Analytical Methods to Develop Accurate Structural Model for the Asmari Reservoir
Bibliographic record
Abstract
Crossing of Asmari can be a challenging endeavor in certain instances, particularly when dealing with structural complexities, compounded by the presence of a substantial layer of Gachsaran formation evaporates overlying the reservoir. The primary aim of this study was to establish a precise and comprehensive structural model for the Asmari reservoir. Utilizing geological logs for dip classification offers the advantage of directly depicting the structural origin. This approach helps in identifying the Asmari fault and fracture systems and their impact on production, ultimately resolving structural complexities. To investigate the reasons behind the intersection of the Kalhur member and the unexpected increase in the thickness of the Asmari formation, FMI data was acquired over the interval ranging from 1550m to 2065m. The analysis of picked bedding dips revealed abrupt variations in dip magnitude and azimuth reversals. These observations were pivotal in unraveling the structural intricacies of the reservoir. A significant fault was identified within zone five of the Kalhur member, and its interpretation suggests that it is a reverse fault. This conclusion is based on the observed dip pattern and the distinctive characteristics of the logs. Around the fault, the beds and layers exhibit elevated dips, largely attributed to the plastic nature of anhydrite and marly/shaly anhydrite within the formation. The anhydrite-indicator curve obtained from the FMI and gamma-ray logs provides further evidence that the well entered the Kalhur member after intersecting the major fault located within this particular zone. The interpretation of structural dip played a pivotal role in resolving structural complexities, leading to the precise determination of the well's location within the Asmari reservoir. This achievement was particularly critical as it enabled the well to reach the lower contact of the Asmari formation. This interpretation was facilitated by analyzing FMI images and petrophysical logs in well LL-26.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".