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Record W2787901442 · doi:10.1306/0108181613217061

Determination of static and dynamic characteristics of microscopic pore-throat structure in a tight oil-bearing sandstone formation

2018· article· en· W2787901442 on OpenAlexaff
Guangfeng Liu, Yaoxing Bai, Daihong Gu, Lu Yang, Daoyong Yang

Bibliographic record

VenueAAPG Bulletin · 2018
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsUniversity of ReginaPetroleum Technology Research Centre
Fundersnot available
KeywordsGeologyBearing (navigation)Tight oilPetrologyGeotechnical engineeringMineralogyPetroleum engineeringPaleontologyOil shaleCartography

Abstract

fetched live from OpenAlex

ABSTRACT In this study, an integrated and practical framework has been developed to quantify the static and dynamic characteristics of microscopic pore-throat structure in a tight oil-bearing sandstone formation. Experimentally, thin sections were prepared out of core samples collected from a tight formation, and corresponding analyses were performed by using the scanning electron microscopy and x-ray diffraction techniques. In addition to pore types and clay minerals, the size, fraction, and distribution of grains were identified and classified. Pore and throat size distributions were then determined by using pressure-controlled mercury injection and rate-controlled mercury injection, respectively, to quantify the changes in microscopic pore-throat structure after brine-flow tests. Subsequently, displacement experiments of water flooding and surfactant flooding were performed to determine the upper and lower cutoff value of the movable throat radius. Rock grains primarily containing fine sand and silt were found to possess complex compositions, and both intergranular pores and intragranular dissolution pores were dominant. Nanothroats may have developed in a tight formation because of small radii of pores and throats. Compared with the pore size distribution, throat radius was found to be reduced by 13.9% after brine-flow tests, and the cutoff value of movable throat can be decreased to 0.019 from 0.033 µm by using a surfactant.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.752
Threshold uncertainty score0.310

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.004
GPT teacher head0.213
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations45
Published2018
Admission routes1
Has abstractyes

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