Ice Monitoring Program in Support of Sakhalin Energy’s Offshore Oil Production
Bibliographic record
Abstract
Since the summer of 1999, Sakhalin Energy Investment Company (SEIC) has been producing oil at the Molikpaq platform in 30m of water 15km off the east coast of Sakhalin Island. The paper in this conference by Reed (2006) covers the project description, the paper by Keinonen et al (2006b) covers the operations in ice and risk management, and Tambovsky et al (2006) covers the environmental conditions, in more detail. The monitoring program described in this paper has been specifically designed to provide extensive ice and environmental data to support the risk management and allow the planning of safe oil production operations using a Single Anchor Leg Mooring (SALM), Floating Storage and Offloading System (FSO), and export tankers in ice. The paper covers two major aspects of the in-ice operations: Ice management to protect the offshore loading operation on a minute by minute basis in moving ice, and also ice forecasting, to determine when any unmanageable ice might approach the tanker loading site and cause the shut down of operations in the fall and during the startup of operations in the spring. The forecasting of ice drift, ice formation and growth in the fall and ice decay in the spring are discussed. Also discussed is the forecasting of episodic events that are unique to the NE coast of Sakhalin Island.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".