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Record W4313069715 · doi:10.1115/ipc2022-88861

Experimental Study of Natural Gas Hydrate Formation Kinetics and Inhibition in Brine and Water

2022· article· en· W4313069715 on OpenAlexaff
Farzan Sahari Moghaddam, Maziyar Mahmoodi, Edison Sripal, Majid Abedinzadegan Abdi, Lesley James

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsBrineHydrateClathrate hydrateChemistryFlow assuranceIsothermal processSalinityIonic bondingSeawaterChemical engineeringInorganic chemistryIonThermodynamicsGeologyOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Hydrates formed under high pressure and low-temperature pipeline conditions are a serious flow assurance challenge. Furthermore, there are uncertainties with respect to the performance of different hydrate inhibitors based on their type, hydrocarbon and brine compositions, and operating conditions. Considering the inhibiting effect of salt ions in the brine composition can benefit hydrate chemical management strategies by reducing the high quantities of inhibitors. This study experimentally evaluates the performance of kinetic and thermodynamic inhibitors and investigates the growth of hydrate under subsea pipeline pressure and temperature conditions. The effect of hydrate inhibitors was studied through a novel isothermal approach using varied brine compositions. Few studies such as Kakati et al. (2015) have focused on the inhibiting effect of multivalent ionic brine composition. Our study considers several multivalent ionic salts in formation brine and seawater including NaCl concentrations of 9.7 wt% and 2.4 wt%, compared to previous isochoric and isothermal studies relying only on one salt type. The influence of high and low salinity levels, including multivalent ionic salts, were evaluated, as they have been shown to be able to reduce the quantity of inhibitors used in hydrate chemical management strategies. The results were benchmarked against experiments using de-ionized (DI) water to capture the individual effect of the inhibitors and brine in inhibiting hydrate formation. Growth detection was also captured through image analysis to improve the understanding of hydrate kinetics in water and brine. The experimental results were evaluated according to hydrate equilibrium curves simulated using Calsep PVTsim Nova. A novel macro scale isothermal approach was applied in PVT Cell to investigate natural hydrate formation and growth in DI water and brine systems. The ability of i) a kinetic hydrate inhibitor (KHI) and ii) methanol as a thermodynamic hydrate inhibitor (THI) to inhibit hydrate formation was studied. A sudden drop in the pressure (indirect measurement) confirmed through visual observations (direct measurement) is applied to identify the hydrate formation point. Nine isothermal hydrate tests were conducted, with and without inhibitors, in DI water and brine systems. Results indicate that the KHI was best able to inhibit hydrate formation. KHI inhibited hydrate formation for more than 20 hours in the presence of formation brine at 4.8°C and 97 bar (>1400 psi). In the absence of an inhibitor, hydrate formation in water occurred during the pressurization step, at a pressure below 35 bar (500 psi). The hydrate mixture resulted in a sudden shift to darker colours upon formation, further grew, and agglomerated.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.209
Teacher spread0.202 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2022
Admission routes1
Has abstractyes

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