Quality grading system for tight sandstone reservoirs in the Quantou 4 Member, southern Songliao Basin, Northeast China
Bibliographic record
Abstract
Abstract A grading system for tight sandstone reservoir quality is needed to predict tight oil enrichment areas and assess the resources. To explore the establishment of the grading system, a variety of research methods, such as rate-controlled mercury injection, conventional mercury injection, contact angle measurement, and the mechanical equilibrium principle, are integrated to determine the upper and lower limits of the porosity, permeability, and pore-throat radius of tight sandstones and to establish a quality grading system. Based on the porosity ϕ, permeability K, and pore-throat size r properties of the studied samples from the K1q4 Member, five sandstone classes have been identified. Three of these classes are tight sandstone reservoirs and include (1) high-quality tight sandstone reservoirs (ϕ=9%−12%, K=0.1−1.0 mD, and r=0.063−0.4 μm), (2) effective tight sandstone reservoirs (ϕ=6%−9%, K=0.05−0.1 mD, and r=0.0063−0.063 μm), and (3) low-quality tight sandstone reservoirs (ϕ=4%−6%, K=0.01−0.05 mD, and r=0.0004−0.0063 μm). Sandstones with ϕ, K, and r parameters higher than the high-quality tight reservoirs are deemed to be conventional reservoirs, whereas those with parameters lower than the low-quality tight sandstone reservoirs are considered as nonreservoir sandstones. It is also noted that oil saturation of the tight sandstone reservoirs correlates positively with the throat radius rather than with the pore size. High-quality tight sandstone reservoirs are usually developed in the distributary channel sand bodies near faults and/or fractures, and they are capable of producing more petroleum.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".