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Record W4404619231 · doi:10.1002/ese3.1918

Experimental Study of Imbibition Characteristics During the Soaking Stage After Fracturing in Tight Reservoirs

2024· article· en· W4404619231 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnergy Science & Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Calgary
FundersNatural Science Foundation of Shandong ProvinceNational Natural Science Foundation of China
KeywordsImbibitionStage (stratigraphy)Petroleum engineeringGeologyFracturing fluidMulti stagePetrologyGeotechnical engineeringEngineering

Abstract

fetched live from OpenAlex

ABSTRACT The soaking stage is vital for oil production after fracturing in tight reservoirs. However, the roles and contributions of spontaneous imbibition (SI) and forced displacement imbibition (FDI) during this stage are poorly understood. This study gave an in‐depth insight on the imbibition characteristics during the soaking stage under non‐zero initial water saturation conditions by static soaking and dynamic waterflooding of the core. The results indicate that the fluid absorbed by SI in the core is short‐ranged. After SI, there is still a substantial amount of remain oil (30.7%) that can be displaced by subsequent FDI. SI considerably drives oil recovery in small pores (10–100 nm), whereas FDI is more effective in large pores (500–1000 nm). Controlling the rate of fracturing water flowing into the matrix from the fracture can enhance the combined effect of SI and FDI. For reservoirs with high initial water saturation, enhancing FDI effect during the soaking stage is favorable for oil production.

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.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.288
Threshold uncertainty score0.698

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.004
GPT teacher head0.213
Teacher spread0.209 · 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