MétaCan
Menu
← Back to cohort
Record W6930871234 · doi:10.5281/zenodo.16354619

Characterization of Onshore Formations in Nova Scotia for CO2 Storage

2024· article· en· W6930871234 on OpenAlexaffabout

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsGeological Survey of CanadaMemorial University of Newfoundland
Fundersnot available
KeywordsPermeability (electromagnetism)PorosityPetrographyCaprockLithologyCarbon dioxide

Abstract

fetched live from OpenAlex

Geological carbon storage is critical to meeting Canada’s long-term energy needs and climate goals. In Eastern and Atlantic Canada, we are just starting to assess potential geological CO2 storage sites. The Maritimes and Fundy Basins are large, under-explored Carboniferous sedimentary basins in Eastern Canada and are potential candidates for carbon storage. Mafic and ultramafic rocks offer additional potential carbon storage targets onshore in the region due to their ability to rapidly mineralize CO2, reducing leakage risk. Comprehensive CO2 storage assessment includes, but is not limited to, routine core analysis to evaluate storage capacity (porosity) and transmissibility (permeability). Detailed petrographic and mineralogical analysis is crucial to understand potential reactive transport (i.e., dissolution reactions between formation brine, acidified upon injection of CO2, and minerals in the target formation). In this study, we assess 20 core plug samples from the Boss Point Formation (sandstone) and North Mountain (basalt) in Nova Scotia for potential CO2 storage. Samples were trimmed to cylindrical shapes, cleaned, and dried to a constant weight difference of ≤ 0.01 g. Porosity was measured using a Helium pycnometer via gas expansion. Permeability was measured using a gas permeameter (steady state method), and then corrected for gas slippage with Klinkenberg correction approach. The mineralogical compositions of these samples were obtained using non-destructive methods of X-ray diffraction (XRD) and X-ray fluorescence (XRF). Porosity and permeability for the Boss Point sandstone were found to range from 10.2 to 18.4% and 0.01 to 3.4 mD, respectively. North Mountain basalt properties were much lower, with 2.7-6.4% porosity and 0.001-0.02 mD permeability. Mineralogical/composition knowledge of rock samples is essential for CO2 storage site selection and screening. Upon injection, CO2 dissolves in brine and subsequently carbonic acid forms. The lower pH aqueous phase can react with reservoir rock minerals depending on pressure, temperature, brine salinity and minerals type. Some minerals rapidly dissolve in the acidic brine, potentially leading to localized increases in porosity and permeability, and subsequently change the geomechanical properties. This could weaken the formation especially in the near injection wellbore region. On the other hand, precipitation and potential deposition of some minerals has been observed in the literature which subsequently decreases rock quality and hence damages the CO2 injectivity. These preliminary assessments are the first step toward screening these two formations for possible future CO2 storage and helping to determine CO2 storage capacity and efficiency to assess risks and optimize injection strategies.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.168
Threshold uncertainty score0.337

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.246
Teacher spread0.221 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)→Same topicImmune Response and Inflammation→French-language works237,207→