Annual Meeting Preliminary Program - Full Brochure (PDF) - SME

TECHNICAL PROGRAM
9:25 AM
What Happened to My Gold? Questions to Ask Your Modeler
A. Jewbali, T. Elenbaas and C. Roos; Newmont Mining Corp, Greenwood
Village, CO
Mining engineers rely on resource models as the basis for their mine plans.
However, many of the assumptions for grade-tonnage relationships or resource
classification are not well-communicated between the geostatistician and the
mine planner. This talk outlines some of the common assumptions and the risks
that engineers may be taking when elevating cutoff grades, optimizing schedules,
or generating forecasts.
9:45 AM
Tired of Hearing Why Did the Mine Plan Change?
T. Bush and C. Roos; Newmont Mining Corp.,
Greenwood Village, CO
Plan erosion is the term given to the loss in value as the mine planning level of detail
increases. The value loss could be associated with a project as it transitions
from pre-feasibility to feasibility and then in to operation or could be the loss in
value as the long range mine plan becomes the short range mine plan. This paper
documents some of the techniques in the areas of practical mining constraints
and model variability that Newmont uses to minimize the impacts of plan erosion
on advanced projects.
10:05 AM
Take Time for Pit Phase Design
A. Eccles; Newmont Mining Corp, Greenwood Village, CO
Phase designs are the foundation upon which all open pit mine sequence optimizations
and budgets should be built. Unfortunately, at times, mine engineers
skip the step of developing realistic pit phase designs - designs that include access
ramps and mineable widths. Without mineable phase designs, their Optimized
schedules are based on theoretical pit shells or quick-and-dirty plans with no
ramps. The output from such optimizations is almost always overly optimistic.
Without mineable designs, the production estimates are misleading, because they
overestimate ore, and underestimate waste stripping requirements. Worse yet,
when plans are not based on realistic phase designs, they can point to exactly the
wrong decision in feasibility studies (i.e. go when it should be no-go ). This paper
discusses the importance and features of good pit phase design, and demonstrates
the pitfalls of relying on optimized production sequences that are not
based on properly designed pit phases.
10:25 AM
Mine Production Scheduling Optimization at Newmonts
Twin Creeks Mine
K. Kawahata, P. Schumacher and R. Hufford; Newmont Mining
Corporation, Golconda, NV
Newmonts Twin Creeks Mine, located in northern Nevada, is producing gold ore
from surface mining operations. The ore is currently processed at three different
on site facilities depending on the ore type and the grade. The processing facilities
operate under stringent geochemical blending contraints that must be met from
mine ore deliveries and off site sourced ore. To analyze various strategic options,
we utilize the mathematical optimization approach. However, due to the size and
the complexity of the operation, we face challenges in optimizing life of mine
production scheduling. We describe those challenges and the methodology that
we are taking to overcome those by using different scheduling software to compensate
each other to get reasonable guidance. We also describe how those scheduling
results are reflected in detailed mine plan and cost estimate work.
10:45 AM
From Optimization to Operations: Bridging the Planning Gap
C. Taylor 1 and O. Wyberneit 2 ; 1 Runge Mining Canada Ltd., Toronto,
ON, Canada and 2 Runge Inc., Denver, CO
Bridging the gap between long and mid-range planning horizons in order to develop
an executable plan without destroying value is a problem which is faced by
many planning engineers. Due to the complexity of most mines optimization
tools tend to simplify the problem so it becomes more manageable. This often
means reducing the number of scheduling blocks, number of materials and number
of destinations. This approach does not lend itself to modelling of real world
mining constraints which often leads to unachievable plans and unrealistic expectations.
The approach used by Runge at many sites to bridge this planning gap involves
stewarding to the optimized plan while utilizing a rules based heuristic
scheduling engine which ensures the sequence generated is operationally feasible.
To ensure that as much of the original NPV is preserved as possible a post scheduling
period product optimization logic is applied. This combination of heuristic
scheduling and optimization logic ensures the value of each sequence is maximized.
This process enables mine planners to deviate from the optimized sequence,
when required, while ensuring the resultant plan is still maximizing potential
value.
11:05 AM
Incorporating Cycle Time Dependency in Truck/Shovel Modeling
A. Anani, B. Osei and K. Awuah-Offei; Mining, Missouri University
of Science and Technology, Rolla, MO
The need to optimize surface mining operations has led to the use of discrete
event simulation (DES) modeling of truck-shovel systems. Often, these models
assume truck cycle times are independent and identically distributed (iid) random
variables although when there is significant bunching on the haul routes,
this may not be valid. The objective of this paper is to present a methodology to
(i) test whether cycle time data is iid; and (ii) account for dependence in truck
cycle times. To test for dependence, truck cycle times were converted to a time series
and statistical correlation test done on the time and cycle time differences. A
time series approach that account for dependence caused by truck bunching is
proposed and validated in ArenaÆ. This work extends the usefulness of DES in
truck-shovel applications
11:25 AM
Mine Planning Efforts Associated with the Round Mountain Pit
Northeast Wall Failure
C. Mimica; Kinross Gold Corporation, CopiapÛ, Chile
Truly understanding geotechnical parameters to reduce the risk associated with
highwall instabilities is an issue throughout the mining industry due to limited
capital availability. Even with the geotechnical investigations and modeling that
are completed when a new pit design or pushback design is proposed, they do not
ensure the absence risk. This paper presents the sequence of events that occurred
when a major slide occurred on the northeast wall of the Round Mountain Pit in
a major ore producing section of the mine and the mitigation effort to allow access
to the affected area. Site technical services personnel worked closely with geotechnical
consultants to prepare a remediation plan that included removing the
upper benches of the slide while maintaining production access to a portion of
the area below the failure during remediation. Full access to the affected area was
achieved approximately 8 months after the slide occurred.
Mining & exploration:
technology: how Software technology
Makes My Job easier
9:00 AM • Tuesday, February 26
chair: R. Diaz, Maptek, Lakewood, CO
9:00 AM
Introductions
9:05 AM
A GIS Model for Selection of Suitable Sites for Underground
Coal Gasification
Z. Hyder, N. Ripepi and M. Karmis; Mining and Minerals
Engineering, Virginia Tech, Blacksburg, VA
Proper site selection is key to the success of Underground Coal Gasification
(UCG) projects. Most important site selection parameters include coal rank, seam
depth, seam thickness, dip, porosity & permeability, groundwater, available infrastructure
and coal quality. This paper describes the development of a GIS model
that helps in the selection of suitable sites for UCG, based on these selection parameters.
The model uses powerful features of GIS software, ArcGIS and IDRISI
and develops a general flowchart of the process that may be applied to any site.
The paper explains all the steps required to develop and use this model such as
data acquisition, data development, importing features from different data sources
and databases, preparation of data layers in GIS software, identification of factors
and constraints, standardizing, weighting and combining factors to form suitability
scores and finally identification & ranking of suitable sites. The paper also describes
the decision support techniques used for this model including development
of tradeoff levels between factors, ranking and scaling of factors based on fuzzy
membership, data uncertainty evaluation and risk management.
This is the Technical Program as of September 1, 2012. IT IS SUBJECT TO CHANGE.
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Please see the Onsite Program for final details.