Field Trials for a Novel Water Deoiling Process for the Upstream Oil and Gas Industry
Bibliographic record
Abstract
Abstract In the upstream oil and gas industry, hydrocarbon well production is very often associated with significant fractions of water, whether from the reservoir or byproducts of the drilling and completion processes. Before discharge into the environment, or reinjection into the formation for pressure maintenance or disposal, this unwanted water must have an extremely low oil content to comply with statutory discharge requirements, or to ensure long-term injectivity. Although many techniques have been used over the years for water deoiling – EARTH<sup>1</sup> – gains could be achieved in the fields of operating expenditures, energy requirement, performance, and ultimately waste reduction. This paper presents a novel water deoiling process that exceeds the foreseen statutory requirements. It is based on a combined coalescence and separation process. The process is able to deliver water down to 10 mg/L oil content, with a very low pressure drop, and without having to discard spent oil-absorbing material.
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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 | 0.000 | 0.000 |
| 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".