MétaCan
Menu
Back to cohort
Record W4407393252 · doi:10.1080/01932691.2025.2462697

Quantitative characterization of spontaneous and forced imbibition during soaking process in tight oil reservoirs

2025· article· en· W4407393252 on OpenAlexaff
Ziqing Liu, Long Xu, Shifan Wu, Hongyu Ding, Houjian Gong, Hailong Zhao, Hai Sun, Mingzhe Dong

Bibliographic record

VenueJournal of Dispersion Science and Technology · 2025
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsUniversity of Calgary
FundersNational Natural Science Foundation of China
KeywordsImbibitionPetroleum engineeringCharacterization (materials science)Tight oilProcess (computing)GeologyChemistryEnvironmental scienceChemical engineeringMineralogyMaterials scienceOil shaleAgronomyNanotechnologyEngineeringBiology

Abstract

fetched live from OpenAlex

During the soaking process after hydraulic fracturing in tight reservoirs, the imbibition between matrix and fracture is an important mechanism for enhancing oil recovery. The soaking pressure acts on the matrix-fracture system in the form of external pressure difference to establish a dynamic-imbibition process. In this study, a core-scale numerical model is developed based on experimental data to study the dynamic-imbibition mechanism under non-zero initial water saturation quantitatively. The simulation results show that the enhancement extent of capillary pressure to the matrix oil mobilization is more significant under conditions of higher external pressure difference. Furthermore, the contributions of spontaneous imbibition (SI) and forced imbibition (FI) to the mobilization of matrix oil are 8.74% and 91.24% respectively. Then, effects of the oil-water viscosity ratio (VROW), matrix initial water saturation (MIWS), and fracture on SI and FI are analyzed in depth. As the MIWS increases from 0.27 (bound water) to 0.3, SI and FI decrease by 64.43% and 10.01%. The increase of VROW, MIWS, and fracture number tends to enhance the contribution of FI. This work is pivotal for gaining profound insights into imbibition and improving tight oil recovery through hydraulic fracturing development.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.276
Threshold uncertainty score0.174

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.006
GPT teacher head0.251
Teacher spread0.245 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Dispersion Science and TechnologySame topicHydrocarbon exploration and reservoir analysisFrench-language works237,207