Stratigraphic and Sedimentological Characterization of An Unconventional Carbonate Deposit: An Example from the Late Cretaceous Shilaif Formation, United Arab Emirates
Bibliographic record
Abstract
Abstract The Late Cretaceous (Cenomanian) Shilaif Formation is an unconventional oil deposit located in the Emirate of Abu Dhabi in western United Arab Emirates (UAE). Presently, it is undergoing early-stage appraisal drilling and development. Due to the reservoir in its natural state having a very low permeability (well below 1mD), traditional primary recovery techniques cannot be used. Instead, extraction of the oil will occur via hydraulic fracking of the reservoir. To better optimize landing zone placement of horizontal wells, which in turn will help lead to improved design of the wells, operations require a thorough understanding of the depositional fabric and stratigraphic architecture of the reservoir. The Shilaif Formation represents a deep-marine carbonate succession deposited within an intrashelf basin. Using Arabian Plate boundary nomenclature present in offsetting wells from various offsetting countries, three primary sequences can be delineated (from oldest to youngest): K120 (Lower), K130 (Middle), and K140 (Upper). Each of these three sequences can be further sub-divided into lowstand (LST), transgressive (TST), highstand (HST), and falling stage (FSST) systems tracts and their corresponding parasequence sets. At the core level, massive bedded and bioturbated organic-rich carbonate facies in each of the three sequences frequently correspond with TST and early stage HST successions. Thin-sections reveal significant planktonic foraminifera and calcispheres. Biostratigraphic analysis of core samples suggests much of the organic material is a by-product of phytoplankton (algal) blooms. Conversely, massive bedded and bioturbated non-organic carbonate core facies in each of the three sequences commonly correspond with FSST and LST successions. Thin-section analysis reveals a higher abundance of fossiliferous fragments thus indicating sediment transport from adjacent platform margins into the basin. It must be noted that different combinations of these organic and non-organic facies, however, can occur within various systems tracts and therefore underpins the need to do detailed core logging and subsequent correlation across the field. Finally, many key stratigraphic surfaces are punctuated by examples of Glossifungities ichnofacies and their recognition in core are of critical importance towards building the basin model and understanding water benches.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".