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Record W2051392169 · doi:10.2118/161446-ms

Offshore Drilling Waste Discharge: Egyptian Environmental Regulations

2012· article· en· W2051392169 on OpenAlexaff
Ahmad Agwa, Rehan Sadiq, H Leheta

Bibliographic record

VenueAbu Dhabi International Petroleum Conference and Exhibition · 2012
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsSubmarine pipelineOffshore drillingPeninsulaDrillingMarine pollutionEnvironmental scienceDrilling fluidEnvironmental pollutionPetroleum engineeringPollutionGeologyOceanographyEnvironmental protectionEngineeringGeographyArchaeology

Abstract

fetched live from OpenAlex

Abstract Egypt is located in the Northeast of Africa where oil and gas (O&G) are produced offshore from the Gulf of Suez and the Southeast part of the Mediterranean. The O&G production in Egypt is distributed as follows: 70% Gulf of Suez, 16% Western desert, 8% Sinai Peninsula and 6% Eastern desert. Past O&G activities, refining and transport have resulted in chronic pollution in Egyptian offshore, and numerous environmental programs have been initiated to protect new development areas from the environmental impacts. The offshore drilling process uses drilling fluids (muds) and generates waste fluids and cuttings, which could be the largest discharges going into the receiving water bodies. Water-based drilling fluids are commonly employed for drilling in Egyptian offshore because of their expected environmental benign behavior in the marine environment. The main objective of this paper is to highlight relevant Egyptian environmental regulations and explain several options to manage offshore drilling wastes: offshore discharge, offshore down-hole injection and onshore disposal.

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: Empirical
Teacher disagreement score0.334
Threshold uncertainty score0.678

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 communication0.0000.001
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 head0.009
GPT teacher head0.197
Teacher spread0.188 · 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

Citations3
Published2012
Admission routes1
Has abstractyes

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