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Record W6945075869 · doi:10.21420/qnd0-6663

Opportunities for underground geological storage of CO2 in New Zealand : report CCS-08/11, monitoring and verification methodologies

2024· article· en· W6945075869 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsCarbon capture and storage (timeline)Baseline (sea)Containment (computer programming)Greenhouse gasCarbon sequestrationProcess (computing)Plume

Abstract

fetched live from OpenAlex

Monitoring and Verification of carbon dioxide (CO2) stored in sub-surface rock formations will be an integral part of potential geological sequestration projects in New Zealand. Its primary purposes are to track the location of the injected CO2 plume in the subsurface and to detect any CO2 seepage from the primary seal through to the overlying strata and to provide assurance that none of the injected CO2 is reaching the ground surface (or sea bed). Information arising from Monitoring and Verification (M & V) offers a means of managing the injection process so that, for example, reservoir pressures and CO2 migration rates remain within predefined limits. Monitoring and Verification is important because it provides assurance to stakeholders that the storage process is safe, will not have detrimental impacts on the environment or existing resources, and confers a benefit to the Earth’s climate by reducing greenhouse gas emissions. Legislation will be used to ensure that these requirements are met and that risks are minimised. M & V programmes could span 20 years or more, commencing prior to injection in order to establish baseline conditions and finishing when the storage site is closed. In New Zealand these programmes are expected to be similar to those conducted overseas at Weyburn (Canada) or Otway (Australia), for example, but may differ in detail due to our geological and cultural settings. The M & V techniques best suited to CO2 storage sites in New Zealand will depend on a number of factors including the type of storage (e.g., deep saline reservoir or depleted oil and/or gas reservoir), the depth of the storage container, the location of the site (e.g., relative to population centres, environmentally valuable areas, the location of other subsurface resources (oil, gas, coal, water and geothermal), local active faults, culturally important sites and the coastline), legislative requirements, public attitudes to Carbon Capture and Storage (CCS), and the economics of these projects. As no potential storage sites have so far been selected in New Zealand this report focuses on identifying those M & V techniques that are likely to be of most use, comprising general descriptions of the main techniques (in Appendix 1), discussion of their application and recommendations outlining techniques suitable for use in New Zealand. (auth/DG)

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.193
Threshold uncertainty score0.627

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)0.0010.000

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 head0.210
GPT teacher head0.374
Teacher spread0.163 · 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 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

Citations3
Published2024
Admission routes1
Has abstractyes

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