Bibliographic record
Abstract
In oil and gas production, flow assurance guarantees a successful and economical flow of the fluids from the reservoir to a designated processing facility. Flow assurance is one of the biggest challenges that a pipeline designer faces, especially under deep water where the temperature is low, and the pressure is high. These deep-water conditions favor the formation of solid deposits, which leads to blocking the flow line, reducing oil production, and potentially shutting down the well. To avoid this problem, the flow line temperature must always be kept above the solid deposit formation temperature. This necessitates accurate analysis of the thermal properties of pipelines in order to choose the best material suitable under these harsh conditions. This thesis provides a quantitative comparison based on thermal characteristics for flow assurance purposes. It also provides a realistic comparison based on strength requirement imposed on risers in general. First, we present a comparison between two different solutions (analytical and approximate) to predict the temperature profile in the steady state flow case. This comparison is carried on a steel pipeline under different cases, which are obtained by varying the length of the pipeline and the flow rate. Based on the results of the comparison, the solution that meets the objectives of this thesis is identified. Then, the thesis focuses on the effect of using different materials in the pipeline. The thesis presents another comparison between traditional steel catenary risers (SCR) and Composite Catenary Risers (CCR) based on their thermal characteristics for flow assurance purposes. The comparison is based on predicting the fluid flow temperature along the pipeline to show which material will keep the temperature above the solid deposit formation temperature, which is set in this thesis to be 20℃. Nominal homogenized mechanical and heat transfer properties are used for composite and steel pipelines of the same thickness and diameter. The obtained results show that composite risers have enhanced thermal characteristics over its counterpart steel pipelines. To establish rational comparisons between SCR and CCR, other aspects of their performance must be considered. Performance aspects regarding material strength, expected life and minimal weight design constitute the most essential minimal set for these comparisons. Comprehensive investigations are conducted, and conclusions are extracted to quantify overall performance aspects of SCR and CCR. All the code used to run the experiments was implemented in MATLAB.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".