Surfactant-Steam Process: An Innovative Enhanced Heavy Oil Recovery Method for Thermal Applications
Bibliographic record
Abstract
Abstract Surfactant-steam process (SSP) is a novel and potentially cost-effective process that utilizes a small amount of surfactant co- injected with steam to enhance the oil recovery of steam assisted gravity drainage (SAGD) well pairs. The mechanism of this process involves interfacial tension (IFT) reduction, reservoir rock wettability alteration, oil relative permeability enhancement, and in-situ emulsification. SSP is expected to result in oil rate acceleration, steam-to-oil ratio (SOR) reduction and enhanced ultimate oil recovery factor. Analogous enhancement is expected if the SSP is combined with other steam-based or steam-solvent processes. This paper provides an introduction to this concept and presents a unique protocol that has been developed for screening surfactants for co-injection with steam in SAGD process. In particular, the paper presents a scientific approach to surfactant selection for SSP applications, describes the conditions in which the surfactants needs to be deployed within the reservoir, and also predicts the potential synergies if use of different classes of surfactants is made. Novel experimental design on different aspects of surfactant-steam phase behavior indicates the optimum surfactant concentrations for field trial applications. Lab testing of selected surfactants on typical Canadian oilsands sand packs shows an improved incremental oil recovery factor (RF) in the range of 6 to 16% (for different tested surfactants) compared to a SAGD base case. SSP simulations were conducted for one of the surfactants that were tested in the lab. The simulation results indicate that this particular surfactant on average accelerated the oil rate by 15% in the first 30 months of SSP operation, increased the ultimate oil RF by 10%, and reduced the cumulative steam-to-oil ratio (CSOR) by almost 11% relative to a SAGD base case. In addition, a sensitivity analysis was conducted to investigate the effect of surfactant concentration co-injected with steam. The simulation results suggest that there is an optimum concentration for a given surfactant that needs to be explored through lab investigations and field trials. It is evident that once the SSP is successfully developed, the use of surfactant promises to improve environmental performance and project economics of the in-situ oilsands recovery.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".