Successful Applications of Pressure-Rate Deconvolution in the Cad-Nik Tight Gas Formations of BC Foothills, Canada
Bibliographic record
Abstract
Abstract The Cadomin-Nikanassin (Cad-Nik) sandstone formations in the lower Cretaceous reservoirs along the reverse thrust faulting belt of North Eastern British Columbia, Canada, have emerged in the recent years as a new tight gas play. The low porosity (3% ~ 6%) of the rock matrix controls gas storativity, while the presence of natural fractures in the form of clusters or swarms allows significant and sustainable flow rates for commercial productions. Newly drilled wells are commonly hydraulically fractured to establish or enhance wellbore connectivity to the natural fracture network. Seismic mappings of these structural unconventional gas reservoirs provide the early assessments of resource sizes and initial gas-in-place (IGIP), which usually bear huge certainties due to the difficulty of determining reservoir structural closures and pay porosity cutoffs. Regional analogue wells are often used to guide development decisions. Meanwhile estimating connected reservoir volumes through conventional gas material balances (P/Z vs. cum production) and production data analysis (RTA) has not been without challenges. Fairly long pressure buildups, on the order of 100's of hours, are often performed without seeing any pressure stabilization. The applicability of pressure extrapolation to these tests has not been systematically investigated. Thus, reliable average reservoir pressure estimates require much longer well shut-in times in order to perform meaningful gas material balance. Since this is not practical, confidence in material balance results requires a second, independent method for establishing connected well volumes to be used in comparisons and cross-checking. One possible choice is rate-transeint analysis (RTA) but, in these fields, many times well head pressure data are also unavailable or unreliable. This paper presents two field case studies, which demonstrate the successful application of the pressure-rate deconvolution approach combining a well's long, high quality production rate history with accurate downhole pressure data from relatively short buildup tests. This approach allows the reservoir engineer to (1) reconcile the performance based EUR estimates with the volumetric OGIPs, (2) establish, at least, minimum well drainage size and connected volume and (3) pick possible infill-drilling opportunities. A final benefit is that this often leads to a better understanding of well/reservoir parameters.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".