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Employing effective soil handling strategies to meet reclamation targets in Alberta’s Athabasca oil sands region

2012· article· en· W2622696669 on OpenAlexaboutno aff
Wade Pruett

Bibliographic record

VenueMine closure · 2012
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsnot available
Fundersnot available
KeywordsLand reclamationOil sandsEnvironmental scienceEngineeringAsphaltGeography

Abstract

fetched live from OpenAlex

This paper describes the role that effective soil handling strategies play in promoting successful reclamation in Alberta’s Athabasca oil sands region. As oil sands developments continue to expand the need to promote effective reclamation planning early in the life of mine becomes integral to successfully meeting reclamation targets. Establishing and maintaining well considered soil handling practices throughout mine development and operation ensures soil quality is maintained and adequate reclamation material is available for the life of mine. Effective soil handling must begin with realistic and achievable material balance calculations. Often mine development projects run into costly reclamation scenarios due in part to unrealistic reclamation material estimates. Potential reclamation material balance shortfalls and potential soil quality degradation are compounded by the relatively large scale and long life of oil sands mines. Soil handling plans should start from the base precept that reclamation planning be more closely tied to achievable life of mine material balances. Reclamation material estimates accuracy benefits from being more mindful of project-specific limiting conditions and operational feasibility, as opposed to stamping an ultimate footprint on a map and running basic calculations. More often than not, material balances do not take into account ‘real world’ factors that impact reclamation material salvage. In this regard, the material balance and soil handling plan must allow for reconciliation based on actual reclamation material recovery rates. Spatial and temporal considerations must be included in soil handling planning to ensure that proposed soil and vegetation prescriptions are attainable. Not achieving reclamation targets, either spatially or temporally, can result in large financial penalties. It is recommended that mine planners work with experienced soil specialists to ensure the best quality materials are salvaged and stockpiled for reclamation early in the mine development process to avoid potential shortfalls later in life of mine. Soil salvage and placement strategies should be dynamic and evolve in step with research and operational changes. Early implementation of practices for effective soil salvage and placement can identify deficiencies before critical stages of mine development where alternation of reclamation practices and targets becomes impractical. Scientifically and operationally sound soil salvage and placement practices provide a solid base for achieving reclamation targets. Establishing reclamation material stockpiles in prudent locations becomes particularly important when linking soil placement with reclamation progression. Within the limitations of the mine plan, stockpiles should be positioned relative to destination points to ensure material availability when targeting soil prescriptions that achieve reclamation targets. A reasoned plan for storage and movement of reclamation material will reduce transportation costs, reduce emissions and improve reclamation efficiency. Effective soil handling also promotes protection of soil quality and ensures adequate reclamation material is available when needed. This process helps to ensure that reclamation targets can be achieved. Poorly designed soil handling plans lead to costly budget overages and unattainable reclamation targets.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.209
Threshold uncertainty score0.837

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.220
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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