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Record W2022176583 · doi:10.1190/1.1817553

Instantaneous spectral analysis applied to reservoir imaging and producibility characterization

2003· article· en· W2022176583 on OpenAlexaff
Feng Shen, Gary Robinson, Tao Jiang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsPetro-CanadaCentennial College
Fundersnot available
KeywordsCharacterization (materials science)Spectral analysisReservoir modelingGeologyComputer sciencePetroleum engineeringMaterials sciencePhysicsNanotechnology

Abstract

fetched live from OpenAlex

PreviousNext No AccessSEG Technical Program Expanded Abstracts 2003Instantaneous spectral analysis applied to reservoir imaging and producibility characterizationAuthors: Feng ShenGary C. RobinsonTao jiangFeng ShenEP Tech, Centennial, CO, 80112, Gary C. RobinsonEP Tech, Centennial, CO, 80112, and Tao jiangPetroChina Oil Company, Chinahttps://doi.org/10.1190/1.1817553 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Permalink: https://doi.org/10.1190/1.1817553FiguresReferencesRelatedDetailsCited byRESEARCH AND APPLICATION OF IMPROVED HIGH PRECISION MATCHING PURSUIT METHOD6 February 2018 | Chinese Journal of Geophysics, Vol. 60, No. 5An Innovative Approach to 3D Fracture Modeling11 November 2012Enhanced Dynamic Simulation through Continuous Fracture Modelling of Carbonate Reservoir, Oman11 November 2012Application of Low-Frequency Energy Increment Technology in Hydrocarbon Prediction1 February 2012 | Advanced Materials Research, Vol. 472-475Research of Spectrum Decomposition Method Based on Physical Wavelet Transform and Its Application31 May 2013 | Chinese Journal of Geophysics, Vol. 52, No. 4An integrated approach for 3D seismic‐based reservoir characterization: An example of northern Chezhen Sag, Shengli OilfieldJun Li, Hongluo Wang, Shaoguo Yang, and Jianxun Yang15 December 2008Integrated Property and Fracture Modeling Using 2D Seismic Data: Application to an Algerian Cambrian Field11 November 2007Seismically Driven Improved Fractured Reservoir Characterization7 November 2004Improved Reservoir Simulation With Seismically Derived Fracture Models26 September 2004Methodology and application of seismic prediction of gas‐bearing volcanic reservoirChuanjin Jiang, Shumin Chen, Erhua Zhang, and Deying Zhong3 January 2005 SEG Technical Program Expanded Abstracts 2003ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2003 Pages: 2452 publication data© 2003 Copyright © 2003 Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished Online: 03 Jan 2005 CITATION INFORMATION Feng Shen, Gary C. Robinson, and Tao jiang, (2003), "Instantaneous spectral analysis applied to reservoir imaging and producibility characterization," SEG Technical Program Expanded Abstracts : 1406-1409. https://doi.org/10.1190/1.1817553 Plain-Language Summary PDF DownloadLoading ...

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: none
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.005
GPT teacher head0.201
Teacher spread0.195 · 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

Citations11
Published2003
Admission routes1
Has abstractyes

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