T-R Cycle Characterization and Imaging: Advanced Diagnostic Methodology for Petroleum Reservoir and Trap Detection and Delineation
Bibliographic record
Abstract
Characterization of stratigraphic sequences (T-R cycles or sequences) included outcrop studies, well log analysis and seismic reflection interpretation. These studies were performed by researchers at the University of Alabama, Wichita State University and McGill University. The outcrop, well log and seismic characterization studies were used to develop a depositional sequence model, a T-R cycle (sequence) model, and a sequence stratigraphy predictive model. The sequence stratigraphy predictive model developed in this study is based primarily on the modified T-R cycle (sequence) model. The T-R cycle (sequence) model using transgressive and regressive systems tracts and aggrading, backstepping, and infilling intervals or sections was found to be the most appropriate sequence stratigraphy model for the strata in the onshore interior salt basins of the Gulf of Mexico to improve petroleum stratigraphic trap and specific reservoir facies imaging, detection and delineation. The known petroleum reservoirs of the Mississippi Interior and North Louisiana Salt Basins were classified using T-R cycle (sequence) terminology. The transgressive backstepping reservoirs have been the most productive of oil, and the transgressive backstepping and regressive infilling reservoirs have been the most productive of gas. Exploration strategies were formulated using the sequence stratigraphy predictive model and the classification of the known petroleum reservoirs utilizing T-R cycle (sequence) terminology. The well log signatures and seismic reflector patterns were determined to be distinctive for the aggrading, backstepping and infilling sections of the T-R cycle (sequence) and as such, well log and seismic data are useful for recognizing and defining potential reservoir facies. The use of the sequence stratigraphy predictive model, in combination with the knowledge of how the distinctive characteristics of the T-R system tracts and their subdivisions are expressed in well log patterns and seismic reflection configurations and terminations, improves the ability to identify and define the limits of potential stratigraphic traps and the stratigraphic component of combination stratigraphic and structural traps and the associated continental, coastal plain and marine potential reservoir facies. The assessment of the underdeveloped and undiscovered reservoirs and resources in the Mississippi Interior and North Louisiana Salt Basins resulted in the confirmation of the Monroe Uplift as a feature characterized by a major regional unconformity, which serves as a combination stratigraphic and structural trap with a significant stratigraphic component, and the characterization of a developing play in southwest Alabama, which involves a stratigraphic trap, located updip near the pinchout of the potential reservoir facies. Potential undiscovered and underdeveloped reservoirs in the onshore interior salt basins are identified as Jurassic and Cretaceous aggrading continental and coastal, backstepping nearshore marine and marine shelf, and infilling fluvial, deltaic, coastal plain and marine shelf.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".