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Record W2133101896 · doi:10.1109/ccece.2002.1015279

Underground ultrasound probing for monitoring carbon dioxide flooding in oil producing reservoirs

2003· article· en· W2133101896 on OpenAlexaff
Ningyu Liu, Raman Paranjape, K. Asghari

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsPetroleum engineeringPorous mediumCarbon dioxideEnvironmental scienceReflection (computer programming)PorosityPosition (finance)Materials scienceUltrasoundProcess engineeringFossil fuelEnhanced oil recoveryComputer scienceAcousticsWaste managementGeologyEngineeringComposite materialChemistry

Abstract

fetched live from OpenAlex

The problem of identifying the position and location of immiscible or miscible layers is a critical issue in methods of carbon dioxide injection for oil producing bodies. Accurate knowledge of the position could lead to an ability to control the position of the carbon dioxide front affecting production, efficiency, economy, and, in the end, profitability. The approach of studying the progress of carbon dioxide in reservoirs using ultrasound is new and may lead to unique and powerful ways of monitoring the position of carbon dioxide, as well as visualizing the reality of the oil producing area. Firstly in this paper, some basic experiments to investigate the acoustic properties in many situations are described. These experiments include the ultrasound reflection properties of stationary water-air, water-oil, air-oil, oil-oil interfaces, as well as those of moving interfaces. Secondly, experiments of ultrasound reflection properties in porous mediums combined with air, water and oil are described. These experiments include reflection of air-water interfaces in porous mediums, oil-water interfaces in porous mediums, and air-oil interfaces in porous mediums. Thirdly, measures of digital signal processing are introduced to obtain position information of interfaces in porous mediums and improve the resolution and accuracy of the location. Ultrasound has many advantages as a tool in underground probing, such as small size, low power consumption and safety.

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 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)0.001
metaresearch head score (Gemma)0.001
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 score0.251
Threshold uncertainty score0.967

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.028
GPT teacher head0.275
Teacher spread0.246 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations2
Published2003
Admission routes1
Has abstractyes

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