Best Practices of Inline Tests and Deliverability Assessment in the Canadian Low Permeability Duvernay for Improved Design of Completion and Characterization of the Reservoir
Bibliographic record
Abstract
Abstract In March 2021, the Alberta Energy Regulator (AER) introduced a new directive on pressure and deliverability testing, providing updated guidelines for inline testing to match industry practices. The AER now receives from oil and gas operators flowback data from inline tests and absolute open flow (AOF) interpretations. After analyzing this data, the AER has developed best practices. Best practices resulting from this study are contrasted to published studies of the Duvernay Formation. Currently, the AER cannot obtain fracture geometry and other fracture parameters. With the addition of pressure data, this study will aid the AER in obtaining fracture geometry, such as half-length, and fracture parameters, such as stimulated reservoir volume (SRV), permeability and productivity parameters. The new interpretation will aid and enhance reserves assessment and improve our understanding of inter-wellbore communication. New descriptions using mathematical (analytical/numerical) methods allow improved design of completions and enhanced characterization of the reservoir. This technical paper provides fundamental equations along with inline test and AOF interpretation techniques, which can be easily replicated by subject matter experts. Eighty unconventional flowback submissions were analyzed and displayed for non-vertical and non-deviated wells in the Duvernay. Productivity indices were calculated using flowback information and the AOF-based C value-related index of productivity (PI). Fracture geometry, SRV permeability, and PI estimates all significantly affect characterization of the reservoir. Currently, the AER only uses production rates in its flagship report AEO. This study will enhance the Duvernay reserves evaluation by using rate transient analysis (RTA) along with pressure parameters, such as tubing/casing pressure. Results from the study will affect what industry could do not only in the Duvernay but also in similar low-permeability resource plays in the United States of America and elsewhere. Production and pressure data aids in the interpretation of flow regimes to determine the optimal separation between wells and designs of completions. Flowback information has been used before. However, our work is novel in how it applies to the Duvernay Formation, which has been target of many companies in Alberta, and the implications on reserves evaluation, completion design, and characterization of the reservoir.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".