Determination of Principal In-Situ Stress Magnitude from Well Logs in Unconventional Reservoirs: A Practical Application in Willesden Green Field, Canada
Bibliographic record
Abstract
Abstract A methodology to determine and delimitate the magnitude of the principal in-situ stresses in the Glauconite Formation of the Willesden Green Field in the Western Canada Sedimentary Basin (WCSB) is presented. The result is used to correlate with several failure scenarios including confirmation of hydraulically fractured zones and to optimize net stress conditions for drilling and wellbore stability. Geomechanical rock properties (Poisson's ratio, Young's Modulus, Biot vertical constant, rock strength, and the coefficient of angel friction) and the minimum horizontal stress (Shmin) are calculated from well logs. The Mohr failure criteria is considered in other to determine possible failure magnitude of normal stress. Based on the minimum horizontal stress, the magnitude of the maximum horizontal stress (Shmax) is delimited. This permits estimating failure magnitudes of normal, reverse, strike-slip faulting planes, wellbore and tensile breakout scenarios. Based on the theory of wellbore equilibrium, the Shmax is calculated in the fractured interval. This is corroborated with different failure scenarios predicted with the Mohr-Coulomb envelopes, and the unconfined rock strength (UCS) estimated from well logs. The stress polygon that describes the in situ stress magnitudes limitations before failure for the Willesden Green Field is elaborated, and defines a very low-stress zone in the highly gas saturated and permeable interval. The polygon is suitable for drilling design and geomechanical analysis, particularly in those intervals where wellbore stability may be a problem. The methodology can have practical and wide application in several fields where the predictions are limited due to restricted geomechanical information. The approach permits a quick delimitation of in-situ stresses valuable in those reservoirs with wellbore stability problems due to abnormal pressures.
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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".