In Situ Bitumen Viscosity and Saturation Estimation From Core Log Integration for Canadian Oil Sands
Bibliographic record
Abstract
Abstract Canadian oil sands contain bitumen with viscosity above 100,000 cP at in-situ conditions. Thermal recovery of this oil requires knowledge of both the oil and water saturation profile, and also the oil viscosity profile in the reservoir. A core-log integration program was conducted for in-situ viscosity and saturation estimation. Two wells were logged with NMR and other special petrophysical logs. Core samples on these wells were taken for lab NMR and other special core analyses, with the goal of calibrating the logging tool outputs against the laboratory core data. Lab NMR measurements were conducted on both core and extracted bitumen samples at different temperatures (12, 20, 50, and 80 °C). Viscosities were also measured for the bitumen samples at these same temperatures. Results show that when viscosity is higher than 100,000 cP, oil viscosity is no longer sensitive to T2 geometric mean, but it still strongly correlates to a parameter defined as the relative hydrogen index (RHI) of the oil (Bryan et al., 2003). RHI is a convenient way of expressing how much of the signal is lost due to the rapidly relaxing components that are not fully captured by NMR equipment. This is also consistent with LaTorraca's (1999) findings, but in the Canadian oil sands the bitumen samples have viscosity values much higher than the heavy oil samples studied by LaTorraca. These results demonstrate that, while in heavy oils the oil mean relaxation time is a valuable parameter for predicting in-situ viscosity, in bitumen formations the RHI term will be the primary NMR parameter for predicting oil viscosity. The results from the lab NMR have been integrated with NMR and other petrophysical logs for viscosity and saturation estimation. A workflow is developed for core-log integration. First, oil/water T2cutoff values were calibrated using Dean-Stark core saturation and lab NMR measurements to establish the separation between oil and water signals in the spectra. Then the water amplitude and oil apparent amplitude were calculated from the NMR log using the calibrated T2cutoff. Finally, water saturation and RHI were computed from the amplitude; while oil viscosity was computed from the RHI using the correlations developed from core-log integration. The output from this study is a combined calculation of fluid saturations, oil viscosity and an indication of variability in pore size distribution within the formation. This allows for an improved understanding of optimal locations for well placement and the expected growth of the steam chamber within the reservoir during thermal operations.
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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".