Rock mass dynamic response to extraction

许多土木和采矿工程项目都要求开挖岩石以满足地下空间设计要求，或从地壳中提取矿石。矿井、隧道和采场只是广泛应用于土木和采矿工程项目的众多岩石开挖中的一些例子。围岩抽采过程扰乱了围岩的平衡，在开挖周围，一些位置的地压降低，另一些位置的地压升高。这可能会导致不稳定问题，导致松散的岩石块在低岩石压力的情况下坠落。在抽采后岩石压力较大的情况下，开挖可能发生剧烈垮塌，特别是当岩石强度较大且脆性较大时。这被称为岩爆或岩爆。它总是伴随着主岩中微地震活动的发生。微震活动发生时，寄主岩石重新调整自己，以适应开采后岩石压力的突然上升。这种效应被称为岩石对开采的动态响应，这也是本研究的主题。为了避免剧烈的岩石破裂或岩爆造成的灾难，在地下安装了微地震传感器网络，以全天候监测岩石对开采活动的反应。分析数据后，可以确定微地震事件的时间、强度和位置，并估计岩石震动的速度（称为峰值粒子速度），以及提取过程中从宿主岩石释放的地震能量。在过去的几十年里进行了大量的研究，以帮助提高对岩石对提取反应的认识和理解。现在有可能开发出复杂的数值模型，能够模拟地质复杂环境中发现的复杂形状的岩石挖掘，以及原位岩石压力和计划的开采顺序。然而，到目前为止，这些努力大多集中在模拟更简单的“静态”条件下的提取过程，即不伴有地震反应的过程。这一缺陷在本研究中得到了解决，因为它造成了已开发的静态模型与现实之间的差距，即表现出冲击和微震活动的岩石的动态响应。近年来，申请人已经开始解决这一建模缺陷，通过开发描述岩石对提取的动态响应的算法，能够计算提取后的压力，峰值颗粒速度和地震释放的能量。本研究将侧重于开发和验证用于表征岩石对提取的动态响应的算法。随后，它将把开发的算法应用于加拿大矿山的实际应用，在这些矿山中，深度地震对矿山操作员的安全非常重要。

Many civil and mining engineering projects require that the rock be excavated to meet underground space design requirements, or for the purpose of extracting ore material from the earth crust. Shafts, tunnels and mining stopes are only some of the numerous examples of rock excavations widely used in civil and mining engineering projects. The process of rock extraction disturbs the equilibrium of the host rock in that the in-situ rock pressure decreases at some locations and increases at others around the excavation. This may cause instability problems leading to the fall of loose rock blocks in case of low rock pressure. In the case of high post-extraction rock pressure, the excavation may collapse violently, especially when the rock is strong and brittle. This is known as rockburst or strainburst. It is invariably accompanied by the occurrence of microseismic activities in the host rock. Microseismicity occurs as the host rock is re-adjusting itself to the sudden rise in rock pressure following extraction. Such effects are known as the dynamic response of rock to extraction – the topic of this research. In an effort to avoid disasters due to violent rock failure or rockburst, networks of microseismic sensors are installed underground to monitor the response of the rock to extraction activities on a 24/7 basis. When the data is analyzed, it is possible to identify the time, intensity and location of microseismic events and estimate the speed of rock shaking, known as peak particle velocity, and the seismic energy released from the host rock as a result of an extraction process. Much research was done in the past few decades to help advance the knowledge and understanding of the rock response to extraction. It is now possible to develop sophisticated numerical models capable of simulating complex shapes of rock excavations found in geologically complex environments, as well as the in situ rock pressure, and the planned extraction sequence. However, to date, the majority of these efforts focused on simulating the extraction process in the simpler-to-model “static” conditions, i.e. a process that is not accompanied by seismic response. This deficiency is dealt with in this research as it has created a gap between the developed static models and reality, i.e. dynamic response of the rock exhibiting burst and microseismicity. The applicant has begun in recent years to address this modelling deficiency, by developing algorithms depicting the dynamic response of rock to extraction, capable of computing post-extraction pressure, peak particle velocity and seismic energy released. This research will focus on the development and verification of algorithms for the characterization of the dynamic rock response to extraction. Subsequently, it will take the developed algorithms to real-life applications for validation in Canadian mines where tremors at great depth are of much concern to the safety of the mine operators.