Pore Structure Characteristics and Influencing Factors of Tight Reservoirs Controlled by Different Provenance Systems: A Case Study of the Chang 7 Members in Heshui and Xin’anbian of the Ordos Basin
Bibliographic record
Abstract
The evaluation of pore structure is critical in understanding reservoir characteristics. This study aims to analyze the microscopic pore structure characteristics of tight reservoirs from various provenances through physical property analysis, casting thin sections, scanning electron microscopy (SEM), and constant−rate mercury injection. The pore throat parameters of the Chang 7 reservoir were analyzed and compared to those of the Xin’anbian and the Heshui areas. The results show that intergranular pores dominate the pore type of the Chang 7 reservoir in the Xin’anbian area, followed by feldspathic dissolution pores, with high-necked and tubular throat content caused by weak compaction and dissolution, respectively. On the other hand, feldspar dissolution pores dominate the pore type of the Chang 7 reservoir in the Heshui area, followed by intergranular pores, with a high content of tube−bundle throats caused by dissolution and flake−bent flake throats caused by compaction. The difference in pore parameters between the two blocks is minimal, but the difference in throat parameters is significant. Under the same permeability conditions, the throat radius distribution range of the Chang 7 reservoir samples in the Heshui area is narrower than that in the Xin’anbian area, with tiny throats contributing significantly to reservoir permeability. Sedimentary hydrodynamic conditions and diagenesis are the primary reasons for the differences in the pores, throats, and pore structure parameters of the Chang 7 tight reservoirs.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".