Using a Modified GOI Index (Effective Grid Containing Oil Inclusions) to Indicate Oil Zones in Carbonate Reservoirs
Bibliographic record
Abstract
The GOI (grains containing oil inclusions) index is used to distinguish oil zones, oil‐water zones and water zones in sandstone oil reservoirs. However, this method cannot be directly applied to carbonate rocks that may not have clear granular textures. In this paper we propose the Effective Grid Containing Oil Inclusions (EGOI) method for carbonate reservoirs. A microscopic view under 10× ocular and 10× objective is divided into 10×10 grids, each with an area of 0.0625 mm×0.0625 mm. An effective grid is defined as one that is cut (touched) by a stylolite, a healed fracture, a vein, or a pore‐filling material. EGOI is defined as the number of effective grids containing oil inclusions divided by the total number of effective grids multiplied by 100%. Based on data from the Tarim Basin, the EGOI values indicative of the paleo‐oil zones, oil‐water zones, and water zones are >5%, 1% 5%, and <1%, respectively. However, the oil zones in young reservoirs (charged in the Himalayan) generally have lower EGOI values, typically 3%–5%.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".