Ice Detection and Management in Support of Canadian East Coast Oil Operations
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".