
(3)提取光谱曲线，利用光谱特征信息，结合已有的光谱数据库，匹配隧道掌子面及周围地质体的岩性与矿物信息；
隧址区三维地质模型的建立流程如下：
(1)以隧道轴线为基准线，取周线两侧50m范围，采用数字高程模型，建立隧址区的三维地质剖面；
(2)根据获取的不良地质体与隧道掌子面相对位置关系，不良地质体赋存范围，将不良地质体标定在三维地质剖面上；
(3)赋予掌子面及周围岩体各个点对应的岩性与矿物信息，完成隧道三维地质模型建立。
步骤5：根据隧址区三维地质模型及不良地质体和掌子面相对位置，确定出应钻孔位置，基于现场钻进试验结果，最终确认不良地质体的种类及性质。
具体地，根据物探方法确定的不良地质体位置选择钻孔位置，开展现场超前钻探试验对钻探过程中获取的随钻参数进行分析，获取不良地质段的岩性与矿物信息；钻探完成后，对钻头取出的岩芯进行光谱扫描，识别其岩性与矿物信息，并与随钻参数反演的岩性与矿物信息进行对照，综合分析不良地质段的准确岩性与矿物信息；将获取的不良地质体的范围与下一步骤获取的不良地质体岩性与矿物种类结合，实现对不良地质体“形”与“性”的判识；利用隧址区三维地质模型，安排隧道施工规划，预防可能发生的地质灾害。
其中，随钻参数反演获取不良地质段岩性与矿物信息的流程如下：
(1)开展现场超前钻探试验，获取钻探过程中随钻参数，随钻参数包括钻进速度V、钻进推力F、钻头转速N、钻进扭矩M和钻进深度D。
(2)进行数据预处理，对所获取的数据进行缺失数据补偿、异常数据剔除以及冗余数据监测；
(3)对五个随钻参数进行归一化处理，获得不良地质段的钻进指数；
(4)利用钻进指数，结合已有的钻探数据库，匹配不良地质段的岩性与矿物信息。
实施例二
本实施例提供了一种天-空-地-隧-孔一体化不良地质识别系统，其包括：
重点勘察区域确定模块，其用于获取沿隧址区的卫星遥感影像数据以及数字高程模型，经地质分析确定出重点勘察区域；
不良地质类型预测模块，其用于基于重点勘察区域的无人机遥感光谱图像，提取相应地质构造信息及岩性信息，识别出重点勘察区域可能存在的不良地质类型；
不良地质体分布确定模块，其用于基于可能存在不良地质体的重点勘探区域的光谱试验，获取相应矿物及岩性信息，再结合地表地球物理勘探结果，确定不良地质体分布的位置、范围及规模；
相对位置确定模块，其用于在掌子面处获取隧道内部掌子面周围地质体的图像光谱信息，识别隧道内部矿物及岩性信息，再结合隧道内部物探试验以及隧址 区的三维地质模型，确定不良地质体和隧道掌子面的相对位置；
异常验证模块，其用于根据隧址区三维地质模型及不良地质体和掌子面相对位置，确定出钻孔位置，基于现场钻进试验结果，最终确认不良地质体的种类及性质。
作为一种实施方式，在所述相对位置确定模块中，根据隧址区的勘察资料，构建隧道的三维地质模型；
作为一种实施方式，在所述重点勘察区域确定模块中，在隧址区利用合成孔径雷达干涉测量方法获取雷达数据，通过处理雷达数据生成高分辨率的数字高程模型；
作为一种实施方式，根据隧址区的遥感影像数据，提取光谱特征、纹理特征、几何特征信息，根据其与矿物及岩性的对应关系，反演出隧址区地层岩性与矿物信息；
作为一种实施方式，所述重点勘察区域确定模块还用于：
通过数字高程模型，提取隧址区的地形特征信息；
通过地层岩性与矿物信息和地形特征，推测隧址区中地质环境脆弱和稳定性未达到设定要求的区域，并划定为潜在的地质灾害隐患区，即重点勘查区域。
此处需要说明的是，本实施中的各个模块与实施例一中的各个步骤一一对应，其具体实施过程相同，此处不再累述。
实施例三
本实施例提供了一种计算机可读存储介质，其上存储有计算机程序，该程序被处理器执行时实现如上述所述的天-空-地-隧-孔一体化不良地质识别方法中的步骤。
实施例四
本实施例提供了一种计算机设备，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，所述处理器执行所述程序时实现如上述所述的天-空-地-隧-孔一体化不良地质识别方法中的步骤。
本发明是参照根据本发明实施例的方法、设备(系统)和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框以及流程图和/或方框图中的流程和/或方框的结合。可 提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
以上所述仅为本发明的优选实施例而已，并不用于限制本发明，对于本领域的技术人员来说，本发明可以有各种更改和变化。凡在本发明的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。

Claims (10)

  1. 一种天-空-地-隧-孔一体化不良地质识别方法，其特征在于，包括：
    获取沿隧址区的卫星遥感影像数据以及数字高程模型，经地质分析确定出重点勘察区域；
    基于重点勘察区域的无人机遥感光谱图像，提取相应地质构造信息及岩性信息，识别出重点勘察区域可能存在的不良地质类型；
    基于可能存在不良地质体的重点勘探区域的光谱试验，获取相应矿物及岩性信息，再结合地表地球物理勘探结果，确定不良地质体分布的位置、范围及规模；其中，基于现场光谱试验，利用非成像光谱仪器，获取该区域的矿物及岩性信息，与无人机遥感图像获取的矿物及岩性信息进行对比分析，进一步确定该区域可能存在的不良地质类型；针对不良地质体的类型选取相匹配的地球物理勘探方法；
    在掌子面处获取隧道内部掌子面周围地质体的图像光谱信息，识别隧道内部矿物及岩性信息，再结合隧道内部物探试验以及隧址区的三维地质模型，确定不良地质体和隧道掌子面的相对位置；其中，在掌子面处开展光谱成像试验，获取掌子面及其周围岩体的图像光谱信息；对图像光谱信息进行预处理，然后反演获取掌子面及其周围岩体的矿物及岩性信息；
    根据隧址区三维地质模型及不良地质体和掌子面相对位置，确定出钻孔位置，基于现场钻进试验结果，最终确认不良地质体的种类及性质。
  2. 如权利要求1所述的天-空-地-隧-孔一体化不良地质识别方法，其特征在于，根据隧道前期勘察资料，构建隧址区的三维地质模型。
  3. 如权利要求1或2所述的天-空-地-隧-孔一体化不良地质识别方法，其特征在于，在隧址区利用合成孔径雷达干涉测量方法获取雷达数据，通过处理雷达数据生成高分辨率的数字高程模型。
  4. 如权利要求1所述的天-空-地-隧-孔一体化不良地质识别方法，其特征在于，根据隧址区的遥感影像数据，提取光谱特征、纹理特征、几何特征信息，根据其与矿物及岩性的对应关系，反演出隧址区地层岩性与矿物信息；
    通过数字高程模型，提取隧址区的地形特征信息；
    通过地层岩性与矿物信息和地形特征，推测隧址区中地质环境脆弱和稳定性未达到设定要求的区域，并划定为潜在的地质灾害隐患区，即重点勘查区域。
  5. 如权利要求1所述的天-空-地-隧-孔一体化不良地质识别方法，其特征在于， 利用无人机搭载光谱相机，在确定的重点勘察区域开展光谱成像工作。
  6. 如权利要求1所述的天-空-地-隧-孔一体化不良地质识别方法，其特征在于，在掌子面处利用推扫式光谱成像仪识别隧道内部矿物和岩性信息。
  7. 一种天-空-地-隧-孔一体化不良地质识别系统，其特征在于，包括：
    重点勘察区域确定模块，其用于获取沿隧址区的卫星遥感影像数据以及数字高程模型，经地质分析确定出重点勘察区域；
    不良地质类型预测模块，其用于基于重点勘察区域的无人机遥感光谱图像，提取相应地质构造信息及岩性信息，识别出重点勘察区域可能存在的不良地质类型；不良地质体分布确定模块，其用于基于可能存在不良地质体的重点勘探区域的光谱试验，获取相应矿物及岩性信息，再结合地表地球物理勘探结果，确定不良地质体分布的位置、范围及规模；其中，基于现场光谱试验，利用非成像光谱仪器，获取该区域的矿物及岩性信息，与无人机遥感图像获取的矿物及岩性信息进行对比分析，进一步确定该区域可能存在的不良地质类型；针对不良地质体的类型选取相匹配的地球物理勘探方法；
    相对位置确定模块，其用于在掌子面处获取隧道内部掌子面周围地质体的图像光谱信息，识别隧道内部矿物及岩性信息，再结合隧道内部物探试验以及隧址区的三维地质模型，确定不良地质体和隧道掌子面的相对位置；其中，在掌子面处开展光谱成像试验，获取掌子面及其周围岩体的图像光谱信息；对图像光谱信息进行预处理，然后反演获取掌子面及其周围岩体的矿物及岩性信息；
    异常验证模块，其用于根据隧址区三维地质模型及不良地质体和掌子面相对位置，确定出钻孔位置，基于现场钻进试验结果，最终确认不良地质体的种类及性质。
  8. 如权利要求7所述的天-空-地-隧-孔一体化不良地质识别系统，其特征在于，在所述相对位置确定模块中，根据隧道前期勘察资料，构建隧址区的三维地质模型。
  9. 一种计算机可读存储介质，其上存储有计算机程序，其特征在于，该程序被处理器执行时实现如权利要求1-6中任一项所述的天-空-地-隧-孔一体化不良地质识别方法中的步骤。
  10. 一种计算机设备，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，其特征在于，所述处理器执行所述程序时实现如权利要求1-6 中任一项所述的天-空-地-隧-孔一体化不良地质识别方法中的步骤。
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