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Record W2133288648 · doi:10.1190/tle31050526.1

Introduction to this special section: Seismic inversion for reservoir properties

2012· article· en· W2133288648 on OpenAlexaff
Reinaldo J. Michelena, William N. Goodway, Tad M. Smith

Bibliographic record

VenueThe Leading Edge · 2012
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsCalgary Laboratory ServicesUniversity of Calgary
Fundersnot available
KeywordsGeologyPetroleum engineeringHydraulic fracturingSection (typography)Inversion (geology)PetrologyReservoir modelingFluid pressureGeotechnical engineeringGeomorphologyEngineeringStructural basinComputer science

Abstract

fetched live from OpenAlex

Among all possible rock properties, reservoir engineers reserve the distinguished title of “reservoir properties” to pore volume, fluid type, and connectivity because of their direct impact in the economics of hydrocarbon reservoirs. In some reservoirs, engineers may be able to alter the original in-situ properties by applying additional processes to stimulate the matrix (with hydraulic fracturing, for instance) or to push the hydrocarbon out (by injecting some other fluid). Then, the rock and fluid properties that control the outcome of these induced processes become as important as the basic, more traditionally distinguished properties mentioned at the beginning. In any case, it is the geoscientist's job to understand how these properties vary within the reservoir to fully realize its economic potential.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0360.025

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 head0.021
GPT teacher head0.227
Teacher spread0.206 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations0
Published2012
Admission routes1
Has abstractyes

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