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Record W4413391478 · doi:10.1115/omae2025-155238

Platform Drilling Life Cycle Assessment of Drilling Waste Handling

2025· article· en· W4413391478 on OpenAlexaboutno aff
Jan David Ytrehus, Arild Saasen, Ute Brönner, May Kristin Ditlevsen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMarine and Offshore Engineering Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDrillingPetroleum engineeringLife-cycle assessmentEnvironmental scienceComputer scienceEngineeringMechanical engineeringProduction (economics)

Abstract

fetched live from OpenAlex

Abstract Different methods to handle oil wet drill cuttings in a field development offshore Canada has been evaluated. The governing requirement is an upper limitation of 6,9% oil on cuttings for discharge to sea when an environmentally acceptable base oil is chosen. Methods that ensure that cuttings remain below this are evaluated primarily with respect to their environmental impact on air, sea and sea bottom. The conclusions are derived from a study including literature review, interview of relevant industry experts, and evaluation of existing reported studies and relevant equipment. Relevant equipment in this sense means equipment with impact on solids control and handling that there exists experience data from in conditions that can be compared to those this location. Dispersion modelling of relevant scenarios is performed. The dispersion modelling findings represent a key part of the conclusion. Five scenarios are evaluated. These include: 1. Skip and ship for onshore cuttings treatment 2. Shaker solution and dryer for additional treatment 3. Shaker and dryer with additional dryer in series 4. Thermal Desorption Unit (TDU) with partial direct disposal to sea instead of storage units 5. TDU processing for all generated cuttings in synthetic-based drilling fluid In the paper it is shown how, based on the review of the five scenarios, the best option for drilling platform wells offshore Newfoundland is scenario 2, shaker and dryer. This gives low emission to air, comparable marine discharge as well as requiring the lowest footprint on a platform.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.601
Threshold uncertainty score0.621

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)0.0000.000

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 head0.007
GPT teacher head0.236
Teacher spread0.229 · 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 designSimulation or modeling
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
Published2025
Admission routes1
Has abstractyes

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