Wu Cai

Quantitative analysis of seismic velocity tomography in rock burst hazard assessment

In order to quantitatively evaluate the relationship between the tomographic images of P wave velocity and rock burst hazard, the seismic velocity tomography was used to generate the P wave velocity tomograms during the retreat of a longwall panel in a coal mine. Subsequently, a novel index (bursting strain energy) was proposed to characterize the mining seismic hazard map. Finally, the structural similarity (SSIM) index in the discipline of image quality assessment was introduced to quantitatively assess the relation between the bursting strain energy index images and the tomographic images of P wave velocity. The results show that the bursting strain energy index is appropriate for quantitative analysis and seems to be better for expressing the mining seismic hazard than the conventional map. The SSIM values of the future bursting strain energy compared with the P wave velocity and the current bursting strain energy reach up to 0.8908 and 0.8462, respectively, which illustrate that the P wave velocity and the bursting strain energy both are able to detect the rock burst hazard region. Specifically, seismic velocity tomography is superior to the bursting strain energy index in the detection range and the precision and accuracy of detection results.

Case Study of Passive Seismic Velocity Tomography in Rock Burst Hazard Assessment During Underground Coal Entry Excavation

Rock bursts, which are sudden dynamic events induced by deformation and fracture of the coal-rock mass, pose a serious threat to the production and safety of underground coal mining throughout the world. With increasing mining depths, rock bursts have become a common safety problem in underground coalmines (Dou et al. 2006; Zhu et al. 2016). In recent years, many rock bursts have occurred during coal entry excavation. Results show that rock bursts are mainly located 30 m behind the excavation face, the lengths of damaged section of entries exceed 100 m, and these areas are also those where rock bursts occur most often during coalface mining. Moreover, it is difficult to determine when a rock burst may occur, and where. For example, a rock burst in the Junde Coal Mine, Hegang mining area, on 18 January 2013 resulted in four deaths and the destruction of 200 m of gateway (Li et al. 2015). The investigation showed that rock bursts also occurred in the damage zone during entry excavation and that rock bursts occurred repeatedly in multiple areas of the coalface during excavation and mining. However, if accident statistics are analysed in more detail, it becomes apparent that stress concentrations were present in these rock burst risk areas because the occurrence of rock bursts mainly depends on the stress distribution around the excavation face. It is well known that the majority of rock bursts are related to geological structures, such as: faulting, folding, and igneous intrusion. Based on field observations of the stress in certain areas, the stress distribution is shown to have been abnormal, where stress concentrations are present. Therefore, stress anomaly information identification is a key issue for use in the monitoring of, and warning system for, rock burst hazards, especially during entry excavation. The prediction of rock bursts in a longwall panel has been researched for over 20 years, and the foci have been: pulverised coal drilling parameters (Gu et al. 2012), electromagnetic emission (He et al. 2011; Wang et al. 2011), borehole exploration (Zhang et al. 2014; Mark and Gauna 2016), and microseismicmonitoring (Cai et al. 2014; Iannacchione andTadolini 2016), with less attention paid to entry excavation. Moreover, the aforementioned conventional methods are not sufficient to meet the needs of engineering projects owing to their shortcomings of being time-consuming, difficult to implement, or causing disruption to production. Seismic velocity tomography allows large-scale rock burst assessment and bestows the advantages of high resolution, high reliability, and clear imagery: it is, therefore, of interest to mining engineers. Depending on the type of source used, tomography is classified as either ‘‘active’’ or ‘‘passive’’ (Swanson et al. 1992). Active tomography, in which the seismic wave is created artificially, is preferred for the detection of stress state (Meglis et al. 2005; Mitra and Westman 2009) and hidden structural defects (Zhao et al. 2000; Cai et al. 2014) in the pre-mining coalface. Passive tomography, which uses mining-induced seismic events as its source, is always feasible for long time-lapse & Lin-ming Dou lmdou@cumt.edu.cn

Roadway Stagger Layout for Effective Control of Gob-Side Rock Bursts in the Longwall Mining of a Thick Coal Seam

Currently, rock bursts pose a serious threat to the safety of miners and equipment in underground coal mining operations, especially in China. The number of coal mines with rock burst hazards is increasing year by year with no signs of letting up. By 31 December 2013, there were 142 coal mines in China which had experienced rock bursts. Each year, rock bursts cause considerable economic loss and enormous casualties. For instance, a rock burst induced by a large thrust fault caused 10 deaths and trapped 75 people on 3 November 2011 during the headgate excavation of LW21221 in Qianqiu coal mine, Yima City, China (Cai et al. 2014a, b; Li et al. 2014). Rock bursts are serious not only because the hazard itself can cause damage, but because it can cause a series of secondary disasters, such as coal and gas outbursts, and gas explosions. The most serious gas explosion recorded to date killed 214 people, injured 30 people, and caused a direct economic loss of U49.689 million. It happened on 14 February 2005 in Sunjiawan coal mine, Fuxin City, China. Investigation revealed that the gas explosion was induced by a rock burst (State Administration of Work Safety, State Administration of Coal Mine Safety 2005). Existing research mainly concentrates on the monitoring, prediction, and prevention of rock bursts (Adoko et al. 2013; Cai et al. 2014a, 2014b; Kornowski and Kurzeja 2012; Mu et al. 2013). Control measures against rock bursts are usually passive and include: de-stress blasting (Konicek et al. 2013), directional fracturing (He et al. 2012a), large-diameter drilling (Li et al. 2014), etc. These measures are time-consuming and only reduce rock burst potential without complete elimination of the hazard. The latest statistical data (Pan et al. 2013) show that 87 % of rock bursts occurred in roadways in China’s coal mines. Compared with the 72.6 % seen from previous statistics (Dou and He 2001), this proportion has increased. Among roadway rock bursts, gob-side rock bursts (GRBs) (i.e., rock bursts occurring in gob-side roadways) account for the majority. For example, the eight rock bursts in the No. 17 coal seam of Xing’an coal mine, Hegang City, China, caused damage to the tailgate and the longwall face eight and two times, respectively. However, the headgate was not damaged at all (see Fig. 1a). The 22 rock bursts in the No. 17 coal seam of Junde coal mine, Hegang City, caused damage to the tailgate, the longwall face, and the headgate 18 times, five times, and once, respectively (see Fig. 1b). Both tailgates in the two coal mines are gob-side roadways. It is common in other coal mines that GRBs account for the majority of rock bursts because gob-side roadways bear a higher stress. If GRBs are controlled effectively, rock burst hazards will be significantly mitigated. In this work, a case study of Yuejin coal mine (YCM) in Yima City, China, was analyzed to ascertain whether, or not, roadway staggered layouts could control GRBs. The aim of this study was to deduce whether, or not, this & Lin-ming Dou lmdou@cumt.edu.cn; kdlzl2010@163.com

Evolution of Stress Concentration and Energy Release Before Rock Bursts: Two Case Studies from Xingan Coal mine, Hegang, China

Since the first recorded rock burst occurred in England in 1738, more than 20 countries have reported rock bursts (Kabiesz and Makowka 2009; Ortlepp and Stacey 1994; Patynska and Kabiesz 2009; Patynska 2013; Uszko 2009), including Germany, South Africa, Poland, the Czech Republic, Canada, Japan, France, etc. In China, rock bursts have become a common safety issue in underground coal mining. The number of coal mines experiencing rock bursts has increased annually (Jiang et al. 2010; Li et al. 2015). To date, 142 coal mines in China have suffered rock bursts which resulted in large economic losses and heavy casualties. For instance, the rock burst on 15 March 2013 in Junde Coal mine, Hegang City, caused the closure of a 200 m gateway, trapped 24 people, and killed four (Lu et al. 2015). The rock burst on 3 November 2011 in Qianqiu Coal mine, Yima City trapped 75 people underground and killed 10 people (Li et al. 2015). The rock burst on 14 February 2005 in Sunjiawan Coal mine, Fuxin City, caused a serious gas explosion and killed 214 people (State Administration of Work Safety, State Administration of Coalmine Safety 2005). The temporal and spatial evolution of mining-induced tremors reveals the process of initiation, development, and expansion of micro-fractures inside the coal-rock mass together with energy accumulation and release. This process may develop to cause either a tremor or a rock burst (Li et al. 2014; Wang et al. 2013). Tremors, rock bursts, or both are more likely to be induced in high-stress regions and the energy released therein is much higher. Therefore, rock burst risk can be evaluated by locating high-stress, and high-energy, regions. Microseismic (MS) monitoring is applicable when detecting the location and energy of mining-induced tremors. Recently, seismic velocity tomography (SVT) has been widely used for inference of high-stress distribution zones in underground mines by introducing seismic signals received by MS monitoring systems. For instance, Luxbacher et al. (2008) and Hosseini et al. (2012, 2013) conducted SVT by introducing mining-induced seismic signals, and found that high-velocity regions agreed well with high-abutment stress regions as predicted by numerical modelling, both of which were observed to redistribute as the coalface advanced. Dou et al. (2012), Banka and Jaworski (2010), and Lurka (2008) conducted SVT at regular time intervals during longwall mining, and found that rock bursts, or strong seismic events (i.e. tremors in underground mining), mainly occurred in high-velocity regions. Meanwhile, the bursting strain energy (BSE) index, which views rock bursts as a process of energy accumulation and release in the coal-rock mass as mining activities disturb the in situ stress field, was proposed here to characterise the spatial distribution of tremors [refer to Cai et al. (2015) for more details]. It was found that the & Si-yuan Gong libcumt@163.com

In Situ Test Study of Characteristics of Coal Mining Dynamic Load

Combination of coal mining dynamic load and high static stress can easily induce such dynamic disasters as rock burst, coal and gas outburst, roof fall, and water inrush. In order to obtain the characteristic parameters of mining dynamic load and dynamic mechanism of coal and rock, the stress wave theory is applied to derive the relation of mining dynamic load strain rate and stress wave parameters. The in situ test was applied to study the stress wave propagation law of coal mine dynamic load by using the SOS microseismic monitoring system. An evaluation method for mining dynamic load strain rate was proposed, and the statistical evaluation was carried out for the range of strain rate. The research results show that the loading strain rate of mining dynamic load is in direct proportion to the seismic frequency of coal-rock mass and particle peak vibration velocity and is in inverse proportion to wave velocity. The high-frequency component damps faster than the low-frequency component in the shockwave propagating process; and the peak particle vibration velocity has a power functional relationship with the transmitting distance. The loading strain rate of mining dynamic load is generally less than class 10−1/s.

Mechanical Analysis of Static Stress Within Fault-Pillars Based on a Voussoir Beam Structure

List of symbols A, B, C Rock blocks A0, B0, C0 Action points of lateral thrust H, L, W Thickness, length and width of rock block (m) h0 Thickness-to-length ratio of rock block (h0 = H/L) Lx Length of fault-pillar (m) a Thickness of voussoir arch (m) d0, d1 Vertical deflections of rock blocks B and C (m) aA, aB, aC Rotation angles of rock blocks A, B, and C ( ) h Angle of fault plane in vertical direction ( ) u, uf Friction angles of rock and fault plane ( ), 0.85 for most rocks and faults c Unit weight of rock (N/m), 2.5 9 10 N/m for most rocks p Applied stress on rock block from overlying strata (Pa) q Total applied stress on rock block from overlying strata and the rock block (q = p?cH) (Pa) rc Uniaxial compressive strength (UCS) of rock (Pa) r, s Compressive stress and shear stress at fault plane (Pa) f(lx) Static stress within fault-pillar (Pa) P Total load on rock block (P = pLW ? cHLW = qLW) (N) T Lateral thrust (N) R0–0, R0–1, R1–2 Shear forces between rock blocks (N) R, R1 Resistance forces of collapsed and broken strata (N) Tf, Rf Normal force and shear force at fault plane (N)

Mining-induced stress changes and rock burst control in a variable-thickness coal seam

In longwall mining, one of the factors most influencing safety in underground coal mining is the stress change, especially when such work is carried out within the thickness variation of a coal seam. This paper analyses the special case of a coal seam which suffers significant overstress as a result of variations in the geometry and dimension of the load itself, in particular, thinning. This is because such thickening and thinning locations of the thickness are generally areas where rock bursts occur most frequently. The results of the research were validated by measuring the stress state in the area under study. A numerical model was established using FLAC3D to understand the results of the field tests and map the zones in the model with a high risk of rock burst. The results of field tests, and the numerical modelling, show that thinning accentuates the stress concentration and energy accumulation. Furthermore, on the basis of a retrospective analysis of what was observed in a coal mine, some preventative measures were instigated as rock burst controls. Also, it was found that rock burst occurrence can be effectively reduced by the use of large-diameter drilling and break-tip blasting.

Tomographic imaging of high seismic activities in underground island longwall face

Anomalous information identification is a key issue for seismic hazard prevention in underground mining. Velocity tomograms can image the stress redistribution around coal face and provide better understanding of strata failure mechanisms. In this paper, based on microseismic events recorded during mining operation, passive tomographic imagings have been presented to assess strong tremor hazard and locate high seismic activity zones around an island coal face under super-thick strata. The zones of high velocity or velocity gradient anomalies have been found to correlate well with the distribution of strong tremors, indicating that velocity tomography is feasible for seismic hazard assessment and risk region division in underground mining.

Mechanical Initiation and Propagation Mechanism of a Thrust Fault: A Case Study of the Yima Section of the Xiashi-Yima Thrust (North Side of the Eastern Qinling Orogen, China)

Thrust faults exist extensively in nature, and their activities often cause earthquakes and disasters involving underground engineering, such as the May 12, 2008 Wenchuan Earthquake; the April 20, 2013 Ya’an Earthquake; and the Nov. 3, 2011 Yima Qianqiu Coal-Mining Accident in China. In this paper, the initiation and propagation of a thrust are discussed from a mechanical viewpoint using fault mechanics and fault-slip analysis, taking as an example the Yima section of the Xiashi-Yima thrust (north side of the eastern Qinling Orogen, China). The research primarily focuses on the stress field and the formation trajectory of the thrust and the genesis of the large-scale inversion thrust sheet. The results show that the thrust results from failures in the compressive deformation state and that its stress state is entirely compressive shear. The rupture trajectory of the thrust develops upward, and the fault fracture zone forms similarly to a listric fault, up-narrow and down-wide. The model results and the genesis of the large-scale inversion thrust sheet are consistent with in situ exploration observations. This investigation can be extended to other thrust faults with similar characteristics, particularly for the design of mining operations in tectonic-active areas. Moreover, this research can be used to further study the mechanism of thrust faults and provide support for the feasibility of using fault-slip analysis to assess fault stability.

Passive velocity tomography for mudstone under uniaxial compression using acoustic emission

A passive velocity tomography method using acoustic emission (AE) was used to study characteristics of AE responses and velocity redistributions in mudstone during uniaxial deformation. Two standard cylindrical samples were uniaxially deformed until failure with axial loading rates of 1.00 × 10–3 mm/s and 2.50 × 10–3 mm/s, respectively. AE activities were monitored using eight sensors and every 100 consecutive AE events were used for tomography calculations. For each sample, three typical tomography results were obtained which reflected significant variation of velocity redistributions. From the experimental data, it can be concluded that the stress drop point observed in the stress-strain curves with high energies and AE events indicated coalescence of micro-cracks and formation of the main shear plane. In the initial tomography phase, the velocity difference was low and few AE events were detected. As loading increased, AE events clustered and velocity differences became obvious with high velocities being mainly located near the sample boundary, whereas low velocities begun to propagate from the bottom corner to the core. When approaching failure, velocity anomaly regions further expanded and low velocity regions interconnected with the position being consistent with macro-fractures in the post-failure samples. The positions of the AE events with large energies over 50 μV·s were found to correlate well with high velocity regions in the tomography results whose calculation phase was conducted prior to the occurrence of large energy AE events. This method can be used for the prediction of large energy AE events in rocks under unconfined pressures.