Accommodation-controlled Systems-tract–specific Facies Partitioning and Resulting Geometric Development of Reservoir Grainstone Ramp-crest Shoal Bodies
Bibliographic record
Abstract
ABSTRACT High-resolution sequence-stratigraphic study from outcrop analogs and from the subsurface West Jordan San Andres unit shows that both stochastic and deterministic reservoir models can be greatly improved by accounting for (1) systems-tract–specific facies partitioning and (2) use of outcrop-based object data from comparable stratigraphic/accommodation settings. The application of systems-tract–specific facies partitioning was first described by Kerans and Fitchen along the Algerita Escarpment in the Guadalupe Mountains of west Texas and New Mexico. Both outcrop and subsurface models illustrate a high degree of facies-dependent compartmen-talization in San Andres carbonates as a result of a varying accommodation setting. Lateral changes in ramp-crest facies tracts parallel (along strike) and perpendicular to the dipping ramp platform should be expected in highstand and prograding tide-dominated sequences as defined by the position in the sequence framework through the use of systems-tract–specific facies partitioning. This study documents the degree of vertical and lateral heterogeneities that should be expected in reservoirs producing from highstand shoal complexes and also provides a predictive geometric relationship between shoal-body maximum thickness and expected maximum dip dimension. The determination of connectivity in productive shoal bodies is of utmost importance when designing secondary and tertiary recovery projects; therefore, having a method to predict shoal extent based on maximum thickness will provide a valuable tool for reservoir characterization in the San Andres. In addition, within the West Jordan unit, chronostratigraphic relationships were also found to control pore-type distribution as related to migrating facies tracts. Whereas many facies exhibit high porosity values, permeability ranges are abrupt in varying facies tracts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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 teacher head, 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".