Design and Operational Procedures for a Locally Made Steam Distillation Apparatus
Bibliographic record
Abstract
In Trinidad, oil production started just over 100 years ago and steam flood operations started just under 50 years ago. In steam flood operations, oil recovery by steam distillation can be in the range of 5 to 60 % and therefore requires separate experimental and mathematical studies for accurate steam flood predictions. The steam distillation apparatus required for the experimental study can be quite costly. In order to conduct steam distillation studies in the Petroleum Studies Unit in Trinidad, a steam distillation apparatus was designed, fabricated and tested to perform these studies, as an integral part of the experimental steam flood studies on Trinidad crude oils. The apparatus consist of a positive displacement pump, a steam generator, a steam distillation cell, a temperature measurement and control system, a back pressure valve and a condensing and liquid collection system. The steam generator and steam distillation cell were fabricated in-house, from stainless steel and were designed to conduct steam distillation studies at a safe working pressure of 4.654 MPa and temperature of 260 °C. From the operational procedures outlined in this study and from repeat test runs conducted at 100 °C and 260 °C steam distillation results were reproduced with differences of less than ± 4.0 % between the original and repeat runs. Details of the apparatus design and operational procedures from this study can provide a useful guide for other Researchers on crude oil steam distillation studies. Key words : Steam distillation apparatus; Design; Operational procedures; Oil; Steam; Temperature; Pressure; Trinidad
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.008 |
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".