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Measurements of Thermodynamic Hydrate Inhibitor Methanol Partitioning in Methane at High Pressures

2025· article· en· W4415615148 on OpenAlexaff
Ahmad A. A. Majid, Michelle Li, Patrick J. Rensing, Douglas J. Turner, Carolyn A. Koh

Bibliographic record

VenueEnergy & Fuels · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsHydraTek (Canada)
Fundersnot available
KeywordsMethanolMethaneHydrateMethanol reformerSynthetic fuelNatural gasHydrocarbonThermodynamic equilibrium

Abstract

fetched live from OpenAlex

Methanol is one of the most common thermodynamic hydrate inhibitors (THIs) for offshore oil and gas production lines. Even with its widespread use, there are few data on methanol partitioning in the hydrocarbon phase at equilibrium due to the complexity of the measurements. Highly accurate data of methanol partitioning in hydrocarbons are crucial for various reasons. First, these data are needed to ensure that methanol is present in adequate amounts to be effective as a thermodynamic hydrate inhibitor. Methanol is effective at preventing hydrate formation only when it is present in the aqueous phase. Next, methanol portioning data are also needed to prevent the excessive injection of methanol in the flowline. Excess methanol in the flowline could cause corrosion to the pipeline and thus, reduce the integrity of the pipeline. Finally, the data are also needed to avoid large downstream processing issues. Specifically, oil/gas that is sent for processing needs to meet the downstream methanol specification. Contractors may be fined if the concentration of methanol is outside this specification. In this work, we performed measurements of the methanol portioning in the vapor methane phase using two different experimental apparatuses (high-pressure equilibrium flow and microfluidic). Each apparatus has its own advantages. The microfluidic system allows visual observation, and thus the first precipitation of methanol can be observed. However, the apparatus has a pressure limit of ∼11 MPa. On the other hand, the high-pressure equilibria flow system has a high-pressure limit (up to 34.5 MPa). This allows measurements to be performed at a high pressure, where currently there are limited reported values. In this work, methanol portioning measurements were conducted at various concentrations for methanol (90, 95, and 97 vol % methanol), a temperature of 40 °C, and pressures up to 34.5 MPa. In the microfluidic system, equilibrium compositions of methane, water, and methanol systems were measured at first liquid appearance using gas chromatography–mass spectrometry (GCMS). Results of these measurements showed that the compositions of methane, water, and methanol are consistent with the predicted values from simulation. Additionally, further analysis showed that in the vapor phase, the normalized methanol concentrations were consistent with the data reported by McGlashan and Williamson at both of the investigated experimental pressures. Similar investigations were also conducted in a high-pressure equilibrium flow system. Results of our measurements using the high-pressure equilibrium flow system showed that the mole fractions of water and methanol in the vapor phase were slightly higher than the predictions from simulation. However, the normalized methanol concentrations were consistent with the data reported by McGlashan and Williamson.

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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.227
Teacher spread0.215 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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