GFREE i Approach to Geologic Characterization of "Tight Gas" Reservoirs
Bibliographic record
Abstract
Increasing demand for natural hydrocarbon gas, coupled with a steady reduction of conventional reserves in North America, has led to greater interest in what were formerly considered to be marginal gas reservoirs. Petroleum industry operators are becoming more interested in unconventional energy resources, out of which gas from tight reservoirs is one of the most important. Technical understanding and development of this type of reservoir is at a more mature stage in the US than in Canada. However, significant efforts are being conducted in Canada to quantify and develop the “tight gas” reserve potential which is suspected to be large. In this context, the GFREE team at the University of Calgary is working in concert with NSERC, AERI and Conoco Phillips to develop an interpretative workflow to characterize these reservoir rocks. The key input data for this analysis workflow are well cores, well logs, drill cuttings, outcrop studies and subsurface analog models based on present-day analogous environments. For this presentation we outline the geologic workflow followed by the GFREE team, which includes a detailed stratigraphic correlation, the definition of sedimentary facies and the petrographic characterization of the reservoir rocks. Porosity and permeability measurements are used to quantify the storage capacity and deliverability of each individual sedimentary body. Production data is included as a final constraint, in order to define the most favourable reservoir architecture combination among the previous analyzed geologic features. The GFREE workflow is currently being applied to the upper part of the Monteith Formation, the lowermost stratigraphic interval of the Late Jurassic – Early Cretaceous Nikanassin Group in the Deep Basin of Alberta (Stot, 1988; Miles et al, 2009). The study area corresponds to the southeast part of the Wapiti Field, approximately 400 Km NW of Edmonton. In this area and for this particular stratigraphic interval, the pore geometries and the distribution of sedimentary facies seem to be among the most important factors to define the quality of the reservoir intervals. The rock properties are affected by different diagenetic processes, and the later seem to be constrained by the boundaries of the sedimentary bodies, the sediment composition, and the tectonic history of the area.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".