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Record W4280533368 · doi:10.1071/aj21163

Industry-wide learnings from the independent review of Australia’s most complex decommissioning program

2022· article· en· W4280533368 on OpenAlexaboutno aff
Alasdair Gray, Chris Wilson

Bibliographic record

VenueThe APPEA Journal · 2022
Typearticle
Languageen
FieldEngineering
TopicMarine and Offshore Engineering Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNuclear decommissioningGeneral partnershipLegislationEngineeringEnforcementAbandonment (legal)BusinessEnvironmental planningFinanceWaste managementPolitical scienceEnvironmental scienceLaw

Abstract

fetched live from OpenAlex

In 2019, the Minister for Resources and Northern Australia issued a Statement of Expectations to the National Offshore Petroleum and Safety Environmental Management Authority (NOPSEMA) establishing heightened expectations for duty holder compliance with their decommissioning obligations. In response, NOPSEMA increased compliance monitoring and enforcement activities to assess adequacy of the level of decommissioning planning and implementation by duty holders. On 20 May 2021, NOPSEMA issued a general direction to Esso Australia relating to their Bass Strait decommissioning program, likely one of Australia’s most significant and complex decommissioning projects. The direction included a requirement to undertake an independent review of Esso’s engineering and project management approach and consider if there were opportunities for reducing the timeframe to commence and subsequently complete all necessary decommissioning activities. This review was subsequently awarded to Xodus, in partnership with Labrador and focussed on core disciplines such as project management, regulatory approvals, stakeholder engagement, well plugging and abandonment, contracting, topsides and subsea facilities and waste management. Australia is at a pivotal stage in the context of decommissioning oil and gas infrastructure. With heightened regulatory oversight alongside recent and continuing changes to legislation, ensuring supply chain is ready to deliver against this backdrop will be critical to the future success of regional decommissioning and ensure all parties bearing the cost of this work are satisfied. This paper will discuss the independent review process of Esso’s decommissioning program and outline key challenges and opportunities the industry faces in realising improved decommissioning efficiency in the region.

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)0.179
metaresearch head score (Gemma)0.293
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.179
Threshold uncertainty score0.949

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1790.293
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0090.007
Science and technology studies0.0040.005
Scholarly communication0.0120.007
Open science0.0030.007
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0030.002

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 head0.032
GPT teacher head0.279
Teacher spread0.247 · 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 designQualitative
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
Published2022
Admission routes1
Has abstractyes

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