Concentric hydrocarbon accumulations in deep rift basins: A case study of Jizhong and Huanghua depressions, Bohai Bay Basin, China
Bibliographic record
Abstract
ABSTRACT Deep rift basins are geological environments that can contain large resources of petroleum and can be particularly rich in unconventional oil and gas reserves. However, due to deep burial and complex geological conditions, the occurrences and distributions of hydrocarbon are not easily delineated, which seriously hampers the exploration process. Based on comprehensive analyses of the exploration process and hydrocarbon accumulation characteristics in the deep basin of the Jizhong and Huanghua depressions in Bohai Bay Basin, it was found that the hydrocarbon accumulations appear to be distributed in a concentric pattern. The interplay among tectonics, sedimentation, and hydrocarbon generation-migration in the deep basin determines the distribution of hydrocarbon accumulation. The inner tectonic zone formed by the deep trough area is mainly defined by the deposition of (semi) deep lacustrine mudstone, which forms retained shale reservoirs. In the outer tectonic zone, prodelta (fan) and (fan) delta front fine-grained strata deposited within the low-middle slope area and shallow lake and the subsequent deposition of (fan) delta plain sandstone bodies form intercepted stratigraphic and lithologic reservoirs. Conventional and unconventional reservoirs are distributed in a concentric order. The mechanisms and patterns of concentric hydrocarbon accumulation in deep basin settings can provide useful analogs for oil and gas exploration in deep basins with similar structures, particularly for unconventional oil and gas resources.
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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 | 0.001 |
| 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".