Bibliographic record
Abstract
This article, written by Special Publications Editor Adam Wilson, contains highlights of paper SPE 169715, “Chemical EOR for Heavy Oil: The Canadian Experience,” by Eric Delamaide, SPE, IFP Technologies; Brigitte Bazin and David Rousseau, IFP Energies nouvelles; and Guillaume Degre, Solvay, prepared for the 2014 SPE EOR Conference at Oil and Gas West Asia, Muscat, Oman, 31 March–2 April. The paper has not been peer reviewed. Chemical enhanced-oil-recovery (EOR) methods such as polymer and alkaline/surfactant/polymer (ASP) flooding are generally not considered suitable for oil viscosities greater than 100 or 200 cp. However, this perception is changing, in particular because of field results from a number of chemical EOR pilots or full-field floods conducted in Canada in higher viscosity oil. The aim of this paper is to review some of these projects. Introduction Canada is well-known for its heavy-oil and bitumen reserves. Most of the bitumen reserves are exploited using thermal methods, such as cyclic steam stimulation or steam-assisted gravity drainage, while heavy oil is exploited mostly using cold production methods, such as cold heavy-oil production with sand. Cold production leads to recovery of less than 10% of original oil in place (OOIP). Thermal methods are not always applicable, in particular when the pay is thin. In that case, alternatives such as chemical EOR are required to increase recovery. The two main chemical EOR processes are polymer and ASP flooding. In the past 10 years, several chemical-flooding projects have taken place in Canadian heavy-oil fields. The most successful of these is the Pelican Lake project, which is currently producing more than 60,000 B/D, much of it through polymer flooding. But other less-well-known projects such as the Taber South project, the Mooney project, and the Seal project are all interesting and worthy of discussion. For full descriptions of these fields, please see the complete paper. Projects Pelican Lake Polymer Flood. The Pelican Lake field is approximately 250 km north of Edmonton, Alberta, Canada (Fig. 1). The recovery factor for primary production remained low even after the introduction of horizontal drilling. Thus, a first—unsuccessful—polymer flood was attempted in 1997, after which waterflood was also piloted. The waterflood managed to increase oil production but with high water cut. Thus, another polymer pilot was started in 2005. Polymer injection started in May 2005. The responses were excellent, with rates going from 18 to 232 BOPD in the first well, from 9 to 364 BOPD in the central well, and from 16 to 139 BOPD in the last well. The water cut increased slowly and moderately in all three wells. The operators estimate that polymer flooding will increase the recovery factor to 20 to 30% of OOIP.
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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".