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Record W2983545206 · doi:10.2118/199787-ms

Silicate-Activated Geopolymer Alternatives to Portland Cement for Thermal Well Integrity

2019· article· en· W2983545206 on OpenAlexaff
Eric van Oort, Maria Juenger, Xiangyu Liu, Michael McDonald

Bibliographic record

VenueSPE Thermal Well Integrity and Design Symposium · 2019
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsPQ Corporation (Canada)
Fundersnot available
KeywordsPortland cementGeopolymerFly ashMaterials scienceUltimate tensile strengthSodium silicateCasingBrittlenessCementWaste managementEnvironmental scienceComposite materialPetroleum engineeringGeologyEngineering

Abstract

fetched live from OpenAlex

Abstract Ordinary Portland cement (OPC) has been the material of choice for oil & gas well cementing and abandonment for many decades now. However, there are drawbacks to the use of OPC for cementing and abandonment purposes, particularly in wells with higher temperatures. OPC is brittle and does not re-heal when cracked. It is easily contaminated by mud and spacer fluids. Furthermore, it has relatively low tensile strength and low strength when bonding to rock formations and casing. Moreover, the production of OPC is the 2nd largest source of CO2 emissions in the world. At the CODA industry-affiliate consortium at the University of Texas at Austin dedicated to well construction, decommissioning and abandonment, work is ongoing to find technically superior alternatives to OPC. Particularly promising materials are so-called geopolymers, formed by activating an alumino-silicate material such as fly ash (a waste material that is often discarded) with an alkali. It was found that these geopolymer materials offer more ductile strength and failure behavior, considerable resistance to contamination, higher tensile strength and bond strength, and an ability to re-heal when damaged. The results obtained for geopolymers formed by activating flyash with potassium and sodium silicates indicate that these may be well-suited for achieving long-term thermal well integrity.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0020.001

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 head0.267
Teacher spread0.239 · 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.

Study designBench or experimental
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

Citations27
Published2019
Admission routes1
Has abstractyes

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