5 APRESENTAÇÃO DO 2º ARTIGO CIENTÍFICO
5.2 METHODOLOGY
5.2.1 Object of study – Fall of Ground
Fall of ground (FOG) is a condition in which the rock detaches from the gallery's sides, pillars, or roof in an uncontrolled manner, possibly endangering people's safety or causing damage to equipment (Ma et al. 2020). According to Ma et al. (2020), the formation process of a FOG may be the expansion
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and penetration of micro-cracks in the rock, resulting in fracturing and detachment. It is also worth noting the role of seismicity in amplifying these fractures and ejecting fragments (Diederichs 2014).
A statistical analysis of all fall of ground in the Cuiabá Mine between 2018 and 2019 was conducted in an internal report This report could statistically identify the most common conditions of occurrence of FOG. Therefore, it was possible to choose a single FOG (Table 5.1) representative of these conditions for further detailed study. Based on that, the present work seeks to characterize this fall of ground microseismicity.
Table 5.1 - Structural Summary of the characteristics of FOG in study.
5.2.2 Space-time filtering of microseismic events
Brown et al. (2015) mention that the choice of the time period for assessing a given area's seismic hazard depends on its rate of seismic activity and the objective of the work. Accordingly, for medium to short-term mine planning, the authors advise that a period of a few months may be used.
Adopting this advice given by Brown et al. (2015), the microseismic data was filtered to three months before the FOG was selected and a few days after it happened. In this way, the objective was to identify how the rock mass's dynamic and stress behavior temporally, based on the microseismic parameters.
Besides, there was also a spatial filter on the recorded microseismic events. This spatial filter aimed to restrict the analysis only to events close to the mine levels (Table 5.2).
Table 5.2 - Parameters of the filter applied to the microseismic data to restrict distant events in space and time to the FOG in study.
Figure 5.2 shows that when delimiting the data in time and space, it was identified three other FOG in addition to the FOG selected in the present study. Moreover, the same image highlights the region's seismic activity (109 events of local magnitude greater than -1.6 in 124 days). Therefore, the seismic hazard methodologies applied in this work attempt to understand the microseismicity and fall of ground correlation for all these four FOG since they are centered in the same cluster of microseismic events.
Date Orebody Level Elevation (m) Excavation type Lithology
19/07/2018 SER 18 -153 Oredrive Schist/BIF
Date Elevation (m) Northing (m) Easting (m)
Start End Max Min Max Min Max Min
01/04/18 03/08/18 -100 -250 -2050 -2240 -750 -1015
Figura 5.2 - Location of fall of grounds (left) and microseismic events (right), between levels 18 and 19 of the SER orebody.
5.2.3 Aparent stress ratio (ASR)
The use of the apparent stress ratio (ASR) in seismological risk mapping in a mine is described by Brown et al. (2015). The principal objective in calculating this ratio is to identify areas of increasing apparent stress as a guide to identifying rock mass in more stressed regions. It can be calculated by Equation 5.1.
ASR =σa80
σa20 Equation 5.1
Where: σa80 = 80º percentile of apparent stress; σa20 = 20º percentile of apparent stress.
The apparent stress used in the previous equation is obtained by the relationship between energy and moment of microseismic events, parameters automatically obtained by the IMS system. Its formula is defined by Wyss & Brune (1968), in Equation 5.2.
σa = μ(E/M) Equation 5.2
Where: σa = apparent stress (Pa = N/m2); μ = shear modulus of the medium stiffness (N/m2); E = seismic energy (Joules = N.m); M = seismic moment (N.m).
Brown et al. (2015) proposes that the ASR should be calculated over a growing event population (cumulative distribution). Thus, the ASR tells how apparent stress behaves over time, based on the distribution of past events. Therefore, it is a relative relative parameter rather than an absolute parameter.
5.2.4 Short-term seismic hazard
Mendecky (1996) says that the relationship between some mine seismology parameters over time may inform conditions preceding a significant dynamic event, such as a rockburst or a seismic event of greater magnitude. The relationship between some of these parameters is best seen graphically
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(Figure 5.3). Between the parameters presented, the energy index (EI) and the cumulative apparent volume (VAC) will be used in this work.
Figura 5.3 - Evolution of microseismic parameters that may inform a precursor condition of a rockburst or a major seismic event (Ma et al. 2020).
➢ Cumulative apparent volume (VAC)
The cumulative apparent volume (VAC) consists of the sequential sum of each microseismic event's apparent volume (VA) over time. The apparent volume, in turn, is related to the inelastic deformation of the rock mass, at the moment of the seismic event, concerning the apparent stress and rigidity of the rock (Dunn 2005b). Simplifying, the apparent volume quantifies the inelastic deformation in the rock by the seismic event. According to Mendecky (1996), this parameter can be given by Equation 5.3.
𝑉𝐴 = 𝑀
2𝜎𝑎= 𝑀2
2𝜇𝐸 Equation 5.3
Where: VA = apparent volume (m3); M = seismic moment (Nm); σa = apparent stress (N/m2); E = seismic energy (J); μ = stiffness modulus (N/m2).
In this context, a high rate of increase in the apparent volume has been used to indicate the rise in the rock's inelastic deformation and the possibility of a significant seismic event.
➢ Energy Index (EI)
Van Aswegen & Butler (1993) defined the energy index (EI) as the rate of seismic energy irradiated by an event (E) divided by the average of energy irradiated by events of the same seismic moment ([M]), in Equation 5.4.
Equation 5.4
log Ē(𝑀) = 𝑐 + 𝑑 log 𝑀 Equation 5.5 Where: E = seismic energy (Joules = N.m); M = seismic moment (N.m); c, d = coeficients obtained in energy-moment relationhip.
The energy index is also an indicator of changes in the state of stress of the rock, specifically the driving stress from the seismic source during the event (T. H. Ma et al. 2018). The necessary constants for its calculation are obtained by the E-M relationship and its trend line, presented in Equation 5.6 and Figure 5.4 for events in the SER orebody.
log Ē(𝑀) = −6,0759 + 0,8504 log 𝑀 Equation 5.6 Where: c = -6,0579; d = 0,8504.
Figura 5.4 - Relationship between the energy values and the moment of the micro-seismic events near the FOG region under study.
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5.3 RESULTS AND DISCUSSION
5.3.1 Aparent stress ratio (ASR)
The first methodology applied to the microseismic data delimited to the FOG area was calculating the ASR. Figure 5.5 shows the value distribution of the ASR parameter for the filtered events.
Figura 5.5 - Value distribution of apparent stress ratio and local magnitude for the 109 microseismic events used in seismic hazard study, between levels 18 and 19 in the SER orebody.
The ASR graph shows that the rock mass apparent stress is constantly changing, represented by the line's tortuous path. The interesting point is that sharp drops in the ASR occur together with an increase in seismic activity rate. This observation becomes meaningful when considering that seismic events can relieve part of the rock’s existing stress, following a subsequent period of stability, since the accumulated energy had been irradiated. The period between these sudden falls in ASR, on the other hand, is marked by a considerable decrease in the rate of seismic activity and a new accumulation of apparent stress. In the context of the previous graph, it is possible to identify falls of ground always associated with a drop in the apparent stress ratio, even if subtle.
A point to be considered is that significant ASR drops are not contemporary to microseismic events of greater local magnitude. In reality, a higher rate of events, even of low magnitude, had more significant potential to alleviate the rock mass apparent stress conditions.
To better understand the four FOG, each one was treated separately, observing the apparent stress ratio specific to its close area. For this, Brown et al. (2015) propose the interpolation of each event's ASR within a predetermined radius to assign this parameter's value to the mine's excavation boundaries, producing a map. Following the same author, the nearest neighbor was the interpolation method used in this work since spatial adjacent microseismic events should estimate ASR values assigned to the map.
5.3.2 FOG1, FOG2 & FOG3 study
Figura 5.6 - Mapping of seismic hazard by the ASR parameter at levels 18 and 19 of the SER orebody, for the period from 01/04/2018 to 1 day before the FOG in study (located by the star).
Figure 5.6 (a) shows the map of level 19 at Cuiaba Mine in the region where FOG#1 has taken place (11/05/2018). The map was colored according to the interpolation of the apparent stress ratio for microseismic events up to one day before the FOG#1. Hence, it is possible to identify that the seismic hazard map had already indicated high apparent stress in the region. However, beyond the apparent stress condition, the influence of nearby detonations or installed support and reinforcement conditions should be considered in a more detailed analysis of the FOG triggers.
The mapping of seismic hazard to level 18 (Figure 5.6 - b) was insufficient to determine the apparent stress condition in the FOG#2 region. This occurred due to the lack of microseismic events close to the area in the analyzed period. An alternative of estimating the region's apparent stress would be to use the nearest neighbor interpolation with a larger sample search radius. However, this type of approach is not ideal for underground excavations since its influence on the rock in-situ stress reaches up to 5 times the excavation radius when circular (Brady & Brown 2004). Therefore, the apparent stress of very distant microseismic events can present values very different from those expected close to the excavation's surface and mined area. Lastly, it is worth mentioning that the FOG2# is located on an access ramp and the technical crew describes it with a relatively small concrete detachment. Thus, factors other than microseismicity may have conditioned it.
Finally, in Figure 5.6 (c) can be seen that the location of FOG#3 is very close to FOG#1 at level 19. The apparent stress conditions have also changed little in the region in the 38 days between these events. It is noteworthy that both have a similar probable cause in their report, in which the induced stress by excavation and rock mass squeezing would have conditioned them. Again, seismic hazard mapping proved to identify this area prone to instability due to stress accumulation. A critical point lies in the fact that from one period to the next, the ASR remained correctly elevated in the FOG area and that, in both cases, this rate was already high days before the rock rupture.
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5.3.3 FOG4 study
As this work initially aimed to characterize the FOG#4, it will be treated in more detail. Before, it is necessary to understand how the apparent stress changes occurred in the region close to this fall of ground.
Figura 5.7 - Time evolution of the seismic hazard mapping by ASR to level 18, SER orebody.
In the first month of analysis (01/04 to 01/05), few microseismic events in the region were detected, making it impossible to map the apparent stress condition widely. However, despite the limited data in this period, there is a low ASR identified. This situation changes considerably after one month when there is an increase in the rate of seismic activity and events of high apparent stress are concentrated next to area 18SER2°SN. At 03/06 follows a microseismic event of local magnitude equal to 0.5 (greatest of the period analyzed) in the same place at the mine. It is important to mention that this unique microseismic event did not significantly reduce subsequent events' ASR (Figure 5.5), even though having a large magnitude. In the last month considered (6/1 to 7/1), the maintenance of high ASR in area 18 SER2°SN is also identified, even with its adjacent regions showing a decrease in the ratio. This site's persistence in presenting high ASR makes the FOG#4 event plausible in response to the rockmass high stress over a long period.
The mine's technical staff descriptive report of FOG#4 (19/07/2018) presents essential considerations. As a first point to be considered, the area has been excavated as an oredrive, generating a large gap between the mining and gallery areas. Besides, several other mine stopes were allocated and blasted in nearby regions. All of these factors may have contributed to the region remain under high stress during this period and, consequently, the microseismicity was sensitive to this situation. Still, it is identified at Figure 5.5 that after the fall of ground #4 there was a period without seismic activity, and maintenance of the ASR for about 30 days. This fact points to these rupture events' capacity to promote accommodation in the rock mass that lasts until the stresses build up again and the rate of seismic activity returns.
5.3.4 Short-term seismic hazard & FOG
Mendecki (1997) proposes that the relationship between some mine seismology parameters during a time, such as apparent volume and energy index, may indicate precursors’ conditions to rock dynamic events. To verify its effectiveness in the Cuiabá mine context, Figure 5.8 graphically reproduces the VAC and EI parameters' behavior throughout the occurrence of the 4 FOG identified between levels 18 and 19 of the SER body.
Figura 5.8 - Short-term seismic hazard chart for microseismic events at levels 18 and 19 of the SER body.
The graph in Figure 5.8 shows that there is a wide variation in the energy index (EI). On the other hand, the cumulative apparent volume (VAC) parameter shows small changes over time, except for an abrupt increase between June 3rd and 4th 2018.
In general, the application of the short-term seismic hazard methodology proved to be incapable of explaining trends between VAC and EI that were related to FOG. A single observation that can be made is the association of FOG with significant falls in the EI. However, it has to be noted the vast variability in EI values. In this case, the non-compatibility of the short-term seismic hazard method with the FOG analysis does not entirely exclude its potential. It is possible to identify that the abrupt increase in VAC occurs precisely next to the microseismic event of the highest local magnitude recorded (ML = 0.5). The graph in Figure 5.9 better restricts this finding in time.
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Figura 5.9 - Short-term Seismic hazard for the period close to the event of greatest local magnitude recorded in the study area.
Figure 5.9 shows that during the four days before the microseismic event of ML = 0.5, the cumulative apparent volume (VAC) showed a noticeable increase in its rate. Between the 3rd and second day before the event, the energy index (EI) has a downward trend. However, this parameter starts to grow again soon after. Such EI and VAC conditions are similar to what is proposed by Mendecky (1996) to indicate that a large dynamic event may occur shortly. This forecast, in this case, was verified, occurring the seismic event one day later.
Despite the success of the methodology in retro analysis, some observations must be made. The first point is the great difficulty in identifying trends, either negative or positive, for the EI parameter (due to its significant variability). The same is true for VAC, but for the opposite reason, in which the changes are not very significant before the great seismic event. Another fact is the short period of time, about 1 to 2 days, for the precursor conditions to be identified and security actions to be taken. Finally, it must be considered that the Short-term Seismic Hazard method has been used in regions prone to larger seismic events, much higher than 0.5 ML. Therefore, stronger precursor events are captured, resulting in better consistency of microsystemic data and making it easier to identify patterns.
5.4 CONCLUSIONS
The microseismic monitoring system installed at the Cuiabá Mine allowed the relationship between microseismicity and FOG occurrence to be investigated. In this study, a target fall of ground and other three were studied due to the space-time proximity between them. The apparent stress ratio (ASR) proved to be an excellent tool in showing the temporal evolution of rock mass’s apparent stress
linked to changes in the rate of seismic activity. In this sense, sudden falls in the ASR were associated with high frequency of microseismic events and sometimes FOG. Still, the interpolation of ASR value for the mine levels enabled the mapping of regions susceptible to instabilities, with an excellent correlation between FOG locations and areas of high ASR. However, having said all of that, one must consider the low impact of high magnitude events on the ASR method. These events of greater magnitude, in turn, were better understood in the study of short-term seismic hazard, capable of informing precursor conditions for significant microseismic events. Although, this methodology proved to be difficult to apply due to the very different behavior between the energy index (EI) and apparent volume (VAC) values.
Given the results obtained, seismic hazard methodologies showed great potential in identifying areas vulnerable to the seismic activity. It can be said that these methodologies can provide overall security gains for the mine when applied in a regular basis. Also, it worth noting that this type of work could be expanded in the future for other areas of the Cuiabá Mine where is suspected that microseismicity may be triggering the occurrences of fall of ground. In a systematic study of other areas, it would be possible to achieve a better understanding of the seismic activity and its hazard for the mine as a whole. Example of this approach in other mines in the world are shown in the works of Rebuli &
van Aswegen (2013) and Brown et al. (2015).
CAPÍTULO 6 6 CONCLUSÕES
A Mina Cuiabá consiste em uma das mais importantes minas de ouro no Brasil, bem como, apresenta condições de operação desafiadoras pela sua profundidade crescente. Nesse contexto, a magnitude e dinamismo das tensões atuantes no maciço resultam em sismicidade elevada (razão da implementação do monitoramento). Essa característica, muitas vezes encarada como prejudicial, entretanto, pode ser revista como uma oportunidade imensa de estudo do maciço rochoso de forma indireta. Neste aspecto ainda há de ser explorado quais as melhores maneiras de se tratar os dados captados pelo recente monitoramento microssísmico da Mina Cuiabá, cabendo diversos estudos. Dentre esses possíveis estudos, essa monografia é apresentada, com aplicação de várias metodologias encontras em pesquisa bibliográfica.
Como primeiro ponto a ser destacado, o processo de clustering dos mais de 5900 microssismos ocorridos entre 2018 e 2019 permitiu que toda a análise subsequente fosse realizada sobre um grupo de dados menor (Cluster 4), que realmente fosse pertinente a área do fall of ground escolhido (FOG#4).
Pelo estudo do Cluster 4 houve um entendimento mais geral da microssísmica na área, desatacando-se:
identificação da sensibilidade completa do monitoramento na área pela taxa de atividade sísmica (mL ≥ -1); O cálculo teórico da magnitude local máxima (MLmax= 0,6) e parâmetro “b” pela relação Gutenberg-Richard; Observações sobre a relação E-M dos eventos e distinções possíveis sobre seu mecanismo focal. Para esse último, eventos com baixo stress aparente mostraram potencial incipiente em serem utilizado no mapeamento de estruturas geológicas extensas, como a foliação S3 da mina Cuiabá.
Feito a análise microssísmica do Cluster 4, de caráter mais generalista, se sucedeu um estudo mais detalhado dos microssismos próximos ao FOG#4 por metodologias de seismic hazard. Neste estudo, outros 3 FOG foram considerados devido à proximidade e possibilidade de correlação. A primeira metodologia aplicada foi o cálculo do apparent stress ratio - ASR, que, pelo seu gráfico, se provou uma excelente ferramenta em mostrar a evolução temporal do stress aparente do maciço em conjunto com variações na taxa de atividade sísmica. Nesse sentido, quedas bruscas do ASR estiveram associadas a um aumento anterior na frequência dos microssismos e/ou acontecimento de FOG. Ainda sobre o ASR dos eventos microssísmicos, a interpolação desse valor para os níveis da mina possibilitou o mapeamento de regiões susceptíveis a instabilidades, com ótima correlação entre localização de FOG e área de alto ASR. Dito tudo isso, há de se ponderar, entretanto, o baixo impacto de eventos de grande
Feito a análise microssísmica do Cluster 4, de caráter mais generalista, se sucedeu um estudo mais detalhado dos microssismos próximos ao FOG#4 por metodologias de seismic hazard. Neste estudo, outros 3 FOG foram considerados devido à proximidade e possibilidade de correlação. A primeira metodologia aplicada foi o cálculo do apparent stress ratio - ASR, que, pelo seu gráfico, se provou uma excelente ferramenta em mostrar a evolução temporal do stress aparente do maciço em conjunto com variações na taxa de atividade sísmica. Nesse sentido, quedas bruscas do ASR estiveram associadas a um aumento anterior na frequência dos microssismos e/ou acontecimento de FOG. Ainda sobre o ASR dos eventos microssísmicos, a interpolação desse valor para os níveis da mina possibilitou o mapeamento de regiões susceptíveis a instabilidades, com ótima correlação entre localização de FOG e área de alto ASR. Dito tudo isso, há de se ponderar, entretanto, o baixo impacto de eventos de grande