WO2020228546A1 - 一种基于微震损伤重构的采动应力评估方法 - Google Patents

一种基于微震损伤重构的采动应力评估方法 Download PDF

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WO2020228546A1
WO2020228546A1 PCT/CN2020/088156 CN2020088156W WO2020228546A1 WO 2020228546 A1 WO2020228546 A1 WO 2020228546A1 CN 2020088156 W CN2020088156 W CN 2020088156W WO 2020228546 A1 WO2020228546 A1 WO 2020228546A1
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microseismic
mining
grid
damage
grid node
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蔡武
窦林名
曹安业
巩思园
袁莎莎
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China University of Mining and Technology CUMT
China University of Mining and Technology Beijing CUMTB
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China University of Mining and Technology CUMT
China University of Mining and Technology Beijing CUMTB
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01L—MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE
    • G01L1/00—Measuring force or stress, in general
    • G01L1/25—Measuring force or stress, in general using wave or particle radiation, e.g. X-rays, microwaves, neutrons
    • G01L1/255—Measuring force or stress, in general using wave or particle radiation, e.g. X-rays, microwaves, neutrons using acoustic waves, or acoustic emission
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
    • G01V1/288—Event detection in seismic signals, e.g. microseismics
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
    • G01V1/30—Analysis
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V2210/00—Details of seismic processing or analysis
    • G01V2210/60—Analysis
    • G01V2210/61—Analysis by combining or comparing a seismic data set with other data
    • G01V2210/616—Data from specific type of measurement

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  • the invention relates to a mine mining stress evaluation method, and is particularly suitable for a mining stress evaluation method based on microseismic damage reconstruction in the field of mine safety microseismic monitoring.
  • Mining stress is a kind of this kind of stress after the original stress in the surrounding rock body of underground mining space is redistributed by the influence of mining disturbance. Understanding the distribution characteristics of this stress is one of the indispensable and important basis and work in the mining production process such as face design, stop line design, coal pillar design, safety protection design, support design and so on.
  • the methods mainly used for mining stress observation include: borehole stress monitoring method, electromagnetic radiation method, drill cuttings method, microseismic method, seismic wave velocity tomography method, etc.
  • the borehole stress monitoring method is a direct observation method, but it is only limited to the observation of a small area in the shallow part of the coal wall of the roadway;
  • the electromagnetic radiation method and the drill cuttings method are both indirect evaluation methods, which are based on electromagnetic parameters, A method for evaluating the indirect relationship between the amount of drill cuttings and the mining stress, and this type of method cannot achieve large-scale observations, and at the same time, it is significantly affected by the surrounding environmental noise;
  • the microseismic method is a powerful and effective method for monitoring coal induced by mining disturbances.
  • the tool for rock micro-rupture events has been widely used in the field of mine safety monitoring.
  • its extended seismic wave velocity tomography technology can realize large-scale detection, and is based on the spatial distribution of microseismic events, frequency density distribution and energy
  • the density distribution can indirectly evaluate the influence range of mining stress.
  • the seismic wave velocity tomography technology indirectly calculates the mining stress distribution based on the longitudinal wave velocity distribution, and in the calculation process, a certain number of microseismic events are required as the inversion raw data, which will inevitably cause the inversion period. The unreasonable assumption that the longitudinal wave velocity must be set to a constant leads to a certain calculation error.
  • the calculation of this technology is generally relatively large, and it is difficult to achieve real-time inversion; based on the evaluation of the spatial distribution of microseismic events, frequency density distribution of microseismic frequency and energy density
  • the method can infer the distribution of mining stress by reflecting the distribution of mining cracks to a certain extent, it lacks obvious physical and mechanical correlation. Therefore, based on the microseismic monitoring data, reconstructing a method that has physical and mechanical significance and can approximate real-time large-scale evaluation of mining stress has very important practical value and practical significance.
  • Purpose of the invention Aiming at the shortcomings of the above-mentioned technology, provide a mining stress evaluation method based on microseismic damage reconstruction, specifically based on real-time microseismic monitoring data, synchronous calculation to obtain the mining stress distribution, to achieve coal mining process Approximate real-time inversion of stress.
  • the mining stress evaluation method based on microseismic damage reconstruction of the present invention first reconstructs the stope's damage parameters according to the microseismic parameters; then obtains the stope stress distribution by correlating the damage parameters based on the damage mechanics, and then Obtain the mining stress field distribution,
  • the assessment of a region is formed to mesh FIG meshing, statistically circle corresponding to each grid node regions statistics window using the cumulative statistical methods to calculate the cumulative deformation of each region can ⁇ Ei and the number of microseismic events or coal N i
  • the loading experience time ⁇ t i is used as the value of each grid node;
  • the strain-time mode is preferred:
  • ⁇ i E ⁇ t ⁇ t i ⁇ (1-D i )
  • ⁇ i E ⁇ N ⁇ N i ⁇ (1-D i )
  • ⁇ i is the corresponding mining stress value at the i-th grid node
  • E is the elastic modulus
  • ⁇ t is the strain-time coefficient
  • ⁇ N is the strain-microseismic frequency coefficient.
  • each grid node statistical circle corresponding to a region statistics window using the cumulative statistical methods to calculate the cumulative deformation of each region can be the number of microseismic events and ⁇ Ei N i or coal under load as the elapsed time ⁇ t i of each network
  • the calculation formula for the value of the grid node is:
  • ⁇ Ei denotes the i th node corresponds mesh deformation energy accumulated statistics of the circular area
  • i N i denotes the number of grid nodes corresponding to microseismic event statistics circular region
  • E ij denotes the i th grid
  • the node corresponds to the energy of the jth microseismic event in the statistical circle area
  • ⁇ t i represents the load elapsed time of the i-th grid node corresponding to the statistical circle area
  • t iN represents the last microseismic event in the i-th grid node corresponding to the statistical circle area The time when the event occurred
  • t i1 represents the time when the first microseismic event occurred in the statistical circle area corresponding to the i-th grid node.
  • the calculation formula of the average cumulative deformation energy ⁇ F is: In the formula: max ⁇ Ei ⁇ is the maximum cumulative deformation energy value of the assessment area; D c is the corresponding damage parameter value in the fully damaged state, and 0.95 is selected here.
  • the mining stress calculation formula involved in the present invention has obvious physical and mechanical meaning, clear calculation of the parameters involved in the formula, strong universality and operability, suitable for programming realization, and good application feasibility; actual measurement data involved in the calculation process
  • microseismic data from large-scale real-time monitoring of mines has high timeliness, and can approximate real-time inversion of the mining stress distribution during coal seam mining in a large range, and can realize daily monitoring and early warning, which has very important practical value and practical significance.
  • Figure 1 is a schematic diagram of the mining stress distribution of the mining stress evaluation method based on microseismic damage reconstruction of the present invention
  • FIG. 2 is a schematic diagram of grid division of the mining stress evaluation method based on microseismic damage reconstruction of the present invention
  • Figure 3 shows the spatial distribution of microseismic events
  • Figure 4 shows the spatial distribution of accumulated deformation energy based on the calculation of microseismic parameters
  • Figure 5 is a time and space distribution diagram of coal and rock loading experience based on calculation of microseismic parameters
  • Figure 6 is a distribution diagram of damage parameters based on calculation of microseismic parameters
  • Figure 7 is a mining stress distribution diagram based on microseismic damage reconstruction
  • the mining stress distribution (ABCD) shown in Figure 1 will be formed in the coal and rock mass in front of the working face, including elastic zone (AB), plastic zone (BC) and post-peak strain softening zone (CD) , Respectively correspond to the curved subsidence zone, fracture zone and collapse zone in the longitudinal overburden space. From the perspective of damage mechanics, the coal and rock materials from point D to the mined-out area are all fully damaged, and the corresponding cumulative microseismic event distribution density will also reach the maximum in this area;
  • the mining stress evaluation method based on microseismic damage reconstruction of the present invention includes the steps of: first reconstructing the damage parameters of the stope according to the microseismic parameters; then obtaining the stress distribution of the stope by correlating the damage parameters based on the damage mechanics, and then obtaining the mining stress field distributed;
  • ⁇ Ei denotes the i th node corresponds mesh deformation energy accumulated statistics of the circular area
  • i N i denotes the number of grid nodes corresponding to microseismic event statistics circular region
  • E ij denotes the i th grid
  • the node corresponds to the energy of the jth microseismic event in the statistical circle area
  • ⁇ t i represents the load elapsed time of the i-th grid node corresponding to the statistical circle area
  • t iN represents the last microseismic event in the i-th grid node corresponding to the statistical circle area The time when the event occurred
  • t i1 represents the time when the first microseismic event occurred in the statistical circle area corresponding to the i-th grid node.
  • Di is the damage parameter value corresponding to the i-th grid node
  • the strain-time mode is preferred:
  • ⁇ i E ⁇ t ⁇ t i ⁇ (1-D i )
  • ⁇ i E ⁇ N ⁇ N i ⁇ (1-D i )
  • ⁇ i is the corresponding mining stress value at the i-th grid node
  • E is the elastic modulus
  • ⁇ t is the strain-time coefficient
  • ⁇ N is the strain-microseismic frequency coefficient.
  • the example analysis selects the microseismic monitoring data of a coal mining face in the mining stage for analysis. Since the mining speed of the face is approximately uniform and stable, and the average daily footage is 1.2m, the calculation of the present invention is finally explained by using the strain-time model as an example. Implement the present invention according to the idea of the present invention:
  • the evaluation area is divided into three-dimensional grids, the grid spacing s is 10m, the statistical slip radius r is 30m, and the cumulative method is used to calculate the location of each grid node
  • Figure 5 shows the time and space distribution of coal and rock loading experience based on calculation of microseismic parameters
  • the example shows that the parameters involved in the present invention are clearly calculated, universally applicable and operability are strong, and the mining stress distribution obtained by the inversion calculation is reasonable and the effect is good, which can realize the approximate real-time inversion of the mining stress in the coal mining process. play.

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Abstract

本发明涉及一种基于微震损伤重构的采动应力评估方法，适用于矿山安全领域微震监测领域使用。具体包括：对评估区域进行网格划分，并采用累加方法计算每个网格节点的累积变形能ε Ei和微震事件数N i或煤岩受载经历时间Δt i，找出评估区域最大的累积变形能数值max{ε Ei}，并计算出平均累积变形能ε F，在计算获得损伤参量D分布的基础上即可获得采动应力分布。该方法物理力学意义明显、涉及的参量计算明确、普适性和可操作性强，适于编程实现，应用可行性好，可实现煤层采掘过程中采动应力的近似实时反演。

Description

一种基于微震损伤重构的采动应力评估方法 技术领域
本发明涉及一种矿山采动应力评估方法，尤其适用于矿山安全微震监测领域的基于微震损伤重构的采动应力评估方法。
背景技术
采动应力是井下采掘空间围岩体内原始应力受采掘扰动影响重新分布后的一种此生应力。了解该应力的分布特征是工作面设计、停采线设计、煤柱设计、安全防护设计、支护设计等采矿生产过程中不可或缺的重要依据与工作之一。
由于煤层采掘扰动是一个动态过程，因此采动应力也时刻产生动态变化，最终导致这种“黑箱”过程难以直接大范围观测和定量描述。目前主要用于采动应力观测的方法有：钻孔应力监测法，电磁辐射法、钻屑法、微震法、震动波速度层析成像法等。其中，钻孔应力监测法是一种直接观测法，但其仅局限于巷道煤壁浅部小范围区域的观测；电磁辐射法与钻屑法均为间接评估法，是一种根据电磁参量、钻屑量与采动应力之间的间接关系进行评估的方法，并且该类方法也无法实现大范围观测，同时受周围环境噪声影响较为明显；微震法作为一种强有力有效监测采掘扰动诱发煤岩微破裂事件的工具，目前已在矿山安全监测领域得到了广泛应用，尤其是其扩展的震动波速度层析成像技术可实现大范围探测，同时基于微震事件空间分布、微震频次密度分布与能量密度分布，可间接定性评估采动应力的影响范围。然而，震动波速度层析成像技术是根据纵波速度分布间接推算采动应力分布，并且在其计算过程中由于需要一定数量的微震事件作为反演原始数据，从而不可避免地会引起因反演期间纵波速度必须设定为常量的不合理假设导致一定的计算结果误差，同时该技术计算量一般比较大，很难实现实时反演；基于微震事件空间分布、微震频次密度分布与能量密度分布的评估方法，虽然能在一定程度上通过反映采动裂隙分布来推断采动应力分布，但其缺乏明显的物理力学关联。因此，基于微震监测数据重构出一种具有物理力学意义、且能近似实时大范围评估采动应力的方法，具有非常重要的实用价值和现实意义。
发明内容
发明目的：针对上述技术的不足之处，提供一种基于微震损伤重构的采动应力评估方法，具体根据实时获取的微震监测数据，同步计算获得采动应力分布，实现煤层采掘过程中采动应力的近似实时反演。
技术方案：为实现上述目的，本发明的基于微震损伤重构的采动应力评估方法，首先根据微震参量重构采场的损伤参量；然后基于损伤力学通过关联损伤参量获得采场应力分布，进而获得采动应力场分布，
具体步骤如下:
a将评估区域进行网格划分形成网格划分图，以各网格节点对应的统计圆为区域统计窗口，采用累加方法计算各统计区域的累积变形能ε Ei和微震事件数N i或煤岩受载经历时间Δt i作为各网格节点的数值；
b遍历网格划分图中的数列累积变形能ε Ei找到其最大值max{ε Ei}，并计算出评估区域的的平均累积变形能ε F；
c利用公式：
Figure PCTCN2020088156-appb-000001
计算网格划分图中每个网格节点处对应的损伤参量D i，式中D i为第i个网格节点对应的损伤参量数值；
d计算各网格节点处的采动应力数值：
当工作面开采速度近似匀速稳定时，优先采用应变-时间模式：
σ i＝E·α t·Δt i·(1-D i)
当工作面开采速度不稳定时，近似采用应变-微震频次模式：
σ i＝E·α N·N i·(1-D i)
式中：σ i为第i个网格节点处对应的采动应力数值；E为弹性模量；α t为应变-时间系数；α N为应变-微震频次系数，最后对各网格节点处的采动应力数值进行插值，即可获得评估区域的采动应力空间分布信息，最终利用分布信息得到被测区域的应力分布图，为矿井安全设计提供指导依据。
在网格划分图中用s为网格划分间距，r为统计滑移半径，为避免统计滑移过程中遗漏个别微震事件而导致结果失真，两者满足关系如下：
Figure PCTCN2020088156-appb-000002
具体计算过程为：以各网格节点对应的统计圆为区域统计窗口，采用累加方法计算各统计区域的累积变形能ε Ei和微震事件数N i或煤岩受载经历时间Δt i作为各网格节点的数值，其计算公式为：
Figure PCTCN2020088156-appb-000003
Δt i＝t iN-t i1
式中：ε Ei表示第i个网格节点对应统计圆区域的的累积变形能；N i表示第i个网格节点对应统计圆区域的的微震事件个数；E ij表示第i个网格节点对应统计圆区域的第j个微震事件的能量；Δt i表示第i个网格节点对应统计圆区域的受载经历时间；t iN表示第i个网格节点对应统计圆区域中最后一个微震事件发生的时间；t i1表示第i个网格节点对应统计圆区域中第一个微震事件发生的时间。
平均累积变形能ε F的计算公式为：
Figure PCTCN2020088156-appb-000004
式中：max{ε Ei}为评估区域最大的累积变形能数值；D c为完全损伤状态下对应的损伤参量数值，这里选取0.95。
有益效果：本发明涉及的采动应力计算公式物理力学意义明显、公式涉及的参量计算明确、普适性和可操作性强，适于编程实现，应用可行性好；计算过程所涉及的实测数据采用矿井大范围实时监测的微震数据，时效性高，可大范围近似实时反演煤层采掘过程中的采动应力分布，同时可实现日常监测预警，具有非常重要的实用价值和现实意义。
附图说明
图1为本发明基于微震损伤重构的采动应力评估方法的采动应力分布示意图；
图2为本发明基于微震损伤重构的采动应力评估方法的网格划分示意图；
图3为微震事件空间分布图；
图4为基于微震参量计算的累积变形能空间分布图；
图5为基于微震参量计算的煤岩受载经历时间空间分布图；
图6为基于微震参量计算的损伤参量分布图；
图7为基于微震损伤重构的采动应力分布图；
具体实施方式
下面结合附图对本发明做出更进一步的说明。
随着井下煤层开采，工作面前方煤岩体内将形成如图1所示的采动应力分布(ABCD)，包括弹性区(AB)、塑性区(BC)、峰后应变软化区(CD)，分别对应纵向覆岩空间上的弯曲下沉带、裂隙带、垮落带。从损伤力学角度分析，D点至采空区区域的煤岩材料均以达到完全损伤状态，对应的累积微震事件分布密度也会在这个区域达到最大；
本发明的基于微震损伤重构的采动应力评估方法，步骤为：首先根据微震参量重构采场的损伤参量；然后基于损伤力学通过关联损伤参量获得采场应力分布，进而获得采动应力场分布；
具体步骤为：
a.将评估区域进行网格划分形成如图2所示的网格划分图，图中s为网格划分间距，r为统计滑移半径，为避免统计滑移过程中遗漏个别微震事件而导致结果失真，两者满足关系如下：
Figure PCTCN2020088156-appb-000005
其具体计算过程为：以各网格节点对应的统计圆为区域统计窗口，采用累加方法计算各统计区域的累积变形能ε Ei和微震事件数N i或煤岩受载经历时间Δt i作为各网格节点的数值，其中，ε Ei用于计算损伤参量数值(见步骤c)，N i和Δt i分别用于计算应变-微震频次模式与应变-时间模式下的采动应力数值(见步骤d)，其计算公式为：
Figure PCTCN2020088156-appb-000006
Δt i＝t iN-t i1
式中：ε Ei表示第i个网格节点对应统计圆区域的的累积变形能；N i表示第i个网格节点对应统计圆区域的的微震事件个数；E ij表示第i个网格节点对应统计圆区域的第j个微震事件的能量；Δt i表示第i个网格节点对应统计圆区域的受载经历时间；t iN表示第i个网格节点对应统计圆区域中最后一个微震事件发生的时间；t i1表示第i个网格节点对应统计圆区域中第一个微震事件发生的时间。
b.遍历网格划分图中的数列累积变形能ε Ei找到其最大值max{ε Ei}，并计算出评估区域的的平均累积变形能ε F；式中：max{ε Ei}为评估区域最大的累积变形能数值；D c为完全损伤状态下对应的损伤参量数值，这里选取0.95；
c.计算每个网格节点处对应的损伤参量D i：
Figure PCTCN2020088156-appb-000007
式中：D i为第i个网格节点对应的损伤参量数值；
d.计算各网格节点处的采动应力数值：
当工作面开采速度近似匀速稳定时，优先采用应变-时间模式：
σ i＝E·α t·Δt i·(1-D i)
当工作面开采速度不稳定时，近似采用应变-微震频次模式：
σ i＝E·α N·N i·(1-D i)
式中：σ i为第i个网格节点处对应的采动应力数值；E为弹性模量；α t为应变-时间系数；α N为应变-微震频次系数。最后对各网格节点处的采动应力数值进行插值，即可获得评估区域的 采动应力空间分布。
实施例一：
实例分析选取某煤矿工作面回采阶段的微震监测数据进行分析，由于该工作面开采速度近似匀速稳定，平均日进尺为1.2m，因此，本发明计算最终以应变-时间模式为例展开说明。按照本发明思想实施本发明：
(1)根据微震事件空间分布如图3所示；对评估区域进行三维网格划分，取网格间距s为10m，统计滑移半径r为30m，并采用累加方法计算每个网格节点处的累积变形能ε Ei和煤岩受载经历时间Δt i，然后采用插值计算方法，即可得出如图4累积变形能空间分布和图5所示的累积变形能空间分布图；
图5为基于微震参量计算的煤岩受载经历时间空间分布图
(2)遍历网格节点序列ε Ei，获得最大累积变形能max{ε Ei}的数值为9141.3678，依此计算出平均累积变形能ε F的数值为3051.4635。
(3)将ε Ei和ε F代入公式
Figure PCTCN2020088156-appb-000008
获得各网格节点处的损伤参量数值，然后通过插值计算得出损伤参量分布如图6所示。
(4)将实际弹性模量E＝9GPa和系数α t＝0.000026代入σ i＝E·α t·Δt i·(1-D i)，获得各网格节点处的采动应力数值，再通过插值计算得出采动应力分布如图7所示。
实例表明，本发明涉及的参量计算明确、普适性和可操作性强，同时反演计算得出的采动应力分布合理、效果较好，可实现煤层采掘过程中采动应力的近似实时反演。

Claims (3)

  1. 一种基于微震损伤重构的采动应力评估方法，其特征在于首先根据微震参量重构采场的损伤参量；然后基于损伤力学通过关联损伤参量获得采场应力分布，进而获得采动应力场分布，具体步骤如下:
    a将评估区域进行网格划分形成网格划分图，以各网格节点对应的统计圆为区域统计窗口，采用累加方法计算各统计区域的累积变形能ε Ei和微震事件数N i或煤岩受载经历时间Δt i作为各网格节点的数值；
    b遍历网格划分图中的数列累积变形能ε Ei找到其最大值max{ε Ei}，并计算出评估区域的的平均累积变形能ε F；
    c利用公式：
    Figure PCTCN2020088156-appb-100001
    计算网格划分图中每个网格节点处对应的损伤参量D i，式中D i为第i个网格节点对应的损伤参量数值；
    d计算各网格节点处的采动应力数值：
    当工作面开采速度近似匀速稳定时，优先采用应变-时间模式：
    σ i＝E·α t·Δt i·(1-D i)
    当工作面开采速度不稳定时，近似采用应变-微震频次模式：
    σ i＝E·α N·N i·(1-D i)
    式中：σ i为第i个网格节点处对应的采动应力数值；E为弹性模量；α t为应变-时间系数；α N为应变-微震频次系数，最后对各网格节点处的采动应力数值进行插值，即可获得评估区域的采动应力空间分布信息，最终利用分布信息得到被测区域的应力分布图，为矿井安全设计提供指导依据。
  2. 根据权利要求1所述的基于微震损伤重构的采动应力评估方法，其特征在于：在网格划分图中用s为网格划分间距，r为统计滑移半径，为避免统计滑移过程中遗漏个别微震事件而导致结果失真，两者满足关系如下：
    Figure PCTCN2020088156-appb-100002
    具体计算过程为：以各网格节点对应的统计圆为区域统计窗口，采用累加方法计算各统计区域的累积变形能ε Ei和微震事件数N i或煤岩受载经历时间Δt i作为各网格节点的数值，其计算公式为：
    Figure PCTCN2020088156-appb-100003
    Δt i＝t iN-t i1
    式中：ε Ei表示第i个网格节点对应统计圆区域的的累积变形能；N i表示第i个网格节点对应统计圆区域的的微震事件个数；E ij表示第i个网格节点对应统计圆区域的第j个微震事件的能量；Δt i表示第i个网格节点对应统计圆区域的受载经历时间；t iN表示第i个网格节点对应统计圆区域中最后一个微震事件发生的时间；t i1表示第i个网格节点对应统计圆区域中第一个微震事件发生的时间。
  3. 根据权利要求1所述的基于微震损伤重构的采动应力评估方法，其特征在于：平均累积变形能ε F的计算公式为：
    Figure PCTCN2020088156-appb-100004
    式中：max{ε Ei}为评估区域最大的累积变形能数值；D c为完全损伤状态下对应的损伤参量数值，这里选取0.95。
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CN118917038A (zh) * 2024-06-24 2024-11-08 中煤科工开采研究院有限公司 基于应变的煤岩试样损伤评估方法、电子设备及存储介质
CN118917038B (zh) * 2024-06-24 2025-12-12 中煤科工开采研究院有限公司 基于应变的煤岩试样损伤评估方法、电子设备及存储介质
CN119001843A (zh) * 2024-08-09 2024-11-22 中煤科工集团重庆研究院有限公司 基于微震-震动波ct反演的煤矿采场应力集中区量化识别方法
CN120278562A (zh) * 2025-06-10 2025-07-08 山东科技大学 一种长观孔水位与工作面采动关联度评价方法
CN121009702A (zh) * 2025-08-15 2025-11-25 辽宁工程技术大学鄂尔多斯研究院 一种爆破振动作用下含采硐群边坡时变稳定性评估方法
CN121522729A (zh) * 2026-01-15 2026-02-13 龙岩学院 一种地面沉降微动监测系统及其方法

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