Integrated approach for fracture characterization of hydraulically stimulated volume in tight gas reservoir
Bibliographic record
Abstract
Hydraulic fracturing is conducted on unconventional reservoir which has very low permeability. It increases the production from unconventional oil and gas reservoirs through the creation of a connected stimulated rock volume (SRV) with higher conductivity. The permeability and the SRVs dimension are important parameters which increase the performance of hydraulically fractured wells. Microseismic monitoring is used to estimate the seismically stimulated volume within the reservoir, which can provide a proxy for the SRV. Finite element analysis was used in this study in the determination of SRV characteristics by utilizing field data from a horizontal well hydraulic-fracturing program in the Hoadley Field, Alberta, Canada. Coupled fluid-flow geomechanics finite element (FE) model was used. The permeability of the SRV is altered to match the field bottom-hole pressure. The pressure drop and in situ stress changes within the SRV are determined through the matching of the FE model. Fracture aperture, number and spacing in the SRV are then inferred from the estimated reservoir parameters by using a semi-analytical approach.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".