Outcrop to subsurface reservoir characterization of the lower Mesaverde Group, Red Wash Field, Uinta Basin and Douglas Creek Arch, Utah and Colorado
Bibliographic record
Abstract
The Mesaverde Group (Late Cretaceous) at Red Wash Field within the Uinta Basin produces oil and natural gas from low-permeability, fluvial sandstone reservoirs that were deposited in a predominantly freshwater, low-energy setting with minor brackish-water influence. Four main architectural elements present in core and nearby outcrops include fluvial bars, crevasse splays, floodplain deposits, and coal. Depositional trends reflect an overall decrease in energy toward the northwest, where subsurface deposits are located on the periphery of the main channel belt, while contemporaneous outcrop deposits record more extensive brackish-water influence.\nStatic reservoir connectivity (total and constrained), assessed using 3-D reservoir models of the fluvial deposits at Red Wash Field, varies as a function of well density, sandstone-body geometry, and net-to-gross ratio (sandstone-body abundance). Results suggest that sandstone geometry produces a minor (6%) increase in total connectivity; however, the abundance of crevasse splays is a major contributor to total connectivity and should be considered as an important factor in reservoir development. Stratigraphic zones with < 40% net-to-gross ratio exhibit greater total connectivity (up to 81.8%) with higher well density. Above 40% net-to-gross ratio, only a minor increase (10-15%) in connectivity resulted. For porous sandstones (porosity > 6%), connectivity is, on average, 26% lower than total sandstone connectivity and is more sensitive to well density and net-to-gross ratio.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".