Design and Analysis of Cellular Tendon for TLPs in Ultra-Deep Water Fields Offshore Southeast Asia
Bibliographic record
Abstract
TLPs (Tension Leg Platforms) are ideal platforms for drilling and dry trees in deep water oil and gas production worldwide. Currently there are over sixteen TLPs installed in regions including GOM, Southeast Asia, and West Africa. Several TLPs are planned for installation in West Africa and Brazil in the near future. The application of TLPs has reached a water depth limit that is around 1500 meters. The bottle-neck is the feasibility of the design of the tendon main body segments. Currently, the conventional tendon main body consists of a single string of steel pipes that in the ultra-deep waters cannot meet the combined requirements on stiffness and collapse resistance using the industry conventional installation methods. Other material such as carbon fibers were conceived as the tendon pipe material but are deemed as economically unviable. The concept of the cellular tendon is developed to meet the industry's demands to go deeper for oil and gas production. It consists of multiple strings of carbon steel pipes bundled together to enable the TLP application in water depths up to 3000 meters. The general concept and merit of the cellular tendon design will be presented in reference [1]. This paper further demonstrates the applicability of the cellular tendon by providing in-depth design details and dynamic analysis results tailored for the fabrication and installation in South and Southeast Asia. The findings and the results presented in the paper can be utilized in the planning and design of a TLP in the ultra-deepwater of these regions. Reference [1]: Conference paper "Cellular Tendon - Enabling Technology for Ultra-Deep Water TLPs, 13OTCB-P-457-OTC".
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".