Application Research of Engineering Construction Standardisation in an Oilfield Development Adjusting Project in Bohai Sea
Bibliographic record
Abstract
Abstract In order to improve the efficiency and economic benefits of oilfield development, the researchers applied the standardisation achievements of Bohai oilfield engineering construction in the preliminary research and basic design of an oilfield development adjusting project in Bohai Sea for the first time. The application research mainly contains the topside, jacket, living quarter and workover rig of the project. In which, the topside and jacket are researched based on the standardisation achievements of Eight-Legged Central Platform Type B, the living quarter applies the standardised 60 persons living quarter and the workover rig adopts the achievements of workover rig HJX180D. Meanwhile, some optimizations and adjustments are carried out according to the actual needs. Through the application research, the basic design of the new platform is basically consistent with the standardised platform, and some settings are optimized and adjusted. Then the comparison and differences of the settings are analyzed between the two platforms, and the improvement measures are proposed for better application of standardisation achievements. Through the full application research of the standardisation achievements of Bohai oilfield engineering construction, the project is conducive to the improvement of the efficiency and quality in management, research design, procurement and platform construction. As a result, it can save the construction period and cost, and improve the overall economic benefits of the oilfield development. Through the application of the standardised drawings and documents of the standardised topside, jacket, living quarter, workover rig and main equipment, the design period is shortened by 3 months comparing with the conventional period. Moreover, the standardised design of the main structural materials and equipment not only can save the procurement time and reduce cost, but also can facilitate the process management of the equipment and materials. Therefore, the economic benefits of the oilfield are effectively improved, which can provide strong support for the smooth production of the oilfield. The experience accumulated in the application research of standardisation achievements in this project can provide some reference value for the promotion and application of similar projects in the future.
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) | 0.000 | 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 | 0.000 | 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".