Overburden characterization with formation pore pressure and anisotropic stress field estimation in the Athabasca Basin, Canada
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Bibliographic record
Abstract
One of the challenges encountered during the life cycle of an oil-sand thermal-production reservoir is the prediction of the formation pore pressure and in situ stress regime during the assessment phase of the reservoir development and, more importantly, during the development phase. We have investigated the state of formation pore pressure and stress in the overburden — represented by the Clearwater Formation, Grand Rapids Formation, and Colorado Group — of a preproduction oil-sands reservoir situated in the Athabasca Basin of Alberta, Canada. Our methodology integrates pressure data from piezometers, stress data from mini-frac (MF), dipole sonic logs, and elastic properties obtained from multicomponent 3D seismic inversion data. It combines the Terzaghi effective stresses with the Schoenberg and Sayers elastic stiffness matrix for horizontal transversely isotropic fractured materials. The total principal stresses (vertical, minimum, and maximum horizontal stresses) are expressed as functions of the normal fracture weakness (anisotropic correction factor), formation pore pressure, seismic data (Lamé constants), and the Biot-Willis coefficient. The effective principal stresses are estimated from the equivalent total principal stresses and the formation pore pressure multiplied by the Biot-Willis coefficient. On all three overburden intervals analysed, the relations between principal stresses indicate a normal stress regime. The estimated total minimum horizontal stress matches the MF values within 10%. The formation pore pressure, along with the 3D seismically derived estimates of the total and effective principal stresses, allows for better assessment of the caprock integrity and for operational savings based on a reduced number of MF tests. It can also be used for stress estimation within the formations hosting aquifers, which is so important for thermal production. Understanding the subsurface on the reservoir area is important for efficient production, but knowing the subsurface of the overburden is equally important for reducing potential issues due to production.
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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 | 0.000 |
| 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 | 0.001 |
| 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 it