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Record W2749583876 · doi:10.1071/aj14108

South West Hub CCS Project: Lessons to be learned from the 2014 3D seismic survey

2015· article· en· W2749583876 on OpenAlexaboutno aff
Martin P. Burke, Dominique Van Gent

Bibliographic record

VenueThe APPEA Journal · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsSeismic surveyBaseline (sea)Scope (computer science)Quarter (Canadian coin)Government (linguistics)Geological surveyProcurementDrillingEnvironmental resource managementEnvironmental planningEngineeringMining engineeringGeologyBusinessGeographyEnvironmental scienceComputer scienceArchaeologySeismology

Abstract

fetched live from OpenAlex

The South West Hub (SWH) project is Australia’s first carbon capture and storage (CCS) flagship project. Managed by the WA government’s Department of Mines and Petroleum (DMP), the SWH is assessing the geological properties of a proposed CO2 storage site in the southwest of WA to determine its feasibility. This includes collating detailed geological information, partnering with researchers, acquiring baseline data, consulting with communities and stakeholders, and negotiating land access. Recent activities have included a 2D seismic survey in 2011, drilling of a stratigraphic well (Harvey–1) in 2012 and a comprehensive (115 km2) 3D seismic survey in 2014. A further drilling program is planned for the fourth quarter of 2014 until the first quarter of 2015. The 2014 3D seismic survey has been described as one of the most complex land-based seismic surveys conducted in Australia due to environmental factors, and competing land use and land access constraints. This extended abstract reviews the recent 3D seismic survey, including the development of the project’s scope and procurement processes through to community engagement and implementation, and outlines how the lessons are being incorporated into the upcoming drilling program. It will also discuss legacy issues that have impacted on community attitudes and confidence, and the challenges of working with potentially hostile communities, and also demonstrate how the project adopted and adapted best practice engagement guidelines and toolkits for CCS projects to achieve successful outcomes.

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)0.002
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.294
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.003

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 head0.159
GPT teacher head0.332
Teacher spread0.173 · 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 designNot applicable
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
Published2015
Admission routes1
Has abstractyes

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