Microseismic monitoring of a tight light oil reservoir: A case history in the Cardium Halo Play, Alberta
Bibliographic record
Abstract
The effectiveness of hydraulic-fracturing completions in a tight-oil play is investigated by detailed interpretation of microseismicity. The microseismic programs were acquired in the Cretaceous Cardium light oil sandstone reservoirs in Alberta, Canada. Events with magnitudes between [Formula: see text] and [Formula: see text] are located by downhole monitor wells to a maximum distance of 525 m, enabling inference of the fracture wing length, height, and azimuth based on event distribution. The fracture ports, one per stage, were located in an open-hole configuration that used external packers for zonal isolation. During completions, the ports were opened with ball-actuated frac sleeves. Event distributions indicated that, in some cases, fractures grew preferentially away from the Rocky Mountain deformation front. This inferred that fracture asymmetry is independent of the position of the monitoring array, indicating that it cannot be ascribed to observation bias and suggesting that the direction of fracture growth was dominantly influenced by the preexisting stress conditions in the reservoir. The distribution of microseismicity further indicates that isolated event clusters occur 30–50 m above the reservoir. These out-of-zone events are interpreted to have occurred on unpropped fractures. In comparison with gelled oil or foamed water, slickwater fracturing fluids are shown to produce more diffuse and scattered microseismic expression accompanied by better cumulative oil production. Taken together, the results of these studies indicate that the use of slickwater fracturing fluid, along with the reduced stage spacing and tighter interwell spacing, is expected to lead to higher initial production as well as higher estimated ultimate recovery.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".