Large Bore Subsea Production Systems for Woodside's Gas Developments
Bibliographic record
Abstract
Abstract Due the high cost of deepwater subsea wells, large bore subsea production systems with high flowrate potential are desirable to lower the development cost of Woodside's gas reserves. With an ever increasing demand for reliable gas supply to LNG facilities, subsea system reliability in Woodside's exsiting and future gas development is of equal importance. With the number of large gas reserves in its portfolio, Woodside has developed an evolving strategy to deliver a suite of standard large bore reliable subsea production components to enable reliable development of gas fields for lower unit cost. This paper will describe how Woodside has worked together with its subsea system partner, FMC Technologies, to develop the equipment and systems required to facilitate reliable production of deep water high rate gas wells, including Standard 7" gas tree;Manifolds and Pipeline termination assemblies;Large bore diver-less connection systems;Umbilicals and control systems;Managing flow assurance issues (Incl. hydrate prevention, sand and flow management); Additionally, the paper will discuss the "stepping stone" approach to developing and proving the large bore system components through initial application on the NWS to the deepwater application of Pluto and will highlight the installation drivers associated with this development approach.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".