Effects of diabase intrusions on surrounding clastic rock reservoir in early diagenetic stages: A case study of the Early Permian Fengcheng Formation in the Dabasong uplift, Junggar Basin
Bibliographic record
Abstract
Abstract A stage of mafic magmatic activity occurred in Early Permian in the Dabasong Uplift of Junggar Basin, part of the magma intruded into the normal sedimentary and shallow buried fine sandstone to form diabase, and part of the magma erupted to form basalt. The surrounding fine sandstone just entered in the early diagenetic stage A when the magma intruded. The compaction of the surrounding clastic rock and rupture of a small number of clastic grains were caused by the extrusion of the magma intrusion. The presence of chemically deposited alkaline minerals such as calcite, dolomite, shortite, natural alkali, and northupite indicates an alkali lake sedimentary environment for the Fengcheng Formation. Primary alkaline minerals dissolved from the surrounding rocks were subsequently transported and precipitated to form cements. The formation of the calcite cements and calcite metasomatism resulted in considerable densification of the surrounding rock during early diagenesis and destruction of the reservoir quality. The mafic magma had abundant Fe2+ and Mg2+ ions and was deficient in K+ ions, resulting in large amounts of chlorite and iron precipitation in the surrounding rock mainly composed of clay. We have analyzed the influence of an ultrashallow intrusion on the surrounding clastic rock during the early diagenetic period, which provided a typical reference for establishing a systematic mechanistic model of how magmatic intrusions affect the surrounding rock.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".