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Record W4284970001 · doi:10.1190/int-2021-0205.1

Characteristics and main controlling factors of dolomite reservoirs in the Upper Cambrian Sanshanzi Formation, eastern Ordos Basin, China

2022· article· en· W4284970001 on OpenAlexaff
Chunlin Zhang, Fengcun Xing, Yueqiao Zhang, Bin Zhang, Xiaoquan Chen, Gu Qiang

Bibliographic record

VenueInterpretation · 2022
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsPetro-Canada
Fundersnot available
KeywordsDolomiteGeologyLithologyOutcropStructural basinCarbonateGeochemistryDolomitizationPorosityPermeability (electromagnetism)Petroleum reservoirGeomorphologyPetrologyPaleontologyFaciesGeotechnical engineering

Abstract

fetched live from OpenAlex

Abstract The Cambrian system in the Ordos Basin has a similar development degree of carbonate strata to that in the Sichuan and the Tarim Basins; however, no significant oil and gas breakthroughs similar to those in the latter two basins have been made in the Ordos Basin yet, and the characteristics, genesis, and differences in the reservoir need to be explored. Field outcrop observations reveal that the oil and gas shows are common in the Upper Cambrian Sanshanzi Formation in the eastern Ordos Basin, indicating important oil and gas exploration potential. Analysis of the characteristics and genesis of dolomite reservoirs can greatly support the exploration and development of the Cambrian carbonate oil reservoirs in the Ordos Basin. Based on the field outcrop observations and comprehensive laboratory tests and analyses, the reservoir characteristics and main control factors are systematically discussed. This study reveals that the reservoir lithology mainly comprises crystalline dolomite, from fine crystalline dolomite to coarse crystalline dolomite; this results in reservoirs with low porosity, extreme-low porosity, and ultralow permeability dominated by intergranular denudation, caves, and microfractures. They can be further divided into two types of reservoirs: type I reservoirs that have low porosity, ultralow permeability, and medium pore-throat radii, and type II reservoirs that have extreme-low porosity, ultralow permeability, and small pore-throat radii. The physical properties of fine-medium crystalline and medium crystalline dolomite reservoirs are slightly better, and the throats tend to be larger with increasing grain size. The reservoirs have not experienced deep burial processes; dolomitization mainly occurs in the marine-sourced fluid environment with weak oxidation and weak reduction, influenced by the atmospheric fresh water and thermal fluid transformation during the late period to some extent, whereas the hydrocarbons mainly charged during the late period. The crystalline dolomite in residual grains superimposes the denudation and cataclasis in the epigenetic karst stage that are the main controlling factors of the reservoirs. The crystalline cataclasis of dolomite can aid in the formation and reconstruction of the reservoirs. The spatial and temporal distribution laws of the reservoirs and key formation periods need to be studied further.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.158

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.216
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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