A New Method to Extract In-situ Bitumen From Core Samples
Bibliographic record
Abstract
Abstract A common challenge in fluid studies involving heavy oil, and bitumen in particular, is obtaining an in-situ bitumen sample from the highly viscous reservoirs that is water and solid free. In this paper, a salt-water assisted centrifugation (SWAC) method that was developed to effectively extract in-situ bitumen suitable for fluid studies from core samples is presented. The method involved mixing salt water with core sample pieces at a defined ratio. The mixture was then centrifuged at 50°C to separate the bitumen from the water and sand. The result was a clean bitumen sample containing less than 1 wt% of water and 0.1 wt% of sediment and a recovery rate of approximately 90 wt%. The properties of the recovered bitumen were characterized and compared with the properties of another bitumen sample that had been extracted by the mechanical squeeze (MS) method in order to understand how the salt and water used during the process may have impacted the chemical and physical properties of the bitumen sample. The experimental data showed that most of the properties of the two bitumen samples were similar with the exception of a slight variation in measured viscosities at various temperatures. The reasons for these measured viscosity differences are discussed. When compared to commercialized methodologies for removing bitumen samples from cores, such as solvent extraction, MS and hot water/steam flooding methods, the presented solvent free method is characterized for its high bitumen recovery rate and high bitumen sample quality. The SWAC method offers an efficient alternative for extracting in-situ bitumen samples in quantities sufficient for fluid related studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".