Processes Responsible for Heavy-Oil Recovery by Alkali/Surfactant Flooding
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Bibliographic record
Abstract
This article, written by Senior Technology Editor Dennis Denney, contains highlights of paper SPE 113993, "Investigation into the Processes Responsible for Heavy-Oil Recovery by Alkali/Surfactant Flooding," by J. Bryan, SPE, University of Calgary and TIPM Laboratory; A. Mai, SPE, University of Calgary and TIPM Laboratory and Laricina Energy; A. Kantzas, SPE, University of Calgary and TIPM Laboratory, prepared for the 2008 SPE Improved Oil Recovery Symposium, Tulsa, Oklahoma, 19-23 April. The paper has not been peer reviewed. This paper describes a suite of alkali/surfactant (AS) floods that were performed in systems containing viscous heavy oil (11 500 mPa⋅s). The study investigates how AS injection can be used to generate oil-in-water (OIW) emulsions, which can in turn improve sweep efficiencies and oil recovery. Data were obtained from coreflooding, with in-situ saturation measurements made using low-field nuclear-magnetic-resonance (NMR) analysis. The corefloods in this study indicate that emulsification is most efficient when used to block preformed water channels and improve the sweep efficiency of the flood. Introduction Several countries, including Canada and Venezuela, contain significant deposits of heavy oil and bitumen. These oil-sands are high-porosity and -permeability unconsolidated reservoirs. The viscosity of the oil in place may range from tens to millions of mPa·s at reservoir conditions, and the oil densities approach or are higher than that of water. Recent estimates put the primary recovery of heavy oil at an average of approximately 5% of the original oil in place (OOIP), with significant oil resources remaining as potential for secondary and tertiary recovery. However, many of the reservoirs in Canada are relatively small or thin, and were possibly disturbed during primary production. As a result, these reservoirs are not prime candidates for expensive thermal or hydrocarbon-solvent enhanced-oil-recovery technologies. Therefore, less-expensive (nonthermal) methods of recovering the oil must be considered. Previous research focused on improved heavy-oil recovery by application of waterflooding and AS flooding. This work found that during a heavy-oil waterflood, water will break through very early in the life of the flood because of viscous instabilities, resulting from the adverse water/oil mobility ratio. After water breakthrough, continuous channels of water existed throughout the reservoir. At later stages in a heavy-oil waterflood, capillary forces and water imbibition were the dominant recovery mechanism. At low injection rates, significant volumes of heavy oil can be recovered after water breakthrough, though at a high water cut. AS injection could be considered either as a primary- or secondary-recovery process. Overall, a combination of waterflooding and AS flooding can lead to significantly improved oil recovery beyond that of primary production. Pressure and recovery data were analyzed to infer how the chemical flood worked, and NMR spectra of the fluids in the sand pack were monitored to understand the wettability of the core as the flood progresses.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it