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Boundary modeling with uncertainty
- Author / Creator
- Mancell, Steven, A.
Mineral exploration and mining are capital intensive and carry significant environmental and societal
considerations. The feasibility of prospective mining operations hinges on a series of engineering
decisions. The mineral resource estimation of the quality and quantity of resources greatly influences
these decisions. Boundary modeling for defining subsurface geology is an essential aspect of the
mineral resource estimation workflow. The proper spatial distribution of geological domains for
further estimation is integral to having accurate and precise models. Uncertainty in the boundary
and resource is quantifiable and is a result of sparse sampling and complex geology. Consequences
of poorly defined boundaries include dilution of ore material, smearing of grade into uneconomical
rock, and increased uncertainty in the deposit tonnage. These consequences directly impact the
economic, environmental, and societal feasibility of operations.
Boundary modeling workflows commonly use implicit techniques that automatically derive domain
extents from data. These models are explicitly checked and edited to ensure the numerical model
reflects known geological attributes. This deterministic approach generates a single model output
and does not carry a measure of uncertainty. Stochastic approaches to boundary modeling capture
short scale variability of the geology; however, imparting geological knowledge on the model is
This thesis develops a new implicit methodology for boundary modeling that provides globally
unbiased models with uncertainty. The indicator approach maps a field of probabilities and applies
a threshold that results in an extracted boundary. Uncertainty assessment by varying the indicator
thresholds provides eroded and dilated boundaries and a zone of uncertainty. Boundary definition is
a critical and early step in resource estimation. The modeling of subsurface geology from sparse drill
holes carries significant uncertainty. The results of this thesis provide a novel approach to boundary
modeling with uncertainty. The geostatistical techniques and concepts are reviewed, the proposed
framework outlined, and implementation, including case studies, are undertaken.
- Graduation date
- Spring 2021
- Type of Item
- Master of Science
- This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.