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Record W2345626009 · doi:10.2523/iptc-17987-ms

Effect of Liquid Hydrocarbon on the Deposition of Gas Hydrate Particles in Gas-Dominated System

2014· article· en· W2345626009 on OpenAlexaff
Kyuchul Shin, Juwoon Park, Young Hoon Sohn, Yutaek Seo

Bibliographic record

VenueInternational Petroleum Technology Conference · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsClathrate hydrateFlow assuranceHydrateMethaneNatural gasDeposition (geology)Chemical engineeringHydrocarbonHydrogenChemistryPetroleum engineeringMaterials scienceGeologyOrganic chemistrySediment

Abstract

fetched live from OpenAlex

Abstract Deposition of hydrate solids is one of important parts to understand the hydrate plugging mechanism in the flowlines. In this study, hydrate segregation and deposition of three different gas-dominated systems, which are water only, decane as a condensate with water, and poly-vinyl caprolactam as a kinetic inhibition polymer included systems, was investigated with measuring the torque of stirring liquid and hydrate phases. The torque – hydrate conversion curves provided some information to classify the hydrate formation process into several specific regions and to characterize each region. The present work suggests that measuring torque is one of useful laboratory scale measurements to investigate the hydrate deposition mechanism and the block properties. Introduction Gas Hydrates are ice-like nonstoichiometric crystalline solids which contain plenty of gas guest molecules in their hydrogen-bonded host water cavities [1]. In nature, huge amounts of gas hydrates containing natural gases are deposited in deep sea sediments or permafrost [2], thus methane recovery from the hydrate deposits has been one of major issues for future energy resources [3–5]. On the other hands, the formation of gas hydrates in the pipelines has been a serious concern in the oil and gas industry because it can cause blockages of flowlines leading to severe operational and safety problems [2,6]. For flow assurance of offshore flowlines transporting hydrocarbons or gases, injecting thermodynamic hydrate inhibitors (THIs) such as methanol or ethylene glycol has been most commonly used in order to prevent gas hydrate formation, as the hydrate equilibrium curve is shifted toward higher pressure and lower temperature than operation conditions [2]. However, the industry continues to explore deeper and colder region of undersea for fresh oil and gas sources and these conventional methods are facing difficulties such as larger injection and higher cost of THIs. Recent trends for flow assurance, thus, have moved from preventing hydrate formation using THIs toward risk management, that is, to allow hydrate formation in pipelines but delaying their nucleation or agglomeration to form a blockage, using kinetic hydrate inhibitors (KHIs) or anti-agglomerants (AAs) [2]. In order to prevent the plugging of hydrates in pipelines, deposition mechanism of hydrate should be understood. From laboratory scale measurements to field modeling, numerous studies for aggregation and agglomeration have been reported and their scenarios for different systems were suggested and developed [7]. To measure the cohesion adhesion force of hydrate particles and to observe hydrate particle aggregation using probe are typical attempts of laboratory experiments for understanding the agglomeration mechanism [8–11]. Torque measurement of fluid stirred in the reactor could be also one of useful methods to understand physical properties of agglomerated hydrate block in the laboratory scale measurements. However, just a few studies measured the torque to confirm whether or not hydrate blockage was formed in their system [12,13]. Here, this study focuses on the hydrate deposition of gas-dominated system containing decane as a condensate or poly-vinyl caprolactam (PVCap) as a kinetic inhibition polymer. The torque of stirring fluid was recorded during the hydrate formation and the deposition of hydrate solid was visually observed. This approach can provide a better understanding on the roles of a condensate and a kinetic inhibition polymer for plugging phenomena. Experiments A synthetic natural gas which was composed of 90 mol% CH4, 6 mol% C2H6, 3 mol% C3H8, and 1 mol% n-C4H10 was supplied by Special Gas (Korea). Decane was purchased from SIGMAALDRICH. Deionized water and PVCap (MW≈5000, purity 98.0 wt%) was used without further purification.

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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)0.001
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 score0.151
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.005
GPT teacher head0.210
Teacher spread0.205 · 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".

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Citations0
Published2014
Admission routes1
Has abstractyes

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