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Record W2023749548 · doi:10.4043/13026-ms

Ice Detection and Management in Support of Canadian East Coast Oil Operations

2001· article· en· W2023749548 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueOffshore Technology Conference · 2001
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsPetro-Canada
Fundersnot available
KeywordsIcebergGeneral partnershipSea iceEnvironmental resource managementEngineeringEnvironmental scienceOceanographyBusinessGeologyFinance

Abstract

fetched live from OpenAlex

Abstract Oil exploration and production activities off the East Coast of Canada lie within the marginal ice zone, and as such, are subject to seasonal incursions of both pack ice and icebergs. Oil operations on the Grand Banks include facilities such as the Hibernia GBS, the forth-coming Terra Nova FPSO, shuttle tankers and loading stations, and semi-submersible drilling rigs, all with a common goal of avoiding contact with ice. Safety of personnel, the environment and equipment is of paramount importance to all operators on the Canadian East Coast. An ice mass, even those as small as a bergy bit (roughly the size of an automobile) can cause disruptions to oil activities and endanger facilities. Early detection and appropriate ice management should significantly decrease the amount of non-productive time for all operations on the Grand Banks. One single iceberg with a dedicated supply vessel to perform ice management operations should not pose a threat to a facility. Individual facilities will naturally be concerned with their own priorities, possibly disregarding the concerns of other facilities. To minimize disruptions to operations from encroaching ice, the Grand Banks operators in partnership with service companies developed and operate an integrated ice management system. A wave of icebergs with limited supply vessel resources is the major challenge to the integrated ice management philosophy. The integrated ice management system combines the elements of detection, tracking, threat assessment and management utilizing a wide variety of information and data sources and limited physical resources. This paper will describe the ice management system, the process for selecting cost effective data for a given situation, and the process of tracking, assessing and managing ice threats. This paper will also report on the economic and operational challenges to integrated ice management philosophy faced by four individual operators during the 2000 ice season. BACKGROUND The East Coast of Canada is subjected to seasonal incursions of both sea ice and icebergs. These annual visitors provide the tourists many photo opportunities, however they present the Offshore Oil Industry with a problem of how to operate safely while minimizing any disruptions to their operations. Sea Ice. The sea ice regime starts in September with the growth of new ice in Northwest Baffin Bay. Beginning in October, a combination of growth and predominantly southward drift, driven by the prevailing northerly winds and the strong, cold Baffin Current, advances the ice southward. By December, the leading edge of the advancing ice pack lies off northern Labrador. In typical years, the ice edge reaches the northern tip of Newfoundland in early January and the Grand Banks in mid-February (Navoc 1986). The pack ice off Newfoundland generally reaches annual peak coverage in March but can remain at high levels through May. Loose (60%) coverage of first year or white ice is the dominant ice form in areas off Newfoundland. Subsequently, the ice pack retreats rapidly northward with significant ice concentrations confined to northern Labrador by the end of July.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.876
Threshold uncertainty score0.808

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
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 head0.013
GPT teacher head0.199
Teacher spread0.186 · 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