1 Introduction

Extracting rock mass leads to a redistribution of the stresses. This redistribution results in zones of high stresses and zones of low stresses in the surrounding rock mass. The areas of high stresses can cause rock pressure phenomena and rock pressure problems. The stress rearrangements can lead to a fracturing of the surrounding rock mass, to rock mass failure, to failure of pillars, or to rock burst damage. The amount of stress changes is depending on the pre-mining stress field, the geological situation, the deposit size, shape and orientation, the prevailing rock mass formation and rock mass properties, and the mine layout and mining sequence. Apart from stress redistributions, also energy changes take place. Accordingly, extracting rock mass leads to a change in the strain energy in the surrounding rock mass, a change in potential energy in the creation of the fracture zone surrounding the excavation, and in the release of seismic energy. The latter two are referred to as energy released. The split of energy into stored strain energy and released energy depends on the stress situation in the mine, the strength of the rock mass, and geological features such as faulting. The stress situation depends on the mining geometry and the percentage extraction. As far as the fairly regular gold mines in South Africa, with the relatively gently dipping tabular reefs of typically less than 2 m in thickness are concerned, numerical systems and design criteria have been developed to calculate the split of energy into stored strain energy and released energy. This has made it possible to develop mining systems for depths below 3000 m.

Unfortunately, the state of seismic and rock engineering for the extraction of relatively massive steeply dipping ore bodies in an environment of high horizontal stresses is less advanced. For this reason, a split between stored strain energy and released energy is not possible at this stage. The aim of this contribution is to analyze the existing mine data to develop a relationship between mining-induced energy changes and occurred seismicity in the Kiruna Mine. This relationship is expressed with a simple approach, which can be implemented in a monitoring program in Kiruna Mine.

2 Correlation of Mining-induced Energy Changes with Released Seismic Energy

The mining-induced energy changes set the baseline for this correlation. The mining-induced energy changes are calculated based on Eq. 1, which provides a rough assessment of the mining-induced energy changes. Where m are the tons of extracted rock, d is the depth of mining, and g is the gravitational acceleration.

$$E=\textit{m*d*g}$$
(1)

It is assumed that the released seismic energy, which is derived from the seismic monitoring system, corresponds to a certain fraction of the mining-induced energy changes. The mining-induced energy changes are compared to the released seismic energy over time. To prevent damage to the mine, the seismic energy should be released as evenly as possible and in small portions over time. In this case, the released seismic energy agrees with the expected energy changes resulting from mining activities (Fig. 1).

Fig. 1
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Evenly released seismic energy

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However, a period of reduced seismic activity, in which the released seismic energy is lower than expected, can be a sign of an upcoming large seismic event or a period of increased seismic activity, in which the released seismic energy catches-up with the mining-induced energy changes (Fig. 2). The reason for this is that the mining-induced energy changes are accumulated as strain energy in the rock mass surrounding the mining area. As a result, large amounts of stored energy can be released suddenly and can cause considerable damage.

Fig. 2
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Irregularly released seismic energy in form of increased seismic activity and large seismic event

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Many studies were made to find a method for predicting upcoming seismic events (e.g. [1,2,3]). In a report of 1997, Srinivasan et al. [1] described the relation between the tons of mined ore and the released seismic energy of the Kolar Gold Fields (KGF) in Southern India. In their observation, they found out that there is a linear relation between mined out ore, seismic events and rock bursts [1]. In another study of 1983, Dempster et al. [4] investigated the relationship between the cumulative released seismic energy and the “cumulative potential energy characteristics” for major gold mining districts in South Africa. In this report, also the depth of mining was considered because this has a significant influence on the stored strain energy in the rock mass. The mining-induced energy changes were calculated after Eq. 1. Their investigation showed that there is a correlation between these two measures, but the ratio between mining-induced energy changes and released seismicity varies a lot between single mines because of many different influencing factors. Besides the depth and the tons of mined ore, also the mining geometry, the geological conditions, and the percentage of extraction have a strong influence on the potential (mining-induced) energy changes, but this was not primarily considered in their work [4].

3 Analyses in Kiruna Mine

3.1 Kiruna Mine

Kiruna Mine is a state-of-the art sublevel caving operation [5]. Iron ore is extracted from a thick, tabular, steeply-dipping ore body, which has a strike extension of about 4 km and a thickness of up to more than 100 m. The extraction depth is around 1000 m below surface. The mine is referred to as seismically active with the largest rock burst occurring in May 2020 with a local magnitude of 4.3 [6, 7].

Due to the reasonable correlations between production activities and the seismicity from Dempster et al. (1983) [4], a potential correlation is investigated in Kiruna Mine. The objective of this correlation is to assess whether such a correlation does in fact exist. If a correlation is found, it could be used for monitoring purposes and as a pre-courser for an upcoming period of increased seismic activity or for an upcoming large seismic event.

Data from the years 2014 to 2020 is used in this analysis. The mining-induced energy changes are derived after Eq. 1. The released seismic energy is calculated with the measured seismic data from Kiruna Mine. Except for three events, for which the calculated seismic energy seems to be erratic, all seismic events have been used. Following that, the cumulative released seismic energy and the mining-induced energy changes are illustrated in diagrams. The cumulated mining-induced energy changes on the left y‑axis, the cumulated seismic energy on the right y‑axis, and the date on the x‑axis. This analysis of the correlation is made for the whole mine as well as for single blocks in the mine. A block is an extraction area in the mine and has a strike extension of about 400 m.

3.2 Correlation on a Mine-wide Scale

The correlation of the two energies is provided in Fig. 3. It shows clearly that the cumulated mining-induced energy changes (blue line) correlate with the cumulated released seismic energy (red line) for the whole mine. As it can be seen, when there was a gap between the mining-induced energy changes and seismic energy, larger seismic events or periods of increased seismic activity occurred, which was the case in mid 2016, late 2018, and in May 2020. Such a gap happened also before the major rock burst in May 2020.

Fig. 3
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Energy correlation for the whole mine

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As a correlation is found, it could be used as a pre-courser in the operation to identify a lack of released seismic energy. However, the correlation does not provide information on the position of the lack of energy release as well as on the time period of increased seismic activity. If such a lack is identified, further investigations are recommended to identify the reasons for the gap and the area where there is a lack of released seismic energy.

Analyses of mines in South Africa showed that about 1% of the mining-induced energy changes are transferred into seismic energy. This percentage is shown in Table 1 as “Seismic characteristic”. This is totally different for the mine in Kiruna because there is much less energy transferred into seismic energy, namely only around 0.00016%. The reasons for this difference may be related to the different shape of the deposit and the different mining method.

TABLE 1 Cumulative seismic energy, potential energy characteristic and seismic characteristic for the major South African gold mining districts (1970–1980) [4]
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3.3 Correlation of a Block Scale

In the next step, single blocks within the Kiruna Mine are investigated to check if there is also a correlation between these two energy measures. This would help to identify the areas in which a lack of released seismic energy is present and in which a larger seismic event or a period of increased seismic activity may occur.

For the correlation on a block scale, the y‑coordinates of the mine-coordinate system are taken as limits for each block. With this separation, we are able to sum up the mining-induced energy and the seismic energy for each block along the y‑axis and correlate them.

Figure 4 provides an example for the block scale analyses. Figure 4 also shows a clear correlation between the cumulated energy changes and the cumulated released seismic energy. Periods of only small amounts of released seismic energy lead to an increasing gap between these two lines, but this gap always closes again either through a period of increased seismic activity or a larger seismic event. The block scale analyses showed further that there are significant differences between individual block of the mine (Table 2). The block numbers in Table 2 are not the real block numbers in the mine. “ESeis” is the sum of the released seismic energy from 2014 to 2020, “EPot” is the sum of the energy changes over time, and the last column shows the percentage of released seismic energy per mining-induced energy changes. In some areas much more energy is released in comparison to the mining-induced energy changes, whereas in others only small amounts of energy are released seismically. Furthermore, the analysis showed also different behaviors in releasing energy between different blocks of the mine. Some blocks released the seismic energy very equally over the time, while some blocks released energy irregularly with a few medium-large seismic events. Reasons for this different behavior could be the result of different geotechnical conditions, the result of different stress conditions(mining depth) or differences in the mine layout and mining sequence. Further investigations are necessary to identify the factors causing the differences.

Fig. 4
figure 4

Energy correlation for a block of the mine

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TABLE 2 Specific released seismic energy of individual blocks and for the whole mine for Kiruna Mine
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4 Discussion of the Results

The comparison between the cumulated mining-induced energy changes and the cumulated released seismic energy shows good correlations on a mine-wide scale. An increasing gap between these two lines tends to be an indicator for an upcoming larger event or for an upcoming period of increased seismic activity. The outlined correlation could be used as a pre-courser in the operation to identify a lack of released seismic energy. Due to the found correlation, the mine operators decided to trial this monitoring measure as one tool for identifying the seismic hazard. If this trial is successful, it may be used a standard measure. However, the mine-wide correlation does not provide information on the position of the area of low energy release as well as of the time period of increased seismic activity and on the characteristics of the period of increased seismic activity. If such a lack is identified, further investigations are recommended to identify the reasons for the gap and the area where there is a lack of released seismic energy. Afterwards specific measures addressing the lack of energy release, such as changes in the layout and sequence or closing down of certain areas until the energy is released, could be implemented. Moreover, the integrity and quality of the support systems should be checked in preparation for the period of increased seismic energy release.

Furthermore, there is a reasonable correlation on a block-scale. All blocks show a reasonable correlation between the mining-induced energy changes and the released seismic energy. Some show a steady slow progress of releasing energy and others show an irregular progress of releasing energy. This can be the result of different geotechnical conditions, the result of different stress conditions (mining depth), or differences in the mine layout and mining sequence. A drawback of the analyses on a block scale is that blocks boundaries are defined on production considerations. For the present correlation, it is, however, recommended to define the boundaries for correlations on a smaller scale (not the mine-wide scale) based on the prevailing geotechnical conditions, which have a significant impact on the characteristic of the seismic energy release. This work is currently ongoing at the mine, and once finished, the newly defined boundaries are planned to be tested for a correlation of the mining-induced energy changes and the seismic energy release. Another drawback on a block-scale is that the measured seismic energy in one block could have its source in a neighboring block because of location accuracy of the seismic system.

5 Conclusions

This contribution has found that the model of assessing mining-induced energy changes based on the depth of mining and the mass of ore extracted can be used for a first rough assessment of seismic energy release and seismic hazard. The basic model works reasonably well in Kiruna on a mine-wide scale but has limitations on a block scale. On a mine-wide scale, there are well defined trends between mining-induced energy changes and seismic energy release. The latter can be steady or non-regular. In the latter case, long periods of low seismic energy release are followed by single large to very large seismic events to bring the seismic energy release back to the overall trend. At a block scale the rough assessment system has its limitations because, particularly because block boundaries are defined by production considerations and not by the prevailing geotechnical conditions. Hence, the correlations on a block-scale are not as good as on a mine-wide scale.

In summary, the found correlations on a mine-wide scale and on a block-scale can be utilized in the seismic risk mitigation as a pre-courser for periods of increased seismic activity or for large seismic events. If such a pre-courser is found, further investigations are recommended to characterize the lack of seismic energy release further and based on these investigations to implement appropriate mitigation measures.