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Record W2917817055 · doi:10.2118/1206-0046-jpt

Overview: Production/Facilities (December 2006)

2006· article· en· W2917817055 on OpenAlexaff
Simon Richards

Bibliographic record

VenueJournal of Petroleum Technology · 2006
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsPetro-Canada
Fundersnot available
KeywordsCorrosionProduced waterEnvironmental scienceWaste managementPipeline transportProduction (economics)EngineeringBiomass (ecology)Sewage treatmentSewageEnvironmental engineeringNatural resource economicsGeologyMaterials scienceMetallurgy

Abstract

fetched live from OpenAlex

Welcome back to the Production/Facilities feature. This issue focuses on environmental and corrosion challenges. These challenges are especially important because the global production infrastructure is aging, with much of it more than 30 years old. These issues are, of course, intertwined because the materials and corrosion engineer spends much of his/her time preventing the produced fluids from escaping into the environment. This issue delves into new or revitalized developments in produced-water treatment. Concern has been mounting over the years regarding the effect on the environment of chemical treatments used by the industry when the chemicals are discharged with produced water, for example. New "green" corrosion inhibitors have been developed. As well as preventing corrosion in susceptible materials, the materials and corrosion engineer also must be able to assess the effect of any corrosion that has occurred. State-of-the-art calculation of the corrosion rate is available. Also, a new approach has been developed to assess the internal condition of a pipeline accurately. A low-cost water-purification treatment has been used in the sewage-treatment industry for many decades. It is being transferred to the petroleum industry. The use of reed beds is common as an alternative waste water treatment in remote areas. This method is being used in the Nimr field, onshore Oman. Essentially, the reeds capture the impurities through the root system, where they are held in the plant tissue. The plants then can be harvested and used as biomass fuel, for example, and the residual ash, which contains the inorganic impurities, can be disposed of safely. Production/Facilities additional reading available at the SPE eLibrary: www.spe.org SPE 100673 "Assessment and Comparison of CO2-Corrosion Prediction Models" by R.C. Woollam, BP plc, et al. SPE 98854 "The Path to Zero Flaring in Zadco" by M.M. Misellati, Zadco, et al. SPE 100412 "Prediction Equation of CO2 Corrosion With the Presence of Acetic Acid" by M.C. Ismail, U. Teknologi Petronas, et al. SPE 103922 "Internal-Corrosion Direct Assessment for Multiphase-Flow Pipeline Systems" by P.G. Puente, SPE, Scandpower PT, et al. IPTC 10548 "Produced-Water-Management Strategy Water-Injection Best Practices—Design, Performance, Monitoring" by A.S. Abou-Sayed, Advantek Intl. Corp., et al.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score1.000

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)0.0010.000

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 head0.013
GPT teacher head0.249
Teacher spread0.236 · 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.

Study designBench or experimental
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
Published2006
Admission routes1
Has abstractyes

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