Floater Concept Selection for Ultradeep Waters in Brazil
Bibliographic record
Abstract
Abstract Uncertainties on design basis during early design stages of offshore fields are a known challenge to deal with when selecting feasible development options. Ultradeep water discoveries have hampered these choices. The scope of this paper is to describe the methodology applied for the identification of most suitable floater(s) to operate in an ultradeep waters block located in the Campos Basin south-east of Rio de Janeiro in Brazil. The block of study is located in a remote area far from shore within water depths nearly to 3000 m. FPSO and semisubmersible floaters are identified as the most preferable floaters. The paper will show the combination of most important design players and decision trees for reaching flexible solutions feasible for several production scenarios at an early project stage. Technical players such as Brazilian environmental conditions, variable risers and topsides loads, variable storage capacities, and floater motion restrictions have been combined with commercial and risk players, such as ultradeep waters technology maturity, local content, market requirements, shipyards capacities and previous experience in the country with solutions adopted in similar fields, locations or depths. As a result, the study will show a number of floater options integrating one or two hulls feasible to develop on further design stages.
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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".