Sedimentary Characteristics and Lithological Trap Identification of Distant Braided Delta Deposits: A Case on Upper Cretaceous Yogou Formation of Termit Basin, Niger
Bibliographic record
Abstract
Lithological trap identification in thin sand and thick shale layers is still a challenge for hydrocarbon exploration. Based on the high-resolution sequence stratigraphy theory and the establishment of high resolution sequence stratigraphy framework with seismic-well tie, the dynamic deposition process of braided river delta sands on late Cretaceous Yogou formation has been analyzed on 62 wells in passive rift Termit basin with multi-stages depressions and reversals. (1) Six kinds of sedimentary microfacies and three major reservoir sands with multi-stages stacking and lateral migration are in Yogou formation; (2) Based on Accommodation space/Sediments supply change and the deposition progress, sedimentary facies distribution in each member of YS3 sub-formation has been done according to sands thickness statistics of sedimentary micro-facies, narrow-time seismic attributes and slices analysis, multi-sources braided river delta depositional model has been concluded; (3) Based on source rock and caprock evaluation, with reservoir sands distribution and faults impact on Yogou formation of Termit basin, four types of traps, including structure-lithology, Structure-strata, stratigraphic and lithology are concluded. Traps influencing factors, i.e., structure geometry, sands distribution, paleotopography, stratigraphy cycling, sand/shale lateral connection, reservoir quality and so on, have different impacts on these traps, and different lithologic-stratigraphy traps have different exploration risks. Structure geometry and sands distribution are very important for the structure-lithology traps; structure geometry and paleotopography are the key factors in Structure-strata traps. Sands distribution and reservoir quality can be focused on lithology traps. Moreover, paleotopography and sand/shale lateral connection are significant on stratigraphic traps. Therefore, different hydrocarbon accumulation types of lithological traps have been established.
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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 | 0.000 | 0.000 |
| 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".