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Record W13095835

Development of an Integrated System for the Simulation and Assessment of Produced Water Discharges from Offshore Platforms

2012· dissertation· hu· W13095835 on OpenAlexaboutno aff
Lin Zhao

Bibliographic record

Venuenot available
Typedissertation
Languagehu
FieldEngineering
TopicMarine and Offshore Engineering Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceSubmarine pipelineOutfallPollutantPollutionEnvironmental engineeringMarine engineeringEngineering
DOInot available

Abstract

fetched live from OpenAlex

Techniques for modeling of marine pollution have been studied for decades. Specialized modeling methods have been used to simulate the dispersions of pollutants from offshore outfalls. Produced water, the largest volume waste stream discharged from offshore oil and gas production activities, is a complex mixture of dissolved and particulate organic and inorganic chemicals including metals and hydrocarbons. In recent years, the growing importance and interest in the ocean environment assessment has urged further evaluation of produced water impacts on the marine ecosystem. This thesis study describes an integrated system for the modeling and assessment of produced water discharges in coastal area. The system integrates ocean circulation simulation, pollutant fate and transport modeling that couples near field mechanisms and far field processes, and risk assessment approaches where exposure risks and probabilistic risks are evaluated. 
\nA literature survey is first introduced to review and present capabilities and limitations of the most widely used methods and models associated with assessment of the impact of marine pollution. This review identified the need for an integrated system with configurations of numerical schemes of Princeton Ocean Model (POM) for ocean circulation simulation, a Lagrangian method to simulate near field transport processes in three dimensional cross flows, and a numerical solution for far field transport modeling. The physical models are dynamically integrated to ensure mass and energy conservation. Furthermore to assess risks, a modified Monte Carlo method which uses a statistical model to establish the relationship between uncertainty parameters and output concentrations is integrated with physical modeling system along with risk characterization approaches to map risk levels. 
\nEvaluation and field validations are conducted for each individual sub-models and for the overall integrated modeling results. Specifically, the near field model is validated against a field study performed in USA platform located about 100 miles of New Orleans Louisiana. The computational efficiency and accuracy of the far field model are evaluated through test cases in comparison with concentration distribution results generated from an exact analytical solution and a RWPT (Random Walk Particle Tracking) method. Validations of ocean circulation results and the integrated produced water dispersion results are conducted in a case study carried out on the Grand Banks of Newfoundland, Canada. Validations show good performance of the developed modeling system which is used to provide satisfactory 3D simulation of marine pollutant dispersion for effective assessment and management of offshore waste discharges. Finally, a risk assessment is carried out to predict risks associated with predicted lead and benzene concentration resulting from potential future produced water discharges in the East Coast of Canada. This research study provide a tool for the modeling of complex transport processes in the coastal area, and improved methods for risk assessment of produced water impacts on the regional water environment.

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 score0.224
Threshold uncertainty score0.969

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.022
GPT teacher head0.281
Teacher spread0.259 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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