Diagenetic Control of Reservoir Performance and Its Implications for Reservoir Prediction in Jinci Sandstone of Upper Carboniferous in the Middle East Ordos Basin
Bibliographic record
Abstract
The Upper Carboniferous sandstone reservoir is a vital replacement area for natural gas exploration in Ordos Basin. In this study, 157 Jinci sandstone samples were selected to conduct a series of experiments and analyses. The reservoir material composition and pore structure analysis shows that the lithology of the reservoir is mainly quartz arenite, followed by sublithic arenite. The detrital particles are mainly quartz (69-97.5%), followed by rock fragments (0.1-24.5%), and the content of feldspar is less than 0.01%. The cement consists of siliceous material, clay minerals, and carbonate, with averages of 2.34, 5.96, and 1.81%, respectively. Three types of pore-throat structures (HPMI curve: types 1, 2, and 3) are identified in the Jinci sandstone reservoir, corresponding to different pore-throat radius distributions (RCP curves: types A, B, and C). The study of the factors affecting reservoir pore structure and its internal mechanism shows that the reservoir pore-throat combination, affecting the reservoir performance, is mainly controlled by deposit composition and the subsquent diagenetic modification. A higher rigid particle content and an appropriate amount of siliceous cementation (2-10%) would lead to resistance of the compaction, in favor of the preservation of primary intergranular pores. When the content of ductile particles is more than 3%, the original intergranular pores tend to be substantially reduced. The deposit composition of sandstone controls the preservation of residual intergranular pores by affecting the intensity of compaction and dissolution controlling the amount and type of cementation. Compared with dissolution-subjected quartz arenites, the sublithic arenites are characterized by a common occurrence of altered kaolinite and recrystallized illite, which would destroy the reservoir property. The early diagenetic carbonate cementation, as well as the strong siliceous cementation in "sedimentary quartz arenite", are unfavorable to the formation of high-quality reservoirs. Then, on the basis of the characteristics of various diagenesis and their interaction and internal relationship, the diagenetic sequence and diagenetic-pore evolution patterns of different types of reservoirs were established. Finally, according to the lithological characteristics and the diagenetic-controlled pore-throat evolution patterns of different types of reservoirs, the reservoir quality in the study area was predicted.
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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 | 0.000 |
| 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".