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Record W4405244929 · doi:10.46690/ager.2024.12.08

Evolution of rock pore structure and physical properties due to acidification: Recent advances and future perspectives

2024· article· en· W4405244929 on OpenAlexaff
Fangzhou Zhao, Xinghe Jiao, X. Xia, Sai Xu, Lei Sun, Yuxuan Xia

Bibliographic record

VenueADVANCES IN GEO-ENERGY RESEARCH · 2024
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsUniversity of Toronto
FundersChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsOcean acidificationGeologyEnvironmental scienceMaterials scienceClimate changeOceanography

Abstract

fetched live from OpenAlex

Acidification is crucial to oil and gas development, which effectively improves reservoir development by reacting acid with some minerals in the rock. There are a large number of minerals that react with acid in carbonate and shale reservoirs. Acidification has a good effect in these two reservoirs, so it is necessary to conduct multi-scale research on the acidification process. This work briefly introduces the evolution characteristics and factors affecting acidification on reservoir pore structure and physical properties, and also analyzes their similarities and differences. Meanwhile, the application status of the acidification method is also discussed. Finally, the challenges and opportunities faced by shale acidification are discussed, aiming to provide new insights into the development of acidizing technology. Document Type: Perspective Cited as: Zhao, F., Jiao, X., Xia, X., Xu, S., Sun, L., Xia, Y. Evolution of rock pore structure and physical properties due to acidification: Recent advances and future perspectives. Advances in Geo-Energy Research, 2024, 14(3): 238-240. https://doi.org/10.46690/ager.2024.12.08

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.546
Threshold uncertainty score0.377

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 head0.017
GPT teacher head0.297
Teacher spread0.280 · 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

Citations7
Published2024
Admission routes1
Has abstractyes

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