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The Relationship of Ultra-Low Permeability Sandstone Aspect Ratio With Porosity, Permeability

2014· article· en· W1921227989 on OpenAlexvenueno aff
Kun Ma, Xiang-an Yue, Xinxin Wang

Bibliographic record

VenueAdvances in petroleum exploration and development · 2014
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPorosityPermeability (electromagnetism)PorosimetryAspect ratio (aeronautics)Materials scienceGeologyPorous mediumMineralogyComposite materialGeotechnical engineeringChemistryMembrane

Abstract

fetched live from OpenAlex

The ultra-low permeability sandstone reservoir has large aspect ratio which significantly influences the multi-phase percolation characteristic. The ratio could be accurately measured by rate-controlled mercury porosimetry, but the testing technology is expensive, time-consuming and core-contaminating. There is not a simple effective method to describe the aspect ratio. The pores of the ultra-low permeability sandstone are mainly connected by the very long narrow throats, which could be advantageously simulated by the compound capillary bundles model. The analytical expressions of porosity and permeability about major pore structure parameters are established based on the model for the tight porous media. After solving the two expressions, the relationship between aspect ratio and parameter combination of porosity, permeability is obtained for the ultra-low permeable sandstone. Then the relation is fitted in this article using many previous published rate-controlled mercury data on compact sandstone and the relevance is strong, which proves that aspect ratio of tight rock is able to be calculated with its porosity and permeability. Key words : Ultra-low permeability sandstone; Aspect ratio; Pore; Throat; Porosity; Permeability

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.281
Threshold uncertainty score0.465

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.012
GPT teacher head0.234
Teacher spread0.222 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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".

Quick stats

Citations2
Published2014
Admission routes1
Has abstractyes

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