| 巷道超前探测的并行Monte Carlo方法及电阻率各向异性影响 |
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| 引用本文： | 刘洋,吴小平.巷道超前探测的并行Monte Carlo方法及电阻率各向异性影响[J].地球物理学报,2016,59(11):4297-4309. |
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| 作者姓名： | 刘洋 吴小平 |
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| 作者单位： | 1. 中国科学技术大学地球和空间科学学院 地震与地球内部物理实验室, 合肥 230026;2. 蒙城地球物理国家野外科学观测研究站, 安徽蒙城 233500 |
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| 基金项目： | 国家自然科学基金（41674076，41374076，41130420），国家高技术研究发展计划（863计划）（2012AA061403、2012AA09A201）和国家重大科学仪器设备开发专项项目任务（2011YQ05006008）联合资助. |
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| 摘 要： | 直流电阻率法通过观测单极-双极装置视电阻率曲线最小值位置估计掌子面前方低阻异常体距离,在巷道超前探测及矿井水害预测与防治工作中有广泛应用,并形成多种经验预测模型.本文基于直流电法巷道超前探测的各向异性电阻率三维有限元数值模拟,给出超前探线性预测模型.然而,实际井下地质结构复杂,异常大小不定且任意分布,而且可能存在有电阻率各向异性,使得目前由简单模型实验或数值模拟获得的预测公式不确定性较大,而且可靠性难于评价.Monte Carlo方法用随机化思想解决非确定性问题,我们将该方法与并行算法结合,对大量不确定的随机模型进行三维数值模拟,以验证各预测模型的准确度及可靠性.结果表明,本文的超前探线性预测模型较其他预测模型更为准确及可靠.但介质各向异性的影响很大,尤其当围岩电阻率具有各向异性时,所有预测模型的准确度及可靠性较差,给安全生产带来很大隐患.
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| 关 键 词： | 超前探测 Monte Carlo方法 并行 电阻率三维数值模拟 各向异性 |
| 收稿时间： | 2016-01-04 |
Parallel Monte Carlo method for advanced detection in tunnel incorporating anisotropic resistivity effect |
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| LIU Yang,WU Xiao-Ping.Parallel Monte Carlo method for advanced detection in tunnel incorporating anisotropic resistivity effect[J].Chinese Journal of Geophysics,2016,59(11):4297-4309. |
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| Authors: | LIU Yang WU Xiao-Ping |
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| Institution: | 1. Laboratory of Seismology and Physics of Earth's Interior, School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, China;2. National Geophysical Observatory at Mengcheng, Anhui Mengcheng 233500, China |
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| Abstract: | Advanced detection in tunnels using the DC (direct current) resistivity method is important to ensure the safety of underground work. When using a pole-dipole array to measure the resistivity in the tunnel, the apparent resistivity curve shows the influence around the tunnel. As the position of the minimum value in the apparent resistivity curve seems to have a relationship with the distance of the low resistivity anomaly in front of the tunnel, several prediction models have been developed by resistivity modeling or experimental measurements in recent years. However, only simple subsurface structure is considered in these models so far. We are not sure whether the developed prediction models are accurate and reliable for the actual complicate subsurface structures. Moreover, the anisotropic resistivity effect should be considered for advanced detection in tunnels.#br#In this paper, we use an unstructured finite element method for 3D DC anisotropic resistivity modeling in tunnels. A linear equation to predict the distance of the low resistivity anomaly in front of the tunnel is deduced. Then we apply the parallel Monte Carlo method to the design of huge number of random models and 3D resistivity modeling of these random models. The statistics results of the prediction for advanced detection in the tunnel are analyzed to evaluate accuracy and reliability for different prediction models, illustrating our linear equation is more accurate and reliable. Finally we focus on the anisotropic resistivity effect and suggest that the available prediction models for the advanced detection in tunnels are completely unreliable especially when the background resistivity is anisotropic, resulting in a safety problem. |
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| Keywords: | Advanced detection Monte Carlo method Parallel 3D resistivity modeling Anisotropy |
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