Pore-Level Investigation of Heavy-Oil Depressurisation
Bibliographic record
Abstract
Abstract Bubble nucleation, growth and mobilisation of gas are important phenomena encounter in oil production by the depressurisation process. The drive energy for oil production during pressure depletion is supplied initially by oil expansion but mainly by gas evolution from solution and expansion of reservoir fluids. Some heavy oil reservoirs in Venezuela and Canada show a high recovery factor during primary production under the solution gas drive process. Factors responsible for high oil recovery in heavy oil reservoirs are not well understood to allow reliable predictions to be made for economic evaluation of the process. A series of flow visualisation tests at the pore level was conducted using a high-pressure glass micromodel to identify the key features of the process. A heavy crude oil, with a viscosity of 2500 cp at the bubble point pressure and API of around 10, was used to perform the tests at reservoir conditions. Micromodels with realistic pore pattern and different wettability characteristics, including oil-wet, water-wet and mixed-wet were used in the tests. A series of experiments was performed to study the effect of depletion rate, saturation history and water presence on the nucleation process, gas evolution and hydrocarbon movements. Our observations highlighted the significance of test conditions, particularly saturation history and operational conditions on the nucleation process and bubble formation. Laboratory tests can produce a large number of bubbles formed by pre-existing micro bubbles activation, or a limited number of bubbles due to bulk nucleation, resulting in widely different depressurisation results. Hence, interpretation of laboratory data and its application to field performance would require particular considerations as identified in this study. Critical gas saturation and subsequent gas/oil production are strongly affected by the critical value of supersaturation and the number of bubbles formed during depressurisation. Two generalised correlations have been developed to predict the above parameters at realistic reservoir conditions. The experimental data generated in this study and interpretation of the results provide information on gas nucleation, critical supersaturation, bubble density and critical gas saturation, which are essential in field development planning and estimation of oil and gas recovery by depressurisation. The study also clears a number of ambiguities in the literature on prevailing mechanisms in depletion of heavy oil and contradictions between laboratory and field results.
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 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 | 0.000 | 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) | 0.001 | 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".