Understanding Volumetric Sweep Efficiency in SAGD Projects
Bibliographic record
Abstract
Abstract An understanding of volumetric sweep and capture efficiency are critical to optimizing SAGD projects. Capture efficiency refers to how much mobilized and heated oil is actually produced. Volumetric sweep efficiency can be estimated reasonably well for SAGD pilots having an abundance of information. A rich data set may include geological, petrophysical, production, injection, pressure, temperature observation and 4D seismic data. With this information, excellent insight into steam chamber development can be assessed. However, determining volumetric sweep and optimal strategies is a problem where data are sparse. This paper summarizes analytical SAGD surveillance methods that estimate volumetric sweep and presents a work flow that can help optimize SAGD processes with limited data. Although the methods each have their assumptions and are not perfect, there is general agreement. The various techniques are corroborated using public core, injection/production, temperature observation and 4D seismic for the Surmont and Christina Lake pilot projects. Introduction Evaluating reservoir performance through the surveillance of production data is an excellent reservoir management tool. For waterflooding, this can be achieved through a conformance plot(1) that indicates how efficiently net water throughput affects recovery. Associating a water balance with an oil balance enhances the understanding of the influx/efflux of fluids and outer boundary losses out of zones. The plot works well for waterfloods because of the low compressibility of the fluids. For SAGD, a similar surveillance principle using abundant data is applied. However, a material balance alone is not definitive because SAGD is an energy-intensive process where steam is required to reduce the oil viscosity to a point where it will flow. Therefore, accounting for the energy within the SAGD process provides a different perspective for multiple geologies and heterogeneities. Typical objectives of SAGD surveillance using production and monitoring data are to determine: Original oil in place (OOIP) Remaining oil in place (ROIP) Mobile ROIP distribution and current condition (saturation, temperature and pressure) Limiting factors in recovery Potential improvements to economic oil recovery Recovery profile and optimizing recovery factor Operating strategies to achieve better volumetric sweep
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".