The effects of diagenesis on the petrophysical and geochemical attributes of the Asmari Formation, Marun oil field, southwest Iran
Bibliographic record
Abstract
Abstract The distribution of good reservoir quality and its causes is the main challenges in carbonate reservoir characterization. This study investigates the effects of diagenetic processes on the reservoir quality of the carbonate successions of the Asmari Formation, in the Marun oil field, southwest Iran. The study applies an integrated approach including core petrography, petrophysical rock typing, stable carbon and oxygen isotopes as well as major and trace elements analyses. Petrographic studies and geochemical analyses express that the Asmari limestones have been affected mainly by compaction, dissolution, recrystallization, calcite and anhydrite cementation and dolomitization. Among those diagenetic overprints, dolomitization and dissolution played an important role to enhance the reservoir quality of the formation. Moreover, four types of dolomites were recognized and the rate of dolomitization increases toward the top of the Asmari carbonate successions. Possible models for dolomitization include mixing zone, brine reflux, seepage reflux and tidal pumping of seawater. Employing Flow Zone Index and Discrete Rock Type concepts led to classification of the Asmari reservoir into seven reservoir rock types. Integrating reservoir rock typing with petrographic studies and geochemical analyses also confirms that reservoir quality of the Asmari Fm. would have been mainly controlled by diagenetic processes. Moreover, stable isotopes, trace elements and facies analyses support the idea that carbonate intervals of the Asmari Formation were deposited in a warm, shallow-water environment under a saline condition.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".