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Record W2000994408 · doi:10.2118/165480-ms

A New Method for Predicting Friction Losses and Solids Deposition during the Water-Assisted Pipeline Transport of Heavy Oils and Co-Produced Sand

2013· article· en· W2000994408 on OpenAlex
M. McKibben, Randall G. Gillies, R. Sean Sanders

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSPE Heavy Oil Conference-Canada · 2013
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of AlbertaSaskatchewan Research Council (Canada)
Fundersnot available
KeywordsPipeline transportAsphaltPetroleum engineeringPressure dropFoulingEnvironmental scienceFlow (mathematics)Volumetric flow rateGeotechnical engineeringDeposition (geology)Materials scienceViscosityGeologyEnvironmental engineeringComposite materialMechanicsSedimentChemistry

Abstract

fetched live from OpenAlex

Abstract In this paper, the results of a multi-year research project to develop reliable engineering scale-up models of water-assisted pipeline transport of heavy oils and bitumen are described. Empirical correlations currently in use do not properly account for the effects of flow rate and pipe diameter on friction losses. They account not at all for effects of water cut, temperature, oil viscosity or sand concentration. Additionally, sand accumulation in operating pipelines is a concern because no accurate method of predicting the conditions under which sand can be transported is available. In water-assisted pipeline transport, water present in the production fluid can form a layer that separates the oil-rich core from the pipe wall, thereby drastically reducing the energy required to transport the mixture. Alternately, small amounts of water can be added to provide the lubricating effect. A multi-year project to explore water-assisted flow regimes was sponsored by Husky Energy, Nexen Inc., Shell Canada Energy and four other heavy oil and/or oil sands producers. An extensive experimental test program was carried out in SRC's 50, 100 and 260 mm (diameter) pipeline flow loops, using oil/water/sand mixtures containing heavy oil, bitumen or a viscous lube oil. Measurements collected during the tests included the frictional pressure drop, thickness of the oil wall fouling layer and solids concentration distribution. The friction loss model developed as part of this project assumes that the flow is only partially lubricated by the water layer so that oil-oil contact at the pipe wall becomes more important as the water cut, superficial mixture velocity and/or ratio of oil-to-water viscosity decreases. The sand transport criterion developed here compares the particle terminal settling velocity to the friction velocity of the turbulent water layer. The models developed here provide accurate predictions for the scale-up, design and operation of water-assisted pipeline flow technology, which has significant potential to reduce the costs and environmental impact associated with heavy oil pro- duction and transportation.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.145
Threshold uncertainty score0.549

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 head0.015
GPT teacher head0.246
Teacher spread0.231 · 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