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Record W4231056841 · doi:10.2118/2004-286

Integration of the CANMET Hydrocyclone In a Conventional Heavy Oil Treatment Facility

2004· article· en· W4231056841 on OpenAlexaboutno aff
Khalid Al Hashmi, H.A. Hamza

Bibliographic record

VenueCanadian International Petroleum Conference · 2004
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsHydrocycloneEnvironmental scienceComputer scienceWaste managementEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract The CANMET hydrocyclone is high-performance separation unit developed to de-oil a variety of oily fluid streams, including high-water-cut wellhead production. A large number of heavy oil wellhead production streams in western Canada contain water in excess of 70% by volume. In conventional processing schemes, the production stream is chemically treated and heated in a gravity separation vessel to produce a concentrated oil stream, which is further treated in a heater treater unit to reduce the water content to achieve pipeline specifications. The CANMET hydrocyclone offers a technically and economically advantageous alternative for the treatment of these production fluids. Hydrocyclones separate fluids of differing densities by means of strong centrifugal forces generated internally without the use of moving parts. The CANMET hydrocyclone combines a number of unique design features that result in enhanced performance in a variety of applications compared to conventional designs. These patented features include balanced multiple inlets that improve separation efficiency in all applications, an adjustable overflow orifice that allows the operator to optimize unit performance for changing feed characteristics, and the capability to remove suspended solids in a separate stream. This paper discusses important features of the CANMET hydrocyclone and how it can be integrated with conventional equipment to enhance separation efficiency and reduce treatment time in existing facilities. Results from field trials are presented to show the benefits that can be achieved by integrating the CANMET hydrocyclone into conventional treatment scheme. Introduction Oil recovery techniques often yield fluids containing large proportions of water and solids. Effective removal of these contaminants is essential to meet specifications (0.5% BS&W) for pipeline transportation of crude oil product. The free-water knockout vessel (FWKO) is the standard unit used for removal of the solids (sand and similar particles) and bulk water from heavy oil fluids before they are treated to pipeline specifications in a heater treater. An alternative to the FWKO vessel, the liquid-liquid hydrocyclone, offers effective separation at a substantially lower cost with the potential to handle a wide range of separation problems. The first liquid-liquid hydrocyclone design was developed by Prof. Martin Thew at the University of Southampton, U.K. in the late 1960s, which began an evolutionary process of technological advancement in oily water separation that has continued ever since. In 1983 a single hydrocyclone test unit designed by Prof. Thew was used in oil recovery trials in Australia and proved extremely successful. The demand for hydrocyclone technology has been growing ever since that initial success. As a result of efforts by government and industry, the hydrocyclone has come to be recognized as one of the most efficient methods of oily water separation in the world. In the 1990s, in collaboration with Prof. Thew, CANMET began development work on an advanced hydrocyclone design that would be capable of treating difficult-to-separate oily fluids encountered by the heavy oil industry in western Canada. Successful field testing of the newly patented design known as the CANMET hydrocyclone in Saskatchewan and Alberta eventually led to commercial installations in western Canada.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.533
Threshold uncertainty score0.923

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 head0.016
GPT teacher head0.221
Teacher spread0.206 · 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 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

Citations2
Published2004
Admission routes1
Has abstractyes

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