Feasibility of Oil Mud Reinjection from Offshore Platforms in Bohai Oilfield
Bibliographic record
Abstract
Sludge produced by offshore oilfields can be difficult to treat. thus, it is necessary to explore the feasibility of its reinjection into reservoirs for environmental protection and economic benefits. In this study, oil sludge produced from an oilfield in the Bohai Sea was ground and refined, and a reinjection system using a polymer solution was developed. To determine the feasibility of the reinjection system, we analysed its stability, solution performance, injection performance, and oil displacement effect. The experiment results indicate that when the particle concentration of the system is ≤ 200mg/L, the system dispersion, anti-shearing, and anti-ageing stability can be enhanced. When he particle concentration is ≤100 mg/L, the system can easily manage the viscous nature of the solid particles, thereby achieving optimal stability. At a particle concentration of 100mg/L, the system can run with optimal performance and achieve good oil displacement efficiency. Therefore, a system with a particle concentration of 100mg/L can be used for long-term reinjection of offshore platforms in the Bohai oil reservoir, achieving environmentally friendly treatment of produced sludge while further enhancing the oil recovery rate of the reservoir.
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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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".