Particle-Size Analysis for the Pike 1 Project, McMurray Formation
Bibliographic record
Abstract
The unconsolidated sands of the Lower Cretaceous McMurray formation are the primary host of the Athabasca oil-sands deposit in Alberta, Canada. Alberta has one of the world’s largest nonconventional hydrocarbon resources with an estimated 1.8 trillion bbl of heavy oil (ERCB ST98-2013). The Pike 1 Project is a joint venture between Devon Canada Corporation (operator) and BP Canada Energy Group ULC. The Pike 1 Project is currently under a multiyear appraisal program to evaluate the McMurray bitumen resources that are amenable to steam-assisted gravity drainage(SAGD). In the Pike 1 Project area, the particle-size distribution (PSD) of the middle McMurray reservoir sands is highly variable because of the complex nature of the depositional environment. In order to understand the McMurray reservoir sands, Devon has exercised rigorous laboratory sampling and quality-control procedures to confirm the comprehensiveness of the PSD data set. By use of an unsupervised hierarchical classification technique, a dynamically growing self-organizing tree algorithm was used to cluster all of the PSD histograms from within the bitumen net-pay zone into one of four sand classes on the basis of similarity. Each sand class has a distinct PSD and permeability range. Using the sand classes, Devon extracted select intervals of core that closely matched the PSD histogram of each class to provide physical samples, termed “sandprints,” to fulfill sand-control-testing objectives. Further work included integrating the sand classes within the Pike 1 geological model, 3D permeability mapping, and upscaled sand-class volumes for SAGD well-pad optimization. This paper describes the process by which Devon has evaluated and classified the Pike 1 PSD data set into distinct sand classes within the unconsolidated middle McMurray reservoir. Devon’s methodology of acquiring these sands, necessary for sand-control testing, is also discussed in detail, emphasizing the overall effectiveness of the process. By use of this innovative PSD classification process as a supporting tool to reservoir characterization, Devon intends to realize the following benefits: • SAGD horizontal-well-pair placement optimization • A more methodical approach to laboratory testing of horizontal-liner technology for SAGD producers and injectors • Improved reservoir management
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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 | 0.002 | 0.002 |
| 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".