Mining Rock Mass Models: 3-D evaluation of the geotechnical
environment for optimal project design and planning
by Peter Jenkins, Gary Dempers & Dr Clive Seymour, Dempers & Seymour Pty Ltd Perth Australia
INTRODUCTION
At the scale of mining projects, rock
masses are inhomogenous and often
extremely variable. A large volume of
data is usually collected during
geotechnical feasibility studies but
rarely is the rock mass variability
effectively established and viewed
spatially in an adequate three
dimensional model.
The concept of the Mining Rock
Mass Model (MRMM) has been
specifically developed to improve the
appreciation of rock mass conditions
across the mine project area. A
MRMM comprises various 3-D
models of logged values or calculated rock mass parameters that
are analogous to a resource block
model in the way that they are
viewed and incorporated into the
mine feasibility study and planning
process. These models facilitate a
robust understanding of rock mass
conditions and their variation across
the project area, as the example in
Figure 1 shows.
An initial MRMM can be created
using data collected from exploration
drill core, providing early indications
of the geotechnical environment and
justification for decisions that shape
project development. Additional data
collection from infill drilling, geotechnical drill holes and other
sources are used to update and reevaluate the MRMM as project
studies progress. Therefore, these
models can add value throughout the
project and mine life.
This article outlines the MRMM
methodology and illustrates the
application of the 3-D models
created with examples from both
underground and open pit projects.
methodology is presented here with
more emphasis placed on the
potential of the MRMM to add value
in project development.
Although primarily consisting of
geotechnical drill core logging, other
forms of data may be used in the
MRMM database. For example,
underground geotechnical mapping
and structural data can also be
incorporated into the database and
viewed against the logged data to
assist in the modelling and
interrogation process.
Domain Logging
Drill hole logging uses the domain
logging technique as described by
Dempers (1991). Selecting the
geotechnical intervals or domains is
the first step in the logging process.
The domains can be many metres in
length or less than a metre and they
are determined by major lithological
boundaries, which are then further
subdivided according to significant
changes in geotechnical characteristics such as strength, RQD (Rock
Quality Designation), the condition of
discontinuities, their frequency and
orientation, etc.
The logging method highlights weak,
broken zones, structures and other
features that are geotechnically
significant. Correlation of these in the
modelling process is facilitated by
the use of a specific code that is
recorded during logging for different
types of features, such as faults,
shears or intense zones of fracturing,
vuggy or deformable ground, discing
and other project specific mineral or
rock mass alteration types.
Importantly, the logging scheme
ensures that sufficient data is
collected within each domain (logged
interval) to allow a rating determination or ranking for all of the
major rock mass classification
systems, i.e. Rock Mass Rating
(RMR) and its derivatives, Geological
Strength Index (GSI) and Rock
Tunnelling Quality Index (Q). As
such, the codes used for data
collection are based on Barton et al
(1974) and Laubscher (1990).
Data validation ensures consistency
of interpretation between different
logging personnel and is vital, as
poor data input would lead to an
RMR
<20
20 - 40
40 - 50
50 - 60
60 - 80
>80
Very Poor
Poor
Poor to Fair
Fair to Good
Good
Very Good
MRMM METHODOLOGY
Establishing a MRMM can be broken
down into the following steps:
•
Data collection
•
Data validation
Figure
1
•
MRMM construction
•
MRMM interrogation
This process has been detailed
previously by Seymour et al (2007),
hence only an overview of the
Page 1 of 7
Figure 1 Plan and section views through the MRMM for a proposed block cave
infrastructure below existing mine workings (blue); shows the trace of some of the logged
boreholes used to build the model with calculated Rock Mass Rating (RMR) values
unreliable model output. Core
photographs of the logged holes are
retained for this purpose and the
validation process may also require
some check logging.
Oxide
Model Construction
The logged data, calculated parameters and rock mass rating values
are converted into block models
using the resource estimation
routines in standard mining software
packages with geological modelling
capabilities e.g. Datamine, Surpac
and Gemcom. Data is loaded into the
software application as a drillhole
“assay” table and then composited
into regular intervals within each
logged domain.
Overall model dimensions and block
sizes are project specific and
dependent on the main geotechnical
controls (lithology, structure, etc.). A
massive deposit could have a larger
block size compared to a thin vein
deposit. The composited data is then
used to estimate block values using
the resource evaluation modules
(kriging, inverse distance, etc.) within
the software package.
The block model estimation process
should be constrained by the likely
controls on the rock mass. These
constraints are project specific and
may include weathering profiles,
lithology, foliation, bedding, major
structural
orientation
or
other
features. This part of the process
requires the development of an
understanding of the controls on rock
mass quality for the project and may
involve a number of iterations.
Weathering profiles and lithology are
usually the primary constraints, as
illustrated in the first pass model for
an open pit project, Figure 2, before
the geotechnical data is introduced.
Model Interrogation
Variable rock mass conditions may
be due to major geological
structures, large fault zones, areas of
closely spaced jointing, geological
structures that carry water, weak
rock, intense alteration or many other
conceivable reasons. The nature of
this variability can be identified and
visualised in the MRMM and each
distinct zone or rock mass domain
may be characterised independently
using only the composited data for
that particular unit.
In Figure 3, the composited borehole
data has been interpolated to
populate the model using estimation
envelopes elongated in the dip and
strike direction of the lithology.
Page 2 of 7
Hangingwall Felsic
Talc
Footwall Felsic
Ultramafic (between
the Talc units)
Figure 2 Initial lithological model and conceptual pit outline
Possible structure or
rock unit
Zone of Poor quality
rock due to a different
lithological unit
RMR
0 - 20
20 - 40
40 - 60
60 - 80
80 - 100
Zone of Poor quality
rock
Figure 3 Second pass cross section through the model with lithological control from
estimation envelopes
Further interrogation of the model
often reveals unique features that
may require separate additional
domains to refine the block
estimates, as illustrated in Figure 4.
Hence, it is an iterative process that
is used to develop the model and at
the same time increase the
understanding of the rock mass
quality and its variation across the
project. At each pass of the
interrogation process, additional
domains were added to the model
reflecting both structure and rock
units.
However,
the
structure
indicated in Figure 4 was flagged for
additional data collection to confirm
its persistence.
The rock mass domains or units
established during model construction are generally larger than the
core log intervals, i.e. they may
correspond with a logged domain but
more often embrace a range of
different logged domains that define
the variability within a broadly similar
rock mass domain.
A benefit of this technique is that
rock testing can then be based on
the true rock mass domain variability,
rather than just testing according to
rock type. Hence, test samples are
picked from the domains, major
structures and joint sets identified
that are relevant to the engineering
structure and its scale. After testing
has been completed, the domains
can be calibrated against test data
and observation, then directly
exported to two dimensional limit
equilibrium and three dimensional
numerical models.
The value of the interrogation
process has been realised in several
studies where the presence of major
structures, variable rock units or
zones of extremely soft rock caused
by alteration have been identified,
where previously only one rock type
was thought to be present. Figure 5
illustrates the variable make up of a
single lithological unit for another pit
project where four distinct design
rock mass domains were identified
within the unit.
Critical Parameters
Understanding the cause of the
variation in rock mass quality is very
important and the MRMM can be
used to evaluate the variable zones.
In addition to the classification
ratings (RMR, MRMR, GSI, Q etc.),
other geotechnical parameters are
also modelled and interrogation of
these models often helps in
understanding the rock mass variability. The ranges of the “critical”
parameters that are routinely interrogated in the modelling process are
given in Table 1, these being:
o Joint intensity, calculated from
RQD/Jn this represents the
structure of the rock mass and
gives a measure of block size
(McCracken and Stacey, 1989).
o Discontinuity shear strength, as
determined from micro roughness
and joint infill, representing the
frictional characteristics of the joint
wall and infill material. (McCracken
and Stacey, 1989).
o Fracture frequency (Seymour et al,
2007)
o Rock strength (Seymour et al,
2007)
Models of these parameters are
compared with each other and the
different rock mass ratings, so that
their likely influence on ground
conditions
and
behaviour
is
appreciated and can be accounted
for in project design.
An example of the variation in two of
these critical parameters in an
underground project setting are
given in the circled areas of Figures
6 and 7, which are plan views at a
central location through the proposed
cave block shown in Figure 1. The
rock strength is classified as Very
Good (UCS > 160MPa) in Figure 7
but is Poor to Fair (Jr/Ja < 2) in terms
of joint shear strength (Figure 8).
This information from the MRMM for
the project had significance for the
likely cavability and fragmentation of
the resource.
MRMM APPLICATIONS
Mining Rock Mass Models have
been created for more than fifty
different projects at various stages
and for both open pit and underPage 3 of 7
Structure?
RMR
Additional domains
0 - 20
20 - 40
Additional domains
40 - 60
Figure 4 Final estimate
with additional rock mass domains, lithologies, weathering profiles
60 - 80
- 100
and 80major
structure oriented to the dip of these features
Figure 4 Final estimate with additional rock mass domains, lithologies, weathering profiles
and major structure oriented to the dip of these features
Additional design units
added to account for poor
quality “stripes” within the
hangingwall unit
Figure 5 Variation in rock mass quality within a single lithological unit
Table 1
Classification of critical geotechnical parameters
Parameter
Very Poor
Poor
Fair
Joint Intensity (RQD/Jn)
Joint shear strength (Jr/Ja)
Good
Very Good
<4
4-8
8 - 15
15 - 25
> 25
< 0.5
0.5 – 0.75
0.75 - 2
2-3
>3
Fracture Frequency (FF/m)
> 15
3 - 15
1-3
0.3 - 1
< 0.3
Rock Strength (MPa)
< 25
25 - 50
50 - 100
100 - 160
> 160
ground minesites or where there is
interaction of both at a site. The
methodology discussed has been
refined through this experience and
is extremely robust. Sometimes the
models are created for specific
problem areas at mature sites but
undoubtedly they can add greatest
value where created early in the
project life at the concept or
feasibility stage. In this respect they
help to minimise the potential for
‘latent’ or unexpected conditions to
arise that can impact project
progression or operational viability.
However, the key attribute of the
MRMM is its ability to provide
detailed information at key locations
for project design and planning,
whilst being a repository for
geotechnical information and the
visualisation of this data. Further
Hangingwall
rock mass
High strength zone
in resource
Features associated with
known structure
Strength MPa
<25
25 - 50
50 - 100
100 - 160
> 160
Interpolated structure 1
Figure 6 MRMM showing rock strength, plan view through a
proposed block cave ore body
Interpolated structure 2
Jr/Ja
0 - 0.5
0.5 - 0.75
0.75 - 2
2-3
3-4
Figure 8 Isometric view showing interpolated structures from a search for
specific fracture characteristics
Poor to Fair joint shear
strength (Jr/Ja < 2)
Figure 7 MRMM showing joint shear strength
discussion and examples of MRMM
applications follow.
Open Pit Assessment
Conceptual open pit slopes and
infrastructure such as haul ramps
can
be
planned
with some
justification during the early design
stages by interrogating the MRMM;
and before rigorous analyses are
performed. The preliminary pit slope
angles, derived from MRMR after
Laubscher (1990), as well as other
parameters can be visualised in
three-dimensions so that the position
and design of initial pit slopes take
cognisance of poor quality zones
within the rock mass.
It must be remembered that
proposed slopes assessed in this
manner must still be rigorously
analysed. Although zones of poor
quality rock are significant, structure
is generally more important in
controlling the behaviour of a rock
mass and is usually responsible or
contributes to the majority of pit wall
failures. The location and nature of
Page 4 of 7
structure in terms of persistence, dip,
surface conditions and integrity
strongly influence pit slope stability
and hence design configurations.
Identifying structural features early in
stages of a project can be very
beneficial in that design considerations can be made that account for
structure. It is often evident in the
exploration phase of a project that
the presence of geological structures
which may impact pit design are not
well recorded (if at all), because the
focus of data collection has been
targeted towards the ore body and
not the surrounding rock mass or pit
walls.
The MRMM can be used to identify
potential structures very early on so
that they can be targeted for further
investigation. The modelling of
discrete major structures is helped
by the specific feature codes used as
well as the fracture characteristics
recorded in the geotechnical domain
logging. The MRMM database is
then interrogated to evaluate major
structures, by applying search
criteria for specific characteristics or
combinations of these, to identify
significant geotechnical structures.
Figure 8 illustrates this search and
interpretation process. The characteristics that met the search
criteria in this example were
intensely fractured core lengths
greater than 1m with highly polished
fracture surfaces. These were
features associated with existing
known structures at this prefeasibility
stage project and they were used to
interpolate and extrapolate other
similar
structures
and
their
orientations. The interpretation in this
case was carried out in tandem with
stereographic analysis of structural
measurements taken from traditional
core structure orientation methods
or, where the rock was too heavily
fractured to orientate the core, from
downhole televiewer surveys.
Data from the MRMM can be
exported to limit equilibrium and
numerical models for rigorous or
deterministic slope stability analysis
purposes,
when
these
are
undertaken.
Rock Bridge
Failure through the intact rock
bridges between structures has been
recognised as a contributing mechanism in many slope failures. Slope
stability analysis methods tend to
use different criteria for failure along
structure (e.g. Mohr-Coulomb) or
through intact rock (e.g. HoekBrown) and and their respective
strengths are usually arbitrarily
adjusted, either up or down, to allow
for rock bridge or structure. However,
a new approach has been developed
that uses fracture frequency to
determine the ratio of structure to
rock bridge expressed as a
percentage of rock bridge. This
allows a specific model for rock
bridge (rather than a generalised
approximation) to be interpreted from
the MRMM.
Figure 9 shows a fracture frequency
model (upper diagram) that has been
used to help define the modelled
rock mass units (lower diagram) and
provide the distribution of rock bridge
values for probabilistic analyses. The
analysis also uses statistical distributions from the MRMM for the other
input parameters used in the model
(UCS, GSI, cohesion, friction angle
and joint roughness condition). The
failure surfaces gen-erated by the
SLIDE limit equilibrium analysis of
this slope are shown in the lower
diagram of Figure 9.
Underground Mine Assessments
The
MRMM
construction and
interrogation techniques used for
underground projects are the same
as for open pits, although the size,
scale and area of influence for data
collection may be different. Access
development usually requires a
specific geotechnical investigation as
Fracture Frequency Rating
>15 frac/m
3 – 15 frac/m
1 – 3 frac/m
0.3 – 1 frac/m
<0.3 frac/m
Rock bridge
boundary
Lithological
boundary
FS = 1.13
PF = 17%
Figure 9 Fracture frequency model (upper diagram) that provides rock bridge
distribution for input to the SLIDE analysis of this slope (lower diagram)
Weak Faulted Zones
Q
0 - 0.1
0.1 - 1.0
1- 2
2- 4
4 - 10
> 10
Q
0 - 0.1
0.1 - 1.0
1-2
2-4
4 - 10
> 10
Section looking North
Figure 10 Q-MRMM for a decline access route
Page 5 of 7
Ore Zone
it is generally outside the area of
interest for resource definition.
Figure 10 shows a series of
geotechnical boreholes along the line
of a proposed decline to access a
narrow vein orebody beneath a deep
weathering profile. In this case a long
section MRMM was created through
these boreholes to provide a detailed
synthesis of the expected development conditions, the nature and
extent of weak faulted zones and
support requirements.
Long section MRMMs are also
created to characterise geotechnical
data for the selection of underground
stoping methods, stope sizing and
support design. These models are
typically created for the ore zone and
immediate hangingwall and footwall.
After constructing the MRMM for the
project, the data within the ore zone
and in the zones 10m either of this
are then modelled as separate
entities to create domain models for
each.
An example of a hangingwall domain
model is given in Figure 11 and
characterisations for the inividual HW
domains (as well as for the
associated ore and footwall domains)
were then used to derive stope
design parameters. Figure 12 shows
the original ore horizon model the
footwall Q-MRMM with prominent
poor quality rock mass (“hot spots”).
The hot spots were asssociated with
swelling ultramafic rock and this
diagram shows how the model was
used to avoid exposure of the
proposed stoping and development
to the areas of worst ground
conditions.
HW Domains
Fair to Good
Fair
Poor
Very Poor
Figure 11 Hangingwall domains established from a long section MRMM with
proposed stoping areas outlined
Ore horizon
model
CONCLUSIONS
Mining rock mass models can be
built at various stages of project life.
However,
greatest
benefit
to
successful
mine
design
and
continuous operation accrues when
a MRMM is constructed in the
feasibility stages of a project with
periodic
review
and
update
thereafter. The idealised sequence of
MRMM application for a project is:
•
Initial
feasibility
(or
prefeasibility) MRMM constructed
from geotechnical logging of
exploration core.
•
The variability of rock mass
conditions established in the
initial model is then used to plan
a
targeted
geotechnical
investigation for the project.
•
A second stage or updated
MRMM is then constructed with
Page 6 of 7
Q
0-1
1-4
4 - 10
10 - 40
> 40
Very Poor
Poor
Fair
Good
Very Good
Figure 12 Proposed development to access the stope blocks in Figure11, avoiding
hot spots in the footwall Q-MRMM
the new information, in which
the interpretation of project scale
geotechnical
domains
is
confirmed and/or revised.
The development of the MRMM has
enabled the transfer of an accurate
representation of the rock mass and
structure directly into numerical and
limit equilibrium models for the
rigorous analysis of both underground and open pit projects.
REFERENCES
Barton, N. Lien, R. Lunde, J. (1974)
Engineering classification of rock
masses for the design of tunnel
support. Rock Mechanics 6 pp189236
Dempers, G. (1991) Optimal usage
of exploration core for geotechnical
purposes.
Young
Geotechnical
Engineers Conference, Stellenbosch
University.
Laubscher, D.H. (1990) A geomechanics classification system for
the rating of rock mass in mine
design. Journal of the South African
Institute of Mining and Metallurgy.
Vol 90, No 10, pp 257-273 October.
McCracken, A. Stacey, TR. (1989)
Geotechnical risk assessment for
large diameter raise bored shafts,
Trans IMM, Section A, v 98, pp A145A150.
Seymour, C.R.W., Dempers, G. and
Jenkins, P.A. (2007) Mining Rock
Mass Models – A Methodology for
Collecting, Processing and Presenting Geotechnical Data in Three
Dimensions. Proc. Int. Symp. on
Rock Slope Stability in Open Pit
Mining and Civil Engineering, 12-14
Sept., Perth.
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