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Record W2018278727 · doi:10.2118/167149-ms

Wellbore Efficiency Model for CO2 Geological Storage Part II: Wellbore System

2013· article· en· W2018278727 on OpenAlexaff
Ahmad Nabih, Richard J. Chalaturnyk

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsWellborePetroleum engineeringLeakage (economics)AquiferPermeability (electromagnetism)EngineeringGeotechnical engineeringGroundwater

Abstract

fetched live from OpenAlex

Abstract Storing carbon dioxide (CO2) in deep geological formations is one part of the carbon capture and storage (CCS) process that is defined as geological CO2 sequestration or CO2 geo-sequestration. Injecting CO2 into a reservoir does not guarantee safe storage because CO2 could leak back to the surface and/or may contaminate specific strata where other energy, mineral and/or groundwater resources are present. Two mechanisms control assurance of storage integrity, which are geological leakage mechanism and wellbore leakage mechanism (Espie, 2005). Wellbore element was presented as a basic unit for developing a model of an entire wellbore system. This paper is the second to assess the performance of a wellbore system for geological storage purposes. The analytical model adopts concept of sequence scenarios of possible leakage paths, concept of wellbore efficiency for storage purposes and concept of the reference state. A new analytical model for modeling leakage through a wellbore system has been proposed. The analytical model represents the wellbore system as serially connected wellbore elements. This provides an advantage that each element can differ from the subsequent one and will have its own characteristics. Effective wellbore permeability also can change from element to another. The effect of site formation arrangement between general system and repeated aquitard-aquifers is investigated and compared. The analytical model is validated with the results of Nordbotten et al. (2004).

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.558
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

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)0.0190.003

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 head0.019
GPT teacher head0.235
Teacher spread0.216 · 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; both teacher heads agree on what is shown here.

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
Published2013
Admission routes1
Has abstractyes

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