Precise 3D seismic steering and production rates in the Wilrich tight gas sands of West Central Alberta
Bibliographic record
Abstract
Abstract We evaluate the controls on production performance of the Wilrich tight gas sand play in West Central Alberta, and show that careful steering using 3D seismic to place the wellbore within the upper reservoir is the most important geophysical contribution to production outcomes. Geologic, geophysical, drilling, and production data from more than 20 wells are used in the analysis. The completion and production parameters within the study area are relatively invariant, creating a control experiment relative to other productivity factors. We thus isolate the effects of varying bottom hole pressures, porosity, wellbore length, number of stimulations, mud gas response, gamma ray measurements while drilling, mud weight, curvature, amplitude versus offset (AVO), amplitude versus azimuth (AVAz), velocity versus azimuth (VVAz), and position of the horizontal wellbore within the reservoir. These variables are treated separately and in a multivariate fashion to determine their relative and combined effect on the productivity of the wells. Several methods of statistical evaluation are used to test confidence in the results. The Wilrich sand is approximately 20-m thick, and it was expected that the multistage fracture stimulation would have minimized the importance of vertical permeability variations by adequately accessing the entire vertical reservoir section. Such is not the case; precise placement of the wellbore in the most permeable stratigraphy of the thin reservoir is of material importance. The pressure and porosity strongly affect the production performance, but to a lesser degree than vertical position within the reservoir. This suggests that stratigraphic concerns as they relate to permeability variation can be critical, even in thin fracture-stimulated reservoirs. Interesting relationships were observed between the AVAz and curvature measures, but neither they nor the AVO or VVAz attributes yielded statistically significant correlations to the production data.
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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".