MétaCan
Menu
Back to cohort
Record W2138273374 · doi:10.1002/ente.201402039

Water Loss Versus Soaking Time: Spontaneous Imbibition in Tight Rocks

2014· article· en· W2138273374 on OpenAlexaff
Qing Lan, Ebrahim Ghanbari, Hassan Dehghanpour, Robert Hawkes

Bibliographic record

VenueEnergy Technology · 2014
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsImbibitionPetrophysicsPetroleum engineeringGeologyOil shaleHydraulic fracturingPorosityTight gasGeotechnical engineeringTight oilPetrology

Abstract

fetched live from OpenAlex

Abstract The combined application of multilateral horizontal drilling and multistage hydraulic fracturing has successfully unlocked unconventional tight hydrocarbon reservoirs. However, the field data show that only a small fraction of the injected water during hydraulic fracturing treatments is recovered during flowback operations. The fate of nonrecovered water and its impact on hydrocarbon production are poorly understood. This paper aims at understanding the relationship between water loss and rock petrophysical properties. It also investigates the correlation between water loss and soaking time (well shut‐in time). Extensive spontaneous imbibition experiments are conducted on downhole samples from the shale members of the Horn River Basin and from the Montney tight gas formation. These samples are characterized by measuring porosity, mineralogy and TOC. Further, a simple methodology is used to scale up the laboratory data for predicting water imbibition volume during the shut‐in period after hydraulic fracturing operations.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.002
GPT teacher head0.173
Teacher spread0.171 · 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 source (direct Gemma or distilled Codex), 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

Citations93
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueEnergy TechnologySame topicHydraulic Fracturing and Reservoir AnalysisFrench-language works237,207