LiuHua Oil/Gas Project: First Self-Developed Completion Campaign Using Subsea Horizontal Trees in South China Sea
Bibliographic record
Abstract
LiuHua4-1 &LiuHua19-5 oil/gas fields are the first batch of Chinese self-developed projects using subsea production system in the Pearl River Marine Basin (PRMB) of South China Sea. We installed 10 sub-sea horizontal trees by a single hull vessel "HYSY708" and a semi-submersible "NH5" in the block, the completion execution phase was performed on Moored Mobile Offshore Drilling Units (MODU) with no prior experience in subsea completions from June 2011 to January 2014. Value creation activities were employed to raise the awareness and competence of the rig team to transform improvement opportunities into high performance goals. This paper presents an integrated completion program developed and implemented for reservoir characterization and formation evaluation in South China Sea. Completion fluid and treatment fluid were carefully selected and tested for well-specific conditions. The program used a combination of various completion techniques such as material corrosion, hydrate prevention, subsea horizontal tree installation, work string design optimization, subsea canned dual ESP completion system, intelligent well completion, emergency response in complex condition, etc. The integrated completion programs were designed and modified to meet the project delivery timeline and cost constraints, while responding to the challenge of properly testing the oil/gas reservoir. This paper also presents completion data analysis results and summarizes the encountered challenges and learned lessons from field operations. Specifically, we present field operation results and explain the key program elements. The learned lessons and gained experiences from the field operation presented here provide valuable guidance for future deep-water oil /gas exploration and development operations.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".