The application of seismic techniques to problems in rock mechanics

doi:10.1016/0148-9062(64)90025-7

International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts

Volume 1, Issue 2, March 1964, Pages 169-179

International Journa...

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Abstract

This paper describes the application of seismic techniques to two problems in rock mechanics. The seismic location of failure foci is discussed and some results of the location, to within 5 m, of the failure foci around longwall stopes between 2500 m and 3000 m below surface, are presented. The seismic measurement of the immediate subsidence of the surface above a deep level stope, following a failure near the stope, is described and discussed.

References (1)

N.G.W. Cook
The Seismic Location of Rockbursts

Cited by (36)

Automatic early warning of rockbursts from microseismic events by learning the feature-augmented point cloud representation
2024, Tunnelling and Underground Space Technology
This study proposes an automatic early warning system for rockbursts in deeply buried tunnels using microseismic data. A novel machine learning model is introduced, which is the first to treats the microseismic event data as a high-dimensional point cloud. The model utilizes a fast approximated convolution (FAC) method to effectively and efficiently learn features from the raw event data with small model sizes. The model is trained and tested using microseismic data from the Hanjiang-To-Weihe water diversion project. Two competing models, a time series model and a traditional threshold model, are also constructed for comparison. Results show that the proposed model achieves reliable early warnings for 90.1% of rockbursts in the tunnel. This study presents a new and feasible rockburst prediction method that can be used independently or as a supplement to current assessment and management approaches for both tunnel boring machines (TBMs) and drilling- and blasting-excavated tunnels.
An insight from energy index characterization to determine the proneness of rockburst for hard rock
2023, Geomechanics for Energy and the Environment
The evaluation index and classification criterion of coal bursting liability are often used to evaluate hard rock rockburst proneness. In view of the great difference between the engineering conditions of embedding rocks (hard) and coal seam (softer), the evaluation results of rockburst proneness of hard rock are not accord with the actual situation. Aiming at this problem, rockburst tendency indices were studied by laboratory test in this paper. Based on the analysis of the data, it is concluded that the peak-strength strain energy storage index $W_{E T}^{P}$ and residual elastic energy index $A_{E F}$ can reflect the energy and rockburst proneness of hard rock from the elastic energy storage and residual elastic energy. By designing the cyclic loading and unloading test and the uniaxial compression test of rock, the loading rates of the above two kinds of energy indices were determined, and the determination and calculation process of the above two kinds of energy indices were clarified. The experimental results show that the linear elastic energy storage law obtained by cyclic loading and unloading of one sample is not very different from that obtained by multiple samples, both methods can be used for measurement. The peak-strength elastic energy density, pre-peak total input energy density and post-peak failure energy density of rock increase slightly with the strain rate, and the degree of rock fragmentation also has the same trend. The energy index of rock cannot fully reflect the rockburst proneness of rock. Based on the test process and results, in the case of hard rocks, 0.3–1 mm/min could be used for displacement control mode, and 50–140 kN/min should be used for load control mode. Extensometer or instrument sensor can be the strain acquisition methods.
Roof fall threat analysis using fractal pattern recognition and neural network over mine microseismicity in a Central Indian longwall panel overlain by massive sandstone roof
2023, Geosystems and Geoenvironment
Due to its high degree of mechanization, caved longwall mining is the most sophisticated and advanced mining method, and it is widely accepted across world's major coal producing countries. The overlying strata dynamics above goaf (void spaces behind powered supports) acts as the deciding parameter towards smooth and safe longwall operation. Usually, this overhanging load above goaf undergoes regular caving for releasing the excess accumulated stress, but sometimes the presence of massive hard strata (mostly sandstone beds) reduces the cavablity of immediate roof. The delayed caving tends to increase the hanging time and load weight of strata. The excess accumulated stress is released in form of sudden roof falls, which are massive by nature and also considered to be the most serious threat to the underground mines. The aftereffects of these untimely roof falls are often associated with catastrophic consequences in form of fatalities, non-fatal injuries, instrument loss and reduction in productivity. Therefore, fast-automated monitoring of roof stress level with higher degree of precision in real time is highly desired for safe operation of mines, which will have the ability to detect the location (in 3D) and threat level of stressed zones in the overlying strata for setting a precursory alarm towards roof fall forecasting. Similar work has been carried out in the present study, which tends to use the passive microseismicity associated with coal mine for monitoring the stress level in the overlying strata and roof fall forecasting through fractal pattern recognition and neural network over microseismic event distribution. The prime objective of the study was to enhance the safety in the working area of the underground mines through: (a) fast and automated identification of roof fall threat level in real time and to categorized it under five threat classes using fractal pattern recognition of microseismic event distribution, (b) developing a suitable predictive model in order to identify high hazard event windows, which acted as precursory signatures towards roof fall forecasting, and (c) timely identification of stressed areas in the overlying strata for providing prior information towards spatio-temporal forecasting of roof fall.
A novel geophysical method for fractures mapping and risk zones identification in a coalmine, Northeast, China
2021, Energy Reports
Citation Excerpt :
Microseismic monitoring technology employed for the purpose of hazard assessment dates back to 1938 when United States Mine Bureau made an attempt for relating seismic velocity to pillar load (Kaiser et al., 1996) and has now become a routine technology in coal mines (Srinivasan et al., 1997; Ge, 2005; Hudyma and Potvin, 2010). By 1961–1990s, with the technological development in terms of data storage, transmission, and processing, the monitoring system was upgraded from analog to complete digital type (Cook, 1964; Xiao et al., 2016). Due to high demand in coal mines, based on the development of full digital technology, the microseismic technological theory and applications were significantly improved in the last 20 years.
A novel approach for mapping induced fractures and associated lineaments has been introduced based on microseismic data, and thus their contribution towards identification, and prediction of the risk zones which may lead to a collapse or rockburst in a coal mine. By taking Tashan Coal Mine (TCM) in Datong coalfield of China as an example, the real-time microseismic data was acquired for a period of 7 months. The microseismic data was processed using standard processing schemes followed by source location and parameters estimation. The proposed approach utilizes microseismic events, trace them to map the induced fractures, and based on their network to interpret associated lineaments. Based on the configuration, geometry, and network, thousands of fractures were identified which vary in length. Regional lineaments have been interpreted based on the orientation of these fractures. The fractures and lineaments distribution were further correlated with computed microseismic energy distribution. The spatial distribution of microseismic energy helped in identification of a geological discontinuity (fault) that clearly separates the study area into northern and southern parts. The reactivation of this fault may pose significant threats to mass stability, life, and property. The northern half is characterized by more and short length fractures while southern by prolonged and fewer fractures. The upper northern half is dominated by high energy ( $\geq$ 50, 000 J), while the lower part is characterized by variable energy pattern (22,000 to 40, 000 J). It is inferred from the energy-lineaments correlation figure, the northern half describes relatively stronger rock type in comparison to the southern part suggesting different rock deformational behavior. The fractures and lineaments converging towards a single point define risk zones where future collapse or rockburst can be expected. This identification of risk zones provides a strong basis for the real-time prediction of future catastrophic hazards in the coal mines. This study may benefit global underground engineering researchers for hazards prediction and establishing of the early warning systems.
Prediction of rockbursts in a typical island working face of a coal mine through microseismic monitoring technology
2021, Tunnelling and Underground Space Technology
Citation Excerpt :
It has been widely used to monitor coal mining, tunnel construction, hydropower station and other engineering fields. ( Cook, 1964) first used seismic data to analyze the rock fracture in the East Rand Proprietary Mines and gain a conclusion that is of great reference value. ( Srinivasan et al., 1999) analyzed the relationship between the microseismic parameters and the rock mass stress through the microseismic monitoring results of the Champion Reef mine, and discussed the three parameters that may be the precursor information of the rockburst. (
Coal has dominated the energy structure in China for a long time. In recent years, dynamic disasters such as rockbursts have affected the safety of coal mine in production with the increase of coal mining depth. Microseismic monitoring is a non-intrusive monitoring technique that can be used to collect much key information: it has been widely applied in coal mine safety monitoring. In this paper, the failure mechanism and energy conversion in a coal-rock mass during mining were investigated, revealing the controlling effect of the surrounding rock mass on the coal seam. microseismic events during mining were monitored by using a self-built high-precision microseismic monitoring system, a variety of analytical methods have been used to quantify the monitoring results, and two rockburst accidents have been identified. The responses of different parameters before the rockburst were analyzed, and the response characteristics of different parameters to rockburst were summarized. The functional relationship between microseismic energy and rock damage was established by classical Benioff strain theory. Combined with the microseismic energy, strain, the degree of damage and the damage, the model of coal-rock mass was verified and modified through physical experiments. A new parameter for rockburst prediction (the energy rockburst warning (ERW) index) was defined and the numerical relationship between ERW and microseismic energy was deduced. The monitoring data were analyzed using this model and results showed that compared with other analysis, the new model can effectively assess the stability of coal-rock mass to a certain extent.
A case study of collapses at the Yangshan tunnel of the Coal Transportation Channel from the Western Inner Mongolia to the Central China
2019, Tunnelling and Underground Space Technology
Citation Excerpt :
The MS monitoring technique was developed to research rockbursts in mines at first. Cook (1964) first used the seismic data of the East Rand Proprietary Mines to gain significant insight into the fundamental nature of the rockburst problem. Fujii et al. (1997) proposed a seismic moment method to predict the rockbursts in the Horonai coal mine and the Miike coal mine, Japan.
Collapse is one of the most frequent and catastrophic hazards in tunnel engineering, which poses serious threats to the safety of personnel and great influence on the excavation schedule. This study presents the geotechnical study carried out after two violent collapses at the Yangshan tunnel of the Coal Transportation Channel from the Western Inner Mongolia to the Central China on July 2, 2017 and July 24, 2017, respectively. The in-situ stresses were first measured by a hydraulic fracturing test close to the first collapse area, and then a comprehensive investigation was conducted to study the causes of the collapses, i.e., the highly concentrated deviatoric stress at the shallow roof and the primary support parameters at the collapse areas. The microseismic (MS) monitoring technique was employed to study the progressive failure process of the surrounding rock mass and to warn of the geological hazard at the Yangshan tunnel. An active MS event zone at the Yangshan tunnel was identified by analyzing the spatial-temporal distribution and event density contour of the 303 recorded MS events, which was in good agreement with the cracking and spalling of the surrounding rock mass. The cracks at the crown in the axial direction were identified as tensile failures of the surrounding rock mass, because most of the events at the shallow roof registered the ratio of S-wave energy to P-wave energy less than 10. The average energy level gradually increased to an extremely high level was recognized as a precursor to the macroscopic cracking of the surrounding rock mass, and the collapse hazard at the Yangshan tunnel may be predicted by quantitative interpretation of the MS data. This study is valuable to understand the collapse hazard of tunnels characterized by high horizontal in-situ stresses and provide a method to warn of the failures.

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The application of seismic techniques to problems in rock mechanics☆

Abstract

The Seismic Location of Rockbursts