Evaluation of the Bottom Water Reservoir VAPEX Process
Bibliographic record
Abstract
Abstract In 1998, Butler and Mokrys proposed a "Closed-loop Extraction Method for the Recovery of Heavy Oils and Bitumens Underlain by Aquifers". The process has potential application to many Alberta and Saskatchewan heavy oil reservoirs. The objective of our work was to produce an experimental evaluation of solvent-assisted process options for bottom-water reservoirs. The current work is entirely experimental, but does provide data that may be used to back up a numerical simulation effort. The experimental series modelled a bottom water process in order to determine its feasibility for a field-scale oil recovery scheme. A series of experiments were run in an acrylic visual model. Pujol ands Boberg scaling were used to produce a lab model scaling a field process by a geometric ratio of 100:1, and compressing field time by a ratio of 10,000:1. The model simulated a slice of a 30 m thick reservoir, with a 10 m thick bottom water zone, containing a pair of horizontal wells, at the il-water interface, offset by 25 meters. To allow field prediction, experimental results were scaled up to represent a 30 m thick reservoir (20 m thick oil zone) with 500 m horizontal wells. The experimental rates were negatively impacted by continuous low permeability layers and by oil with an initial gas content. The lower effective diffusion rates required that the surface area exposed to solvents be increased in order to achieve commercial oil recovery rates. The Bottom Water process described in this report offers the opportunity to do just that, as the large surface area of the oil water interface between the wells will provide contact for solvent by injecting gas at the interface. Given an appropriate well spacing, high production rates may be possible. Introduction The Alberta Research Council (ARC) has done several years of investigative work into solvent-assisted heavy oil recovery processes (Frauenfeld et al 1997; Frauenfeld et al, 1998). The present report describes a particular contribution to solvent-assisted oil recovery technology: a comparative scaled physical model study of bottom water process options. Mechanisms of the Bottom Water Vapex Process The Bottom Water Vapex Process, illustrated in Figure 1, is a recovery process depending for its success on the interplay of several mechanisms. The solubility of the gas in the oil is controlled by the k-values of the oil-solvent system. Diffusion, hydrodynamic dispersion and swelling also play a role in the movement of gas into the reservoir oil. The oil flow is enabled by viscosity reduction due to the dissolution of solvent in the oil. Oil-solvent contact is further augmented by capillary pressure moving some oil into the vapour chamber zone. Heterogeneity of the reservoir sand further increases the surface produced by capillary action, but excessive layering can hinder the movement of oil. Drainage occurs in both a classical Vapex chamber above the injection well, and in a layer at the oil-water interface. Another mechanism for solvent-based processes is viscosity reduction by asphaltene precipitation.
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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 | 0.001 | 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".