Using passive and active seismic data to better understand

Using passive and active seismic data to better understand the stress conditions in a Canadian mine

April 2016

Copyright © Institute of Mine Seismology 2016

From Hasegawa et al. 1989

Sources of Mine Seismicity


Seismic Wave Propagation












































Relative Velocity Changes

Aim is to see how changes in velocities (directly related to changes in stress) can be correlated with mining.

Once we know this we can use future observations of velocity (stress) changes to help the mine with understanding the state of the rockmass.


Wave Propagation


Seismic Events

4502 events in 3 years (10 trigger or more)


Seismic Source


Moment Tensor


Moment Tensor


Moment Tensor


Moment Tensor Decomposition


Moment Tensor Decomposition


Seismic Events

4502 events in 3 years (10 trigger or more)


Moment Tensors

3504 events with MT


Moment Tensors – slip events

1583 events with large DC component


Hemlo Mine B-Zone Stress Conditions

After Coulson, 2009


Principle Stress Trend (°)

Plunge (°)

Magnitude (MPa/ metre)

σ1 358 10 0.0437

σ2 093 28 0.0299

σ3 250 60 0.0214

After Coulson, 2009

B-Zone Stress Conditions


Moment Tensors – Away from Mining


Inferred Stress Directions


C-zone

This is the adjacent ore-body so stress conditions were extrapolated from the known B-zone stress conditions.But the C-zone ore-body has been rotated on an adjacent fold limb (Muir 1997).


Moment Tensor - C-zone


Stress Inversion C-zone

Region A Region B Region C

Model 1 σ1

Seismic Proxy(P-axis)




Model 1 σ2

Seismic Proxy(B-axis)




Model 1 σ3

Seismic Proxy(T-axis)




Model 2 σ1

Seismic Proxy(P-axis)




Model 2 σ2

Seismic Proxy(B-axis)




Model 2 σ3

Seismic Proxy(T-axis)


Seismicity vs Modelling

We have compared modelling parameters with seismic information● maximum shear stress, orientation of principal axes vs● source locations and mechanisms

This is somewhat simplistic ● regions of maximum shear stress provided by elastic model

may yield before the analysed seismicity is recorded. ● seismic events can be associated with specific weaknesses,

which may locate outside the regions of maximum shear stress.

● P , B and T axes of source mechanisms represent proxies of maximum principal stresses provided the strength of the rock mass is isotropic and homogeneous. These axes can deviate from the principal stresses significantly for preferred planes of weakness.


Modelling Seismicity

Original idea was from M.G.D. Salamon (1993) and it was elaborated on by A.M. Linkov (2005, 2013).

We implemented a variant of this (Malovichko, Basson, 2014).

It forecasts seismic events associated with disturbances of the stress field by mining.

Requires information about in situ stress and failure criteria for the rock mass, joint sets and specific 3D surfaces (e.g. faults).


The modelled seismicity can be compared with the observed data in a rigorous way using two fundamental characteristics: ● amount of co seismic deformation (seismic potency)● geometry of co seismic deformation (source mechanisms)

Calculate two parameters for each cell namely:● ratio of modelled and observed cumulative potencies,● minimum rotation angle between the average source

mechanisms of modelled and observed seismic events.




Observed

East South

Model 1

Jul 2013

Nov 2013

Mar 2014

Jul 2014



Observed

East South

Model 2

Jul 2013

Nov 2013

Mar 2014

Jul 2014



Observed

East South

Model 1



Observed

East South

Model 2



Cumulative Potency



Comparison with model 1



Comparison with model 2



Model RMSD (log(Pobs

/Pmod

)) Median misorientation angle[deg]

1 0.98 79

2 0.96 53


Active Seismic Source

Part of the Ultra-Deep Mining Network projects

Hosted by Barrick Williams Mine, Hemlo


Seismic Wave Velocities

In rock seismic wave velocities depend on:● Young's modulus, Poisson's ratio and density of intact rock in 3D● Fractures (density, orientation and wet/dry)● Stresses (amplitude and orientation)

Only fractures and stresses change in response to mining


Seismic Wave Velocities

Passive seismic tomography can yield seismic velocities, but poor resolution (few %) due to ● Unknown source locations● Non-repeating signals

We can get much higher resolution (0.01%) with a controlled repeating seismic source


Seismic Source


Active Seismic Source


Radiation Patterns


Radiation Patterns with Attenuation


Experimental Design


Active Source Signal

Signal recorded by reference sensor 0.5 m away



Signals as the slug bounces



Signal recorded by sensor 158 m away

S-wave arrival on the sensor

Reference pulse


Resolution

For a signal of dominant frequency f0 and signal-to-noise ratio SNR,

the smallest measurable time shift determined by cross-correlation is

δt ≥ 1/(2πf0SNR)



SNR ~ 3

This is equivalent to about a 0.1% velocity change


Original Signal


Stacked Signal





Aim is to see how changes in velocities (directly related to changes in stress) can be correlated with mining.

Once we know this we can use future observations of velocity (stress) changes to help the mine with understanding the state of the rockmass.


Questions

Questions?

Documents

Using passive and active seismic data to better understand