Solvent Versus Surfactant Co-Injection with Steam to Improve Efficiency of Steam Assisted Bitumen and Heavy Oil Recovery Processes
Bibliographic record
Abstract
Abstract In Alberta, Canada bitumen is produced by SAGD and CSS methods at about 1.5×106 barrels per day capacity. Efficiency of these operations is measured by steam-to-bitumen mass ration, which is reported in the range of 2.6 to 5. Oil industry has invested on solvent such as light hydrocarbons co-injection with steam to reduce SBR, speculating that solvent would reduce bitumen viscosity and increase Darcy mobility of bitumen in the reservoir, which has resulted limited commercial success. In majority of these studies, effect of solvent co-injected with steam on bitumen-water interfacial tension, therefore on Darcy permeability was ignored. Our laboratory has been studying to increase Darcy permeability of bitumen by reducing bitumen-water interfacial tension. For this purpose two methods were investigated: (i) surfactant species were produced by in-situ sulfonation-sulfoxidation of bitumen asphaltenes by co-injecting a trace amount of gaseous sulfur dioxide (SO2) with steam; and (ii) co-injection of biodiesel (BD) as a surfactant additive, with steam at under 2 g-BD/kg-bitumen dosages, which corresponds to under 0.32 kg-BD/bbl-bitumen, or under 0.67 kg-BD/ton-steam if SBR is 3:1. Bitumen recovery tests were also made to compare performances of solvent versus surfactant co-injection with steam methods by operating the test apparatus in bath mode, which most likely stimulate the steam zone of the steam zone of the SAGD and CSS reservoirs. These tests showed that solvent co-injection potentially reduces bitumen recovery efficiency compared to steam-only methods. We wonder that the solvent co-injected with steam increases bitumen-water interfacial tension, increases slip velocity at bitumen-water interface and reduces Darcy permeability of bitumen. Experimental observations supported with fluid dynamics analysis of two immiscible fluids with slip boundary condition at the interface of two fluids were encouraging to expand our research in BD-water emulsions flooding for cold heavy oil recovery, CHOPS and Post CHOPS, and BD-solvent-water emulsions flooding for extra viscous heavy oil, and bitumen production from high permeability reservoirs, which would eliminate demand for steam. Experimental data on bitumen viscosity, bitumen-water interfacial tension and potential effects of solvent and surfactant co-injection with steam on commercial steam assisted bitumen and heavy oil recovery operations will be discussed.
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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".