Francesca De Santis
email: francesca.de-santis@ineris.fr

Vincent Renaud
email: vincent.renaud@ineris.fr

Yann Gunzburger
email: yann.gunzburger@univ-lorraine.fr

Pascal Bernard
email: bernard@ipgp.fr

Isabelle Contrucci
email: isabelle.contrucci@ineris.fr

Francesca De
email: francesca.de-santis@ineris.fr.

Ineris

In situ monitoring and 3D geomechanical numerical modelling to evaluate seismic and aseismic rock deformation in response to deep mining

Keywords: mining-induced seismicity, rock mass response, creep, quasi-static stress changes, seismic and aseismic deformations, geomechanical numerical modelling

In this work we investigated seismic and aseismic rock mass behaviors in response to deep underground mining. For this purpose, an area under production of the metal mine of Garpenberg (Sweden) was instrumented with a geophysical and geotechnical monitoring network. In situ monitoring data were analyzed and interpreted considering mining operations and the local geological setting. In addition, a 3D elasto-plastic numerical model was built to better understand the interactions between quasi-static stress changes due to mining and the generation of the induced seismicity. Results of this multiparameter approach show a complex rock mass response. We observed two main types of seismic behaviors: one local and temporally short, directly induced by production, the other long-lasting over time and remote from excavations being mainly controlled by geological heterogeneities. In addition to seismicity, we also observed creep-like phenomena induced by mining. In turn, these time-dependent strains appear to be a third mechanism driving seismicity. All these findings underline the importance of considering both seismic and aseismic deformations when one wants to characterize the rock mass response to mining. This significantly enhances our understanding of the phenomena involved, as well as their interactions, for an improved hazard assessment in deep mining operations.

Introduction

Anthropogenic seismicity related to underground mining excavations, also referred to as mininginduced seismicity, is one of the most documented types of seismicity caused by human activities. Its characteristics have been largely studied worldwide [START_REF] Bischoff | Coal mining induced seismicity in the Ruhr area, Germany[END_REF][START_REF] Gibowicz | Seismicity induced by mining: Recent research[END_REF][START_REF] Hudyma | Seismic hazard in Western Australian mines[END_REF][START_REF] Mendecki | Mine seismology reference book: seismic hazard[END_REF][START_REF] Mendecki | A guide to routine seismic monitoring in mines[END_REF][START_REF] Stec | Characteristics of seismic activity of the Upper Silesian Coal Basin in Poland[END_REF][START_REF] Urbancic | Recent advances in seismic monitoring technology at Canadian mines[END_REF], since many decades, with the aim of forecasting its occurrence and mitigate related hazards. Nevertheless, this problem is still far from being solved, especially when massive mining methods are employed at great depths, requiring a deeper characterization of the phenomena involved. In this framework, to be able to fully describe the rock mass response to mining, both seismic and aseismic mechanisms should be investigated. Indeed, as it will be discussed in the following section, mining-induced stresses can result in seismic as well as in aseismic deformations, which both may have significant impacts in terms of rock mass stability and mining strategies.

If mining-seismicity can be monitored by means of seismic networks, aseismic deformations induced by mining can be evaluated by means of geotechnical instruments, such as extensometers or strain measurement cells. Seismic monitoring, which is nowadays a routine technology for seismic hazard assessment in underground mines [START_REF] Ge | Efficient mine microseismic monitoring[END_REF][START_REF] Hudyma | An engineering approach to seismic risk management in hardrock mines[END_REF], can provide information on large-scale seismic rock mass response when a good coverage of geophones is ensured. On the other hand, geotechnical monitoring is often employed only for local or punctual measurements, not sufficient for describing the aseismic response at large-scale. For this reason, when large-scale geotechnical monitoring is not possible, well calibrated geomechanical numerical models can give an estimation of stress and strain changes due to large-scale mining. There exist nowadays a wide spectrum of modelling approaches and techniques which can be adopted to investigate rock mechanics problems and estimate/simulate rock mass behaviors [START_REF] Jing | A review of techniques, advances and outstanding issues in numerical modelling for rock mechanics and rock engineering[END_REF]. Moreover, several studies demonstrate that static and continuous numerical models, although not accounting for rock fractures neither for transient behaviors due to seismic activity (i.e. dynamic models), can be suitable to investigate the potential for induced seismicity in mines [START_REF] Mk | Mining-induced seismicity: Seismic measurement using multiplet approach and numerical modeling[END_REF][START_REF] Shnorhokian | Analysis of microseismic cluster locations based on the evolution of mining-induced stresses[END_REF][START_REF] Spottiswoode | Energy and stiffness of mine models and seismicity[END_REF][START_REF] Vatcher | Mine-scale numerical modelling, seismicity and stresses at Kiirunavaara Mine, Sweden[END_REF].

These considerations highlight that the coupling between in situ monitoring and geomechanical numerical modelling, could make it possible to better characterize rock mass behaviors in response to mining.

Seismic and aseismic deformations in deep mines

When rock mass volumes are extracted due to underground mine excavations the virgin state of stress is disturbed. This results in the redistribution of the local stress field which can lead to seismic and aseismic deformations in surrounding rocks.

The seismic component of the rock mass response is linked with rupture phenomena which emits seismic signals transmitted as elastic waves [START_REF] Wang | Acoustic emission/microseismic source location analysis for a limestone mine exhibiting high horizontal stresses[END_REF]. Mining-induced seismicity is, thus, the result of fractures propagation inside the rock mass. Depending on fracture dimension and mechanisms involved, mining-induced seismicity can be characterized by microseismic events (M < 2), as well as by much larger events, whose magnitudes can be greater than 3 [START_REF] Alber | Rock mechanical analysis of a M1= 4.0 seismic event induced by mining in the Saar District, Germany[END_REF][START_REF] Pechmann | Seismological report on the 6 August 2007 Crandall Canyon mine collapse in Utah[END_REF].

Generally, mining seismicity is directly induced by stress changes due to excavations.

Consequently, spatiotemporal behaviors of induced seismicity are directly related to spatial and temporal characteristics of mining operations. Moreover, mining, and in particular the volume of extracted rock mass, also influence the energy content of the resulting induced seismic events [START_REF] Glowacka | Continuous evaluation of seismic hazard induced by the deposit extraction in selected coal mines in Poland[END_REF][START_REF] Kijko | Theoretical model for a relationship between mining seismicity and excavation area[END_REF][START_REF] Mcgarr | Seismic moments and volume changes[END_REF]. The larger the volume mined, the greater the radiated seismic energy.

On the other hand, local geological properties can as well influence seismicity in mines. This is the case for the so-called triggered seismicity which is associated with movements along major geological structures. In this case, mining-induced stresses only contribute to the nucleation of the failure, while the rupture process (i.e. events magnitude) is controlled by tectonic or local stress field [START_REF] Dahm | Recommendation for the discrimination of human-related and natural seismicity[END_REF][START_REF] Mcgarr | Case histories of induced and triggered seismicity[END_REF]. As a consequence, triggered events can occur at some distance from mine workings and can be characterized by an erratic time distribution [START_REF] Gibowicz | An Introduction to Mining Seismology[END_REF], as driven by stress changes at larger temporal and spatial scales.

Apart from the influence of geology and mining-induced stress, the interaction between subsequent seismic events through static stress transfer has been as well recognized as a mechanism influencing mining seismicity [START_REF] Marsan | Spatio-temporal analysis of stress diffusion in a mining-induced seismicity system[END_REF][START_REF] Orlecka-Sikora | Response of seismic activity in mines to the stress changes due to mining induced strong seismic events[END_REF]. In this case, stress changes induced by larger seismic events strongly affect location and timing of subsequent seismic activity.

In addition to seismicity, the rock mass response to mining is also characterized by aseismic mechanisms. Indeed, depending on the rate of stress changes and on rock mass mechanical parameters, slow plastic deformations, not detectable from seismic sensors, can occur. Deformations can have a temporally short behavior, as well as being long-lasting in time. Time-dependent strain (i.e. deformation) is known as creep, a phenomenon observed even in brittle rocks [START_REF] Scholz | Mechanism of creep in brittle rock[END_REF]. The primary effect of creep in underground mines is the occurrence of rock deterioration, that is the progressive strength degradation with time [START_REF] Sainoki | Numerical investigation into pillar failure induced by time-dependent skin degradation[END_REF]. This mechanism mainly affects pillars, as well as roofs, walls and floors of mine galleries, resulting in large deformations which can lead to catastrophic failures under the effect of time [START_REF] Alber | Time dependent properties of sandstones and their effects on mine stability[END_REF][START_REF] Kovrizhnykh | Deformation and failure of open and underground mine structures under creep[END_REF]. A seismic phenomena often observed in relation with creep are repeating earthquakes (also called seismic repeaters), almost identical seismic signals emitted from the same seismic source, which are interpreted as locked seismic asperities (fault patches) loaded by surrounding creep of stable slipping fault plane [START_REF] Linde | A slow earthquake sequence on the San Andreas fault[END_REF][START_REF] Perfettini | Postseismic relaxation driven by brittle creep: A possible mechanism to reconcile geodetic measurements and the decay rate of aftershocks, application to the Chi-Chi earthquake, Taiwan[END_REF]. Such repeaters, are observed in many tectonic regions [START_REF] Nadeau | Seismological studies at Parkfield VI: Moment release rates and estimates of source parameters for small repeating earthquakes[END_REF] and in the context of fluid injection for deep geothermal applications [START_REF] Bourouis | Evidence for coupled seismic and aseismic fault slip during water injection in the geothermal site of Soultz (France), and implications for seismogenic transients[END_REF][START_REF] Lengliné | Seismicity related to the hydraulic stimulation of GRT1, Rittershoffen, France[END_REF], while they appear rater uncommon and less investigated in the context of mining induced seismicity.

Nonetheless, a recent study by Naoi et al. [START_REF] Naoi | Unexpectedly frequent occurrence of very small repeating earthquakes (-5.1≤ Mw≤-3.6) in a South African gold mine: Implications for monitoring intraplate faults[END_REF] shows the occurrence of small (-5.1 ≤ Mw ≤ -3.6) repeating earthquakes in a deep South African gold mine.

The analysis of seismic activity, aseismic deformations as well as of their possible interaction is, then, of paramount importance for a correct interpretation of the rock mass response to mining. In this article, we propose to analyze seismic and aseismic behaviors in Lappberget orebody of Garpenberg mine (Sweden) . Previous studies in the same area of Garpenberg, highlighted a complex rock mass behavior in response to mining. More precisely, De Santis et al. [START_REF] Santis | Impact of geological heterogeneities on induced-seismicity in a deep sublevel stoping mine[END_REF] studied spatiotemporal behaviors of seismic clusters in the study area, showing that seismicity can have a local and short-term nature, as well as being long-lasting over time and distant from excavations. In addition, Kinscher et al. [START_REF] Kinscher | Seismic repeaters linked to weak rock-mass creep in deep excavation mining[END_REF] showed the occurrence of seismic repeaters in Garpenberg mine, demonstrating that seismicity in the study area is as well driven by aseismic creep. The present paper presents a continuation of the previous works by De Santis et al. [START_REF] Santis | Impact of geological heterogeneities on induced-seismicity in a deep sublevel stoping mine[END_REF] and Kinscher et al. [START_REF] Kinscher | Seismic repeaters linked to weak rock-mass creep in deep excavation mining[END_REF],

investigating seismic and aseismic mechanisms in Garpenberg mine, coupling in situ monitoring data analysis and geomechanical numerical modelling.

Study area: Garpenberg mine and Lappberget orebody

Garpenberg mine is located in central Sweden and owned by Boliden mining company. Minerals, mainly zinc and silver together with copper, lead and gold as by-products, are extracted from different polymetallic sulfide orebodies, reaching mining depths of about 1300 m. The study area of this article runs between about 1100 m and 1300 m below ground surface, in the block 1250 of Lappberget orebody, the largest and deepest orebody of Garpenberg mine.

Geological setting and rock properties

Lappberget is an almost vertical orebody hosted in a limestone-dolomite unit [START_REF] Ahmadi | High-resolution 2D seismic imaging and forward modeling of a polymetallic sulfide deposit at Garpenberg, central Sweden[END_REF]. Both, the ore and the limestone, are very stiff rocks, with high Young moduli (Table 1). The ore appears to be heterogeneous (Young modulus between 45 and 91 GPa) and characterized by the presence of some weak and very weak zones (Figure 1) mainly constituted by schist rich in talc [START_REF] Santis | Rock mass mechanical behavior in deep mines: in situ monitoring and numerical modelling for improving seismic hazard assessment[END_REF].

These zones pose significant issues in terms of mine infrastructure stability. Indeed, rock falls are quite common at drift's faces when they hit a weakness zone. Such failures are particularly observed in the eastern side of the study area, where weak and very weak zones are mostly present (Figure 1).

Mining method and mining sequence

Block 1250 of Lappberget orebody is exploited using the sublevel stoping mining method with backfilling, which ensures a recovery of the ore close to 100%. Stopes are vertical rock columns lying between consecutive drifts along the entire height of the mine (Figure 2), which are subsequently excavated. Stope production is performed level by level, charging and blasting vertical drill-holes. This allows to mine and, then, collect the ore between two overlaying levels, in so-called sub-stopes. This paper focuses on production performed between February 2015 and December 2016, for a total of 52 sub-stopes extracted in the study area (Figure 2). During this period, Stope 13 (in orange in Figure 2) was completely mined along the entire height of block 1250, following a simultaneous bottom-up and top-down sequence. Therefore, the sub-stope between levels 1157 and 1182 (Figure 2a) was left as pillar and exploited at the end.

Stress measurements and virgin stress state

The stress state in the study area was determined by overcoring method in two different boreholes (H1 and H2) located close to Stope 13 [START_REF] Bouffier | Stress measurement campaign and stress monitoring experiment in the Lappberget mining area, at Garpenberg mine, Boliden. Ineris[END_REF]. Results are summarized in Table 2 in terms of principal stress magnitudes, while principal stress orientations are reported in Figure 3.

Both measurement points show a strong stress anisotropy, with a sub-vertical minor principal stress (σ3) and significantly higher horizontal stresses (Table 2). Major (σ1) and intermediate (σ2) principal stresses are oriented almost parallel (along Y axis) and perpendicular (along X axis) to mine drifts (Figure 3).

None of the measured stress can be assumed to be equal to the virgin stress state, as measures were performed after excavation began. Souley et al. and Tonnellier et al. [START_REF] Souley | Numerical investigation of the development of the excavation damaged zone around a deep polymetallic ore mine[END_REF][START_REF] Tonnellier | Integrating microseismic and 3D stress monitoring with numerical modeling to improve ground hazard assessment[END_REF] back-computed the virgin stress state (i.e. prior to any excavation) of the study area by means of elasto-plastic numerical modelling, based on stress measurements at H1 and H2 locations. The calculated virgin stress state is reported in Table 3. It was obtained by imposing that the vertical principal stress at depth 1155 m equals the overburden weight. Orientation of principal stresses assumes that σ1 is parallel to mine drifts (along the Y axis) and that σ2 is oriented along the X axis, coherently with measurements at H2 (Figure 3 on the right). The back-computed virgin stress state is in agreement with the large-scale average Scandinavian stress field, which is characterized by a sub-horizontal σ1 with mean orientation N120°E ± 45° and generally characterized by a significant anisotropy between principal horizontal stresses and the principal vertical stress [START_REF] Müller | Regional patterns of tectonic stress in Europe[END_REF][START_REF] Stephansson | Stress measurements and tectonic implications for Fennoscandia[END_REF].

Magnitudes of measured stresses significantly differ from that of the virgin stress computed by numerical modelling (see Table 2 andTable 3). This indicates that mining excavations strongly influenced vertical as well as horizontal stresses.

Seismic and aseismic deformation monitoring

The study area of this article was instrumented in December 2014 with a monitoring network installed and operated by Ineris (the French national institute for industrial environment and risks).

The network consists of both strain cells and seismic sensors for monitoring quasi-static deformations and microseismic activity as excavations progress.

Strain cells (named PD and PH) have been installed close to Stope 13, at level 1157 (Figure 4).

Both are composed of 12 strains gauges oriented along different directions. Strain measurement are performed on a one-hour basis with an accuracy of about ± 5 µm/m. This allows determining stress changes by inversion, assuming an elastic behavior of the rock.

Seismic monitoring network is equipped with six 1-component (1C) and five 3-component (3C)

14-Hz geophones installed in such a way that microseismic activity can be recorded within the whole block 1250 (Figure 4). The acquisition system is operating in triggering mode, with an imposed threshold on amplitudes and with a sampling frequency of 8 kHz. Mean location errors are in the order of 15 m within the central area of Lappberget array [START_REF] Santis | Numerical approach for evaluating microseismic array performances: case study of a deep metal mine monitoring network[END_REF]. For a detailed description of methodologies used for seismic events localization and for seismic source parameters estimation, the reader is referred to [START_REF] Santis | Impact of geological heterogeneities on induced-seismicity in a deep sublevel stoping mine[END_REF][START_REF] Santis | Numerical approach for evaluating microseismic array performances: case study of a deep metal mine monitoring network[END_REF].

Geomechanical numerical modelling

In addition to field monitoring and in order to evaluate strain and stress changes at the scale of the entire block 1250, an elasto-plastic, 3D continuous, mine-wide numerical model has been set up and run using a finite difference code. The numerical model simulates the exact mining sequence followed in block 1250 between February 2015 and December 2016. This corresponds to a total of 52 extracted sub-stopes, simulated in 52 equivalent model steps. At each model step, the numerical model estimates quasi-static (i.e. at the equilibrium) strain and stress changes due to mining, discarding short-term temporal effects, such as dynamic loading due to blasting.

Geometry, discretization, initial and boundary conditions

The model reproduces the whole Lappberget orebody (Figure 5), which has been constructed in order to be as accurate as possible within the area of interest (i.e. block 1250). Elements considered in the model are the ore, the weak and very weak zones (Figure 5b), as well as mine galleries and stopes within block 1250 (Figure 5a). In addition, shallower mining areas of Lappberget orebody, which extend from -578 m down to -1088 m, have also been included in the model (Figure 5 on the left), to account for their influence on the local stress field in block 1250. These areas have been approximated to cuboids whose volume is roughly equal to the excavated rock volume.

Model mesh has been built at varying degrees of details, with a high resolution (i.e. a small size) within the area of interest (maximum mesh size of 1 m) and being coarser (i.e. larger) further away (maximum mesh size of 20 m). The final 3D volumetric mesh consists of more than 13.3 million elements.

Model boundaries have been placed far enough (about 700 m) from excavations within block 1250 to avoid boundary effects, both in horizontal and vertical directions. In addition, null normal displacement conditions were assigned to laterals and lower boundaries.

Prior to simulating mining excavations, the model has been consolidated by initializing the load due to the overburden and the virgin stress state. This has been done by introducing the stress gradient reported in Table 3 and already discussed in Section 3.3. Moreover, 14 additional steps are executed in order to: (i) excavate and then backfill with paste the upper levels and (ii) excavate stopes and galleries mined in block 1250 before February 2015, for a total of 13 sub-stopes and a large volume of galleries. Then follow the 52 steps which simulate excavations performed in block 1250 between February 2015 and December 2016.

Constitutive laws and rock mass properties

Geomechanical parameters used for the numerical model are reported in Table 4. The unconfined compressive strength (UCS) of the intact rock, the Hoek-Brown material constant (mi) and the Geological Strength Index (GSI) were selected for each geological unit, based on rock mass types, structures and discontinuities. The elastic material properties, namely the Young modulus (E) and the Poisson ratio (ν), were determined choosing mean values from biaxial tests performed on rock samples (Table 1) and paste-fill. In the previous formulations, we assumed a disturbance factor (D) equals to 0 as blasting procedure in Garpenberg is accurately designed and controlled, such that the damage to surrounding rock mass is minimal [START_REF] Hoek | Hoek-Brown failure criterion -2002 edition[END_REF].

Assuming that neither thermal, nor hydraulic effects occur, rock masses in the proposed numerical model were modelled assuming purely mechanical constitutive laws. For very stiff rock masses as the orebody in Lappberget, a brittle behavior in the post-failure phase can be expected.

According to Hoek and Brown [START_REF] Hoek | Practical estimates of rock mass strength[END_REF], this type of good quality rocks deviate from the elastic behavior for higher stresses compared to soft rocks but, once the peak-stress reached, rock strength decreases dramatically and fractures occur without any prior plastic strain. To model this behavior, Souley et al. [START_REF] Souley | Numerical investigation of the development of the excavation damaged zone around a deep polymetallic ore mine[END_REF] developed a non-linear constitutive model which modifies the Hoek and Brown criterion for taking into account the brittle-ductile transition in the post-peak phase. The authors applied the proposed model to the case of Garpenberg mine, showing a significant improvement in the prediction of strain and plastic zone localizations around simulated excavations than a classical Hoek and Brown model. For this reason, in the present study, we adopt the constitutive law proposed by Souley et al. [START_REF] Souley | Numerical investigation of the development of the excavation damaged zone around a deep polymetallic ore mine[END_REF] to model the mechanical behavior of the orebody. In contrast, limestone, weak zones and very weak zones, which are softer than the orebody, were modelled considering a perfectly plastic behavior with a Hoek-Brown parabolic failure criterion. Finally, a linear elastic behavior was assumed for the paste. Several tests based on smaller scale models were realized to evaluate mechanical effects of the paste fill. Results show that stress load within the paste directly depends on stope walls (i.e. the ore) convergence: the stiffer the orebody, the smallest the load in the paste fill. For this reason and considering that the orebody in Garpenberg is characterized by stiff properties, the influence of the stress field on the paste could be neglected. This justify the assumption of a linear elastic behavior for the paste, instead of using more complex constitutive models. Moreover, due to the low Young modulus of the paste, the introduction of plasticity would result in computational problems (i.e. bad geometries) due to large strains.

Defining model outputs at seismic event hypocenters

In order to compare seismic data with geomechanical model outputs, seismic active regions have been selected within the numerical model, based on microseismic events hypocenters. To do so, and in order to account for errors in seismic events localization (on average about 15 m), as well as for numerical model uncertainties, we defined sub-volumes within the whole model, that have the shape of 10 m-radius spheres centered on events hypocenters (Figure 6). The entire selected spheres sub-volume is considered as a new smaller volume of interest with respect to the whole 1250 block.

Selecting average or cumulative values of model outputs at each modelling step, it is possible to follow temporal variations of model results within the spheres, looking for differences between seismically quiet and active periods. At the same time, temporal variation of model parameters within the spheres can be compared with that of seismic variables, to look for correlations.

Identification of different rock mass responses to mining 6.1 Overview of observed seismic activity and strain changes

During the analyzed period, more than 750 microseismic events were located around mine galleries in block 1250 (Figure 7a), with moment magnitudes ranging between -2 and 0.8 [START_REF] Santis | Impact of geological heterogeneities on induced-seismicity in a deep sublevel stoping mine[END_REF]. The observed magnitude values are rather small if compared with other hard-rock mines at similar depths [START_REF] Gibowicz | Scaling relations for seismic events induced by mining[END_REF][START_REF] Lizurek | Mining induced seismic event on an inactive fault[END_REF][START_REF] Nuannin | Inverse correlation between induced seismicity and b-value, observed in the Zingruvan Mine, Sweden[END_REF]. No damaging seismic event (e.g. rockbursts) has been observed during the analyzed period, even if some small damage started to be identified within the study area in 2016, when we also observe an overall increase of the seismic rate (Figure 7a).

As already pointed out by De Santis et al. [START_REF] Santis | Impact of geological heterogeneities on induced-seismicity in a deep sublevel stoping mine[END_REF], two main clusters have been identified during the studied period (Figure 8): the central cluster (CC, in blue in Figure 8) located in the main production area, around Stope 13, and the right cluster (RC, in violet in Figure 8), located in the eastern area of block 1250, in coincidence with the major weak talc-schist zone. Events located outside of these clusters represent only about the 17% of the entire seismicity catalogue (gray dots in Figure 8b andc).

The recorded induced seismicity appears to be strongly influenced by mine production, even if microseismic events are more related with blast locations than to blasted volumes [START_REF] Santis | Impact of geological heterogeneities on induced-seismicity in a deep sublevel stoping mine[END_REF]. Indeed, throughout the study period, six major seismic sequences have been identified, which are characterized by significant increases of seismicity rate (Figure 7a). Out of six seismic sequences, five are observed in coincidence with the occurrence of production blasts in Stope 13 (Figure 7a, b), during its final mining stages. As reported in Table 5 and in Figure 7a, these blasts are characterized by a wide range of extracted rock mass volumes and blast charges. However, the number of seismic events is not proportional neither to the extracted volumes (Figure 7a and Table 5) nor to the amount of explosive (Table 5), for any of the five seismic sequences directly triggered by excavations.

On the other hand, during the same analyzed period, we observe a large number of strain shifts (Figure 9a, b), which are often not accompanied by significant increase of seismic rate. Moreover, of the total 19 strain shifts, 17 are observed in coincidence with the occurrence of production blasts (Figure 9a,b). These observations indicate that strain changes are strongly related to nearby production, where most of the stopes have been extracted inducing mainly aseismic deformations within the surrounding rock masses. However, strain shifts intensity is not proportional neither to the volume of extracted rock mass, nor to the distance from excavations (Table 6).

The observed poor proportionality between strain changes and microseismic activity with respect to location and extracted rock mass volumes during blasts, highlights that the rock mass response to mining in the study area is not solely related to the immediate stress change induced by excavations and that additional features influence its pattern.

Mechanisms driving seismicity are discussed in detail in the following sections, considering both seismic and aseismic phenomena, and using numerical modelling results as an aid for data interpretation.

Local seismicity induced by mining

Until the beginning of May 2016, the rock mass presents a weak seismic response to mining.

Indeed, despite the large number of sub-stopes extracted during this period (34 sub-stopes excavated out of 52 total sub-stopes), the cumulative curve of microseismic events exhibits mainly a constant slope (Figure 7a and Figure 8a). Seismic rate is punctually increased by the occurrence of some production blasts in Stope 13 (Figure 7a), even if the resulting events are few (see sequences 1, 2 and 3 in Table 5). Seismicity in this first period appears to be mostly a local and temporally short response to nearby production. Indeed, as reported in Figure 8b, events are mainly localized within the CC, thus, in coincidence with the most active production zone. Within the same period, the RC is not very seismically active, with less than 30 events localized in this area (violet dots in Figure 8b).

The local behavior of the rock mass response in this first period is confirmed by the stress redistribution retrieved from numerical modelling. This can be seen in Figure 10, which reports the variation in deviatoric stress (q) between consecutive model steps, namely between steps 10 and 11, which correspond to shift 4 and 5 in Table 6, respectively. The deviatoric stress, or Von Mises equivalent stress, is written as:

= 1 2 - + - + - ! 4
where σ1, σ2, and σ3 are the major, the intermediate and the minor principal stress, respectively.

Step 11 of the numerical model corresponds with a production blast in Stope 13 (whose location is depicted by a star in Figure 10), which also resulted in seismic sequence 1 (Table 5). Warm colors (from yellow to red) in Figure 10 highlight model zones with Δq > 0, thus, the areas to which stresses are mostly transferred at Step 11 in response to mining in Stope 13. Overall, the excavation presents a radius of influence of about 15 m around the blasted area, indicating that stress transfer acts mainly at local scale.

Remote seismicity induced by mining

As visible in Figure 8a, the seismic rock mass response is intensified starting from May 2016, when the cumulative curve of microseismic events presents a stepwise trend both for CC and RC, indicating rapid seismic rate changes. During this period, three seismic sequences take place (sequences 4, 5 and 6). Contrary to sequence 4, which is not related to production, the other two are coincident with the last two production blasts in Stope 13 (see Figure 7b). These excavations had the potential, on one hand, to induce an intense seismic activity close to production area (i.e. in the CC) and, on the other hand, to remotely trigger seismicity in the RC, at more than 80 m distance from excavations (Figure 8a andc).

Before the occurrence of seismic sequences 5 and 6, Stope 13 was almost entirely mined and backfilled with paste, leaving only the last two sub-stopes 5 and 6 (see Figure 7b) acting as pillars.

Here large stresses are redistributed and concentrated due to the coupled bottom-up and top-down sequence chosen for Stope 13. Indeed, in this zone (indicated by an arrow in Figure 10b), the deviatoric stress computed by numerical modelling reaches more than 60 MPa immediately prior to its excavation, which means an increase of more than 5 times with respect to its initial value.

Consequently, mining of these final blocks of Stope 13 results in large stress changes. The process of stress redistribution acts, then, at larger scales, influencing the local stress field in the RC area, where seismicity occurs (Figure 8a,c).

Influence of stress transfer and geological heterogeneities on remote seismicity

To better understand the mechanism of stress transfer toward RC area during sequences 5 and 6, we analyzed the temporal evolution of stresses within seismic active regions in the numerical model. This was done by determining mean deviatoric stresses at each model step within the spheres centered at microseismic events hypocenters (see Section 5.3 and Figure 6) and distinguishing spheres belonging to CC from those belonging to RC. Results are reported in Figure 11a and compared with CC and RC seismicity (Figure 11b). Three distinct phases can be identified in Figure 11a. At the beginning of the analyzed period (Phase 1), CC and RC regions present similar rates of stress increase. Then, during Phase 2, the mean deviatoric stress remains almost constant within CC at the highest level, while it increases significantly in the RC. Finally, during Phase 3, in coincidence with the two last stages of Stope 13 exploitation, stress in CC drops dramatically until the end of the study period, while stress within RC keeps rising.

Phase 1 and 2 are characterized by very low levels of seismic activity within RC, while seismicity is punctually and locally enhanced in CC, due to production in Stope 13 (Figure 11b). Remote seismicity in RC occurs during Phase 3, in coincidence with the destressing of the rock mass in the major production area (i.e. CC). This indicates that, in addition to the large stress release due to final production stages in Stope 13, the remote seismicity within RC is triggered when the CC is not able to sustain large loads, and stresses are preferentially transferred toward the RC area. This is confirmed by the analysis of plastic deformations predicted by numerical modelling within the spheres. Indeed, the percentage of plastic zones with respect to the total number of zones within CC spheres reaches the 39% and the 43% in coincidence with the occurrence of seismic sequences 5 and 6, respectively.

On the contrary, during the same seismic sequences, plasticity within RC spheres only represents the 9% and the 12% of the total number of zones.

In addition to stress transfer, geological characteristics within RC area locally influenced stress field distribution and fracture propagation, as demonstrated by seismic source parameters analysis [START_REF] Santis | Impact of geological heterogeneities on induced-seismicity in a deep sublevel stoping mine[END_REF]. Indeed, RC events are characterized by larger stress drops [START_REF] Eshelby | The determination of the elastic field of an ellipsoidal inclusion, and related problems[END_REF], as well as by smaller fracture dimensions, compared to CC seismicity. This trend has been attributed to geological heterogeneities of RC area, where stiff rock masses (i.e. ore and limestone) are interbedded with weak plastic lenses (i.e. talc-schists). As a result, stress in the RC is non-homogeneously distributed and large fractures (i.e. large magnitude events) are impeded by the presence of weak lenses at direct contact with the breaking stiff rock mass (i.e. stiffer lenses).

Seismicity triggered by aseismic creep

The occurrence of seismicity driven by aseismic creep in Lappberget orebody has been extensively studied in a recent work by Kinscher et al. [START_REF] Kinscher | Seismic repeaters linked to weak rock-mass creep in deep excavation mining[END_REF], who analyzed seismicity of the study area by means of cross correlation cluster analysis looking for the occurrence of multiplet families (i.e.

groups of seismic events characterized by highly similar waveforms). The authors demonstrate that more than the half of Lappberget events, within the period 2015-2017, can be classified into different multiplet families with highly coherent (> 0.9) waveform similarity. Families appear to be active over weeks and up to several months and are located both in the CC and in the RC.

Observations demonstrate that multiplets found in Lappberget can be interpreted as seismic repeaters, that are the proof of a repeating rupture process of the same seismic source loaded by creep in surrounding areas. Creep in Lappberget is most probably occurring within weak talc-schist lenses which load the interbedded stiff rocks, where seismicity occurs once the induced stress exceeds the point of material failure.

Indications of seismicity driven by aseismic creep can be seen in the spatiotemporal behaviors of some seismic sequences analyzed in the present study. Indeed, we identified the occurrence of a seismic sequence not related to mine production (sequence 4). It took place at the beginning of the strong seismic rock mass response period (Figure 8a) and is characterized by events mainly localized within the CC (Figure 12a). One may assume that this sequence was induced by a large magnitude event, through quasi-static stress transfer, in an after-shock like effect. However, no main shock (i.e. larger magnitude event) is observed at the beginning of the sequence (Figure 12b). In addition, sequence 4 (Figure 12b), as well as sequences 2, 3 and 6 (Figure 13), are all characterized by delayed reactivations of seismic rate, which are not driven neither by new blasts, nor by large magnitude events. Seismicity during the observed delayed reactivations do not occurs at same location as the initial activity (e.g. Figure 12a), indicating that a mechanism acting at larger scales is involved. These observations suggest that seismicity is not driven by a cascade-like effect of earthquakes which triggers additional events, thus, a model driven by aseismic slip, as proposed by Kinscher et al. [START_REF] Kinscher | Seismic repeaters linked to weak rock-mass creep in deep excavation mining[END_REF],

seems to be more appropriate.

Coupling between seismic and aseismic responses

Creep can be observed in strain measurements (e.g. Figure 9c,d). Indeed, after the sudden strain shift observed in coincidence with blasting, strains do not stabilize quickly in a steady state. A progressive strain drift has been observed for the majority of the recorded strain shifts, indicating that creep (i.e. aseismic slip) is induced by mining. As a result, stress field redistribution and consequent deformations are not immediate but a long-lasting process over time.

Moreover, when comparing temporal behaviors of microseismic activity and measured strains, similarities are visible (e.g. Figure 14), implying that seismic activity is decaying proportionally to the decaying rate of induced deformations. This is particularly visible in Figure 14a which reports temporal trends of seismic activity and measured strains at PH cell during seismic sequence 4.

Seismicity has a temporal behavior which is nicely reshaping that of measured strains, even for the delayed reactivation which occurs at the same time for seismic activity and measured strains.

The observed proportionality between seismicity rate and temporal evolution of measured strains is a strong evidence for the occurrence of coupled mechanisms of seismic and aseismic slip driven by creep, confirming results on seismic repeaters by Kinscher et al. [START_REF] Kinscher | Seismic repeaters linked to weak rock-mass creep in deep excavation mining[END_REF]. Indeed, as proposed by other authors [START_REF] Perfettini | Postseismic relaxation driven by brittle creep: A possible mechanism to reconcile geodetic measurements and the decay rate of aftershocks, application to the Chi-Chi earthquake, Taiwan[END_REF][START_REF] Bourouis | Evidence for coupled seismic and aseismic fault slip during water injection in the geothermal site of Soultz (France), and implications for seismogenic transients[END_REF] some faults, or some segments of faults, obey a velocity-strengthening frictional law which leads to a stable silent creep (i.e. slip without seismic activity). Ruptures (i.e. seismicity) occur along locked segments of the faults which are gradually charged by the aseismic creep around them. Once earthquakes are triggered on the seismic parts of the fault, the aftershocks decay rate is driven by creep, thus, seismicity decays proportionally to the slip rate.

Changes in seismic regime

As demonstrated by the occurrence of the non-blast related seismic sequence (sequence 4), and in agreement with findings by Kinscher et al. [START_REF] Kinscher | Seismic repeaters linked to weak rock-mass creep in deep excavation mining[END_REF], coupled mechanisms of seismic and aseismic slip appear to be intensified during the period of strong rock mass response to mining, thus, during the final mining stages in Stope 13. This change in seismic regime is also validated by numerical modelling results, particularly when comparing seismic moment (M0) of microseismic events with the volume of plastic zones computed by modelling. This is shown in Figure 15 On the contrary, in coincidence with sequence 4, seismic moment presents a significant increase which is not followed by an equal increment in plastic volume. Therefore, starting from sequence 4, the two curves show different trends, indicating that numerical model is not anymore capable to account for changes in seismic regime. This means that mechanisms driving seismicity become more complex during the period of strong rock mass response to mining, probably due to the influence of geological characteristics and aseismic creep phenomena.

Conclusions and outlooks

In this paper we investigated rock mass behaviors in Garpenberg mine by combining the analysis of geophysical and geotechnical data with geomechanical numerical modelling. Results, which have been interpreted considering mining operations, as well as local geological characteristics, significantly enhanced our understanding of the rock mass response to mining, highlighting complex behaviors. Indeed, at least three concomitant mechanisms appear driving seismicity in Lappberget orebody. On one hand, microseismic activity is directly induced by immediate stress changes due to mining. As a result, seismic events in the central area of the mine (i.e. CC) show strong spatiotemporal correlations with production. On the other hand, seismicity is as well triggered by stress transfer from the main production area (i.e. CC) toward the eastern side (i.e. RC), where local lithological heterogeneities strongly influence seismic activity. As a result, RC seismicity is spatially remote from excavations, even being temporally coincident with blasting, and characterized by significant different source parameters with respect to CC events. Finally, a third overlapping mechanism seems driving seismicity in both CC and RC. It is characterized by a slower response, persistent after the blasts, and responsible for the delayed reactivation of seismic rate observed in most of the analyzed seismic sequences. This latter component of seismicity might be associated to creep-like phenomena induced by mining within soft rocks (i.e. talc-schists), that slowly load surrounding seismic asperities bringing them to rupture (i.e. seismicity).

If seismic and aseismic behaviors are generally approached separately with respect to safety issues and hazard assessment in mines, our study demonstrates that time-dependent strains can also be one of the mechanisms driving seismicity. As a result, the aseismic component of the rock mass response to mining should be considered when assessing seismic hazard.

Deeper investigations will be needed in order to: (i) better constrain geomechanical and geological origin of seismic repeaters, (ii) characterize and quantify short-and long-term post-blast creep processes in space and time, as well as (iii) their influence on fracture propagation within seismic asperities. This could be done, on one hand, by performing and analyzing local highresolution strain measurements which could give essential information about transient creep from weak rocks, as well as coseismic strain from repeaters. On the other hand, future seismic data should be analyzed following the methodology proposed by Kinscher et al. [START_REF] Kinscher | Seismic repeaters linked to weak rock-mass creep in deep excavation mining[END_REF] based on template matching techniques, which allow characterizing the nature of seismic repeaters. In addition, dimension and geo-lithological composition of seismic asperities should be examined in future studies by means of drill logs data and geological inspections to be performed in some seismic repeater prone zones. All these data and analyses will be of paramount importance for the conception of an advance

Figures and figure captions

Finally

  , the UCS and mi values of the intact rock and the GSI values of the rock mass were used to calculate the Hoek-Brown constants m and s based on the following empirical relations[START_REF] Hoek | Hoek-Brown failure criterion -2002 edition[END_REF]:

  which reports M0 cumulated over time for all microseismic events recorded throughout the study period with the volume of plastic zones cumulated between each modelled mining step within spheres sub-volume of the numerical model.Until the occurrence of sequence 4, cumulative curves of seismic moment and plastic volume present similar trends, indicating comparable behaviors of the rock mass response between direct measurements (i.e. recorded seismicity) and numerical model predictions. In other words, model results and observed seismic activity respond similarly to mining excavations in this first analyzed period. As no time-dependent constitutive laws (i.e. creep) have been considered in the numerical model, model outputs variability is solely driven by the quasi-static effect of excavations and by the influence of the modelled geological properties. As a result, the observed similarity between seismic moment and plastic volume trends indicates that seismicity in this first period is mostly driven by quasi-static stress changes induced by mining.

  geomechanical numerical model able to reproduce mechanisms triggering seismicity at Garpenberg mine. The model should account for (i) the induced seismicity linked with quasi-static stress changes due to mining, (ii) the triggered seismicity due to local geological heterogeneities and stress transfer at large distances and (iii) the seismicity driven be aseismic deformations due to post-blast creep phenomena. A well calibrated geomechanical model representative of the main physical processes involved, combined with improved in situ data analysis, will allow studying aseismic mechanisms at larger scales and constraining the mechanical coupling between creep and seismic ruptures.

Figure 1 -

 1 Figure 1 -Orebody, weakness zones and galleries at different depths in block 1250. The figure shows horizontal maps at each of the seven levels of block 1250. Numbers indicate depth (in meters) below ground surface.

Figure 2 -

 2 Figure 2 -Mining sequence in block 1250 of Lappberget. The figure shows how excavation progressed between November 2015 (on the left) and December 2016 (on the right). Red and orange blocks represent excavated sub-stopes. The two arrows illustrate the simultaneous top-down and bottom-up production of Stope 13 (in orange).

Figure 3 -

 3 Figure 3 -Stereographic representation of principal stress orientation. H1 measurements are reported on the left, while results for H2 are on the right. Stress orientations are reported with respect to drifts direction (0° ≡ Y axis). True North direction is also depicted in the image (after Bouffier et al., 2015). Note that each data point is

Figure 4 -

 4 Figure 4 -Geophysical and geotechnical monitoring network displayed on a horizontal (left) and a vertical (right) cross section of Block 1250.

Figure 5 -

 5 Figure 5 -Numerical model geometry. The entire model, together with its boundaries, is reported on the left. The orebody profile is displayed in yellow, while gray areas are assigned to limestone. Upper levels refer to shallower mining areas of Lappberget orebody. Note that, for a better visualization, the limestone surrounding orebody and mined areas has been removed from the left figure. The close-up on the right show the geometry of galleries and stopes in block 1250 (a), as well as that of weak and very weak zones (b) in green and red, respectively.

Figure 6 -

 6 Figure 6 -Selection of seismic active regions within the numerical model. This sub-volume is identified by 10 mradius spheres centered at microseismic events hypocenters. Grey areas represent galleries and stopes in block 1250, as built in the numerical model.

Figure 7 -

 7 Figure 7 -Microseismic activity and production blasts. (a) Number of microseismic events (MSE) per hour (in red) and cumulative number of events (in black). Dashed lines indicate the occurrence of some seismic sequences. Production blasts which triggered the seismic sequences are reported by circles colored and sized according to the volume of extracted rock mass. (b) Positions of mined sub-stopes (in red) in Stope 13 during seismic sequences 1, 2, 3, 5 and 6. Gray blocs indicate sub-stopes mined and refilled with paste.

Figure 8 -

 8 Figure 8 -Space-time characteristics of microseismic activity. (a) Cumulative number of microseismic events separated between Central Cluster (CC) and Right Cluster (RC). Stars and dashed lines indicate seismic sequences numbered as in Figure 7. (b) Localization of microseismic events during the period of weak rock mass response. Gray dots indicate events located outside CC and RC. (c) The same as in (b) but for the period of strong rock mass response to mining.

Figure 9 -

 9 Figure 9 -Strain measurements at PD (a) and PH (b) cells over the whole analyzed period and during two different strain shifts induced by production blasts (c and d). Colored lines in the figures represent the measure at each gauge of the cells. Dashed gray lines in (a) and (b) indicate significative strain changes occurred in coincidence with production blasts. Red lines in (a) and (b) refer to strain changes non-related to production. Gray areas in (a) and (b) highlight periods where the system was out of order.

Figure 10 -

 10 Figure 10 -Stress changes retrieved by numerical modelling. (a) Difference in deviatoric stress between subsequent model steps along a horizontal section in block 1250. The star indicates the position of the production blast at model Step 11. (b) Contour of deviatoric stress along a vertical section for the Step 25 of the numerical model. The arrow highlights the last exploited area in Stope 13. White areas in (a) and (b) depict mined stopes and galleries. Numbers within white areas indicate stope's names, while numbers on the right of figure (b) refer to depths.

Figure 11 -

 11 Figure 11 -Temporal trend of stress state in seismogenic regions retrieved by numerical modelling (a) compared with temporal trend of microseismic activity (b). (a) Average deviatoric stress at each model step

Figure 12 -

 12 Figure 12 -Spatiotemporal characteristics of seismic sequence 4. (a) Localization of microseismic events during sequence 4, analyzed along 16 days. (b) Cumulative number of microseismic events (MSE) (left-hand axis) and cumulative seismic moment (M0) (right-hand axis) over 16 days. Yellow dots in (a) and (b) indicate events occurred at the beginning of the sequence, while green dots are the events occurred during the reactivation of the sequence.

Figure 13 -

 13 Figure 13 -Temporal trend of some seismic sequences. The charts report the cumulative number of microseismic events (left-hand axis) and the cumulative seismic moment (right-hand axis) during sequence 2 (b), sequence 3 (a) and sequence 6 (c). For this latter, events are reported separately for central cluster (CC) and right cluster (RC). Note that temporal intervals are different per each sequence.

Figure 14 -

 14 Figure 14 -Comparison between seismicity and strain measurements. (a) Cumulative number of microseismic events (left-hand axis) during seismic sequence 4 and measured strains (right-hand axis) at PH cell in the same temporal interval. (b) The same as in (a), but during seismic sequence 5 and considering strains measured at PD cell.

Figure 15 -

 15 Figure 15 -Comparison between cumulative seismic moment (M0) (in black) and cumulative plastic volume retrieved by numerical model (in red). Plastic volume is computed considering only model zones within the spheres sub-volume as defined in Figure 6. Gray lines indicate seismic sequences occurrence.

Acknowledgements

Authors would like to thank Boliden engineers Shahram Mozaffari and Anders Nyström for their scientific and technical collaboration during the project. We also thank Ineris and Boliden technical staff for equipment installation and maintenance, as well as for data management.

Tables and tables captions