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Record W1987387464 · doi:10.2118/100065-ms

Rate-Time Flow Behavior of Heavy Oil From Horizontal and Multilateral Wells

2006· article· en· W1987387464 on OpenAlexaffabout
M. D. Fetkovich, G. E. Petrosky, C. B. Hughesman, R. P. Sawatzky

Bibliographic record

VenueSPE/DOE Symposium on Improved Oil Recovery · 2006
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsConocoPhillips (Canada)
FundersConocoPhillips
KeywordsPermeability (electromagnetism)GeologyPetroleum engineeringTransient analysisExponentFlow (mathematics)Transient (computer programming)Exponential functionMechanicsPetrologySteady state (chemistry)MathematicsPhysicsChemistryComputer science

Abstract

fetched live from OpenAlex

Abstract This paper examines the behavior of heavy oil reservoirs developed with horizontal and multilateral wells. Advanced decline curve analyses were used to characterize flow regimes and estimate the time to pseudosteady-state. Reservoir and well parameters such as the OOIP, Arps "b" exponent, decline rate, reserves, permeability and well productivity indices were also determined. Example analyses are presented for single, dual and triple lateral wells from heavy oil fields located in Venezuela and Canada. All wells exhibit a characteristic extended transient linear flow regime followed by an exponential decline. Similar results were obtained whether the analyses were performed on single, dual or triple lateral wells. Interference between laterals was not observed.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.003
GPT teacher head0.181
Teacher spread0.178 · 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 designObservational
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

Citations5
Published2006
Admission routes2
Has abstractyes

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