Computed Tomography Study of VAPEX Process in Laboratory 3-D Model
Bibliographic record
Abstract
Abstract Vapour Extraction (VAPEX) process has been an intense research topic in recent years as an alternative technology to thermal recovery method for heavy oil and bitumen resources. In the past, most two-dimensional (2-D) transparent modelsstudies have only simulated the vapour chamber evolution behavior of a vertical slice of the reservoir; however, the longitudinal vapour chamber evolution characteristic in three dimensional reservoirs could not be detected. This paper presents the results of three-dimensional (3-D) monitoring of the VAPEX process in a small laboratory model, using computed tomography (CT) technology to investigate the vapour chamber expansion behavior in both radial and longitudinal directions. The model is an aluminum cylinder with 140 mm inside diameter and 600 mm length. Two slottedaluminum tubes were installed inside to act as the injection and production well, respectively. Solvent by-passing concern was considered for the model designing and sand packing. Solvent was commercial propane, oil was Lloydminster type heavy oil, and all experiments were conducted under room temperature. The experiments showed that in 3-D geometry, the claimed "V" shape vapour chamber expansion by the previous 2-D model was only a localized phenomenon. In longitudinal direction the dominant characteristic was overriding of the injected solvent at the top of the model promoted by gravity segregation, solvent gas longitudinally expanding was more significant than upward expanding at the early stage of VAPEX process. This is enhanced by the confinement provided by the cylindrical geometry of the core holder. In addition, the further residual oil recovery potential after VAPEX process was investigated by "solvent soaking" method. The oil production performance under different solvent injection rates was compared. By numerical analysis of the CT images, the in-situ model porosity, density and oil saturation profiles were obtained. The results indicate some new ideas about VAPEX process mechanism. Introduction From the more than 400 billion m3 heavy oil and bitumen deposits in Canada, only 10% is surface minable. The major part of the deposits has to be relied on in-situ recovery process.1 However, due to their high viscosities and low degree API gravities in native state, 2 these reservoirs can only be recovered with low recovery efficiency by conventional methods. For example, primary recovery in the best of these heavy oil reservoirs is about 6% of the original-oil-in-place (OOIP). Subsequent water flooding can improve the recovery to an extent of 1% ∼2% incremental of OOIP.3 In order to more effectively recover these reserves, tertiary recovery methods have to be directly applied.4 The main technology challenge is to reduce the heavy oil viscosity in-situ.5 As the oil viscosity is very sensitive to temperature, thermal recovery methods seem to be very effective and have been widely researched and pilot tested, 6 including as Cyclic Steam Simulation (CSS), In-Situ Combustion (ISC), Steam Assisted Gravity Drainage (SAGD) and Steam Flooding.7 The SAGD process has been commercially used by several oil companies.
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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".