Hydrate mitigation for subsea production multiphase pipeline by flow assurance approach

Hartono, Kartika Fajarwati; Ginting, Mimpin; Sulistyanto, Djoko; Karono, R

doi:10.1088/1757-899x/434/1/012188

Cited by 3 publications

(2 citation statements)

References 2 publications

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“…Various studies have utilized multiphase simulation to predict hydrate free zone and assess inhibitor sensitivity [11]. Kamarudin, [12] compared the performance of MEG with TEG by process modeling using the Aspen Hysys simulation package. The result of testing methanol and mono-ethylene glycol in a reactor shows that adding 10% inhibitors to the reactor can prevent hydrates formation [13].…”

Section: Introductionmentioning

confidence: 99%

Prediction of Optimum Hydrate Inhibitors Mass Percent for Hydrate Formation Prevention

Kinate,

Igwe,

Elikee

2023

Journal of Earth Energy Science, Engineering, and Technology

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The production tubing and pipeline have the critical task of transporting economically significant fluids. As a result, they must be meticulously designed to manage potential issues like gas hydrate formation that can lead to blockage of the pipeline. In this study, the OLGA dynamic multiphase simulator and Multiflash were employed to determine the optimum mass percentages of thermodynamic inhibitors- namely, methanol, monoethylene glycol (MEG), diethylene glycol (DEG) and triethylene glycol (TEG) that are necessary to prevent hydrate formation within the pipeline. The pipeline model was developed using OLGA and Multiflash to characterised the fluid properties and generate the requisite input files (hydrate and PVT table files) for dynamic multiphase simulation with OLGA. Sensitivity analyses were performed to determine the optimum mass percent of methanol, MEG, DEG, and TEG required to suppress hydrate formation in the pipeline. Different mass percent of 10%, 20% 30%, 40%, 50%, 60%, 70%, 80% and 90% of the four inhibitors were introduced into the pipeline to evaluate their impact on hydrate volume fractions and locations along the pipeline at where hydrate attains thermodynamic stability. Addition of the inhibitors was stopped when the system exhibited conditions of no hydrate volume fraction. Result shows that the optimum mass percent for complete hydrate inhibition was 60% for methanol, 45% for MEG, and 70% for TEG inhibitors in the pipeline. DEG showed reduced hydrate fraction but did not inhibit formation effectively even at 90%. It was observed that as the inhibitor mass percent increases, the hydrate dissociation temperature (the temperature below which the hydrate will form) is reduced for a given pressure. Consequently, Monoethylene glycol (MEG) with an optimal mass percentage of 45% was the most efficient inhibitor for curbing hydrate formation within the given pipeline, surpassing the performance of other inhibitors and offering potential cost saving.

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Section: Introductionmentioning

confidence: 99%

Prediction of Optimum Hydrate Inhibitors Mass Percent for Hydrate Formation Prevention

Kinate,

Igwe,

Elikee

2023

Journal of Earth Energy Science, Engineering, and Technology

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“…When guest molecules are trapped inside a cage-like structure consisting of water molecules, gas hydrates form [1]. Methane (CH 4 ), ethane (C 2 H 6 ), propane (C 3 H 8 ), nitrogen (N 2 ), carbon dioxide (CO 2 ), and hydrogen sulfide (H 2 S) are the most important guest molecules that form gas hydrates [2,3]. Gas hydrates are part of the clathrate hydrate group, widely spread in nature.…”

Section: Introductionmentioning

confidence: 99%

Development of a Prediction Model for Gas Hydrate Formation in Multiphase Pipelines by Artificial Intelligence

et al. 2022

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A prediction model is developed by means of artificial neural networks (ANNs) to determine the gas hydrate formation kinetics in multiphase gas dominant pipelines with crude oil. Experiments are conducted to determine the rate of formation and reaction kinetics of hydrates formation in multiphase systems. Based on the results, an artificial intelligence model is proposed to predict the gas hydrate formation rate in multiphase transmission pipelines. Two ANN models are suggested with single-layer perceptron (SLP) and multilayer perceptron (MLP). The MLP shows more accurate prediction when compared to SLP. The models were predicted accurately with high prediction accuracy both for the pure and multiphase systems.

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Experimental investigation on the phase behaviour for gas hydrates in CO2 rich gas mixtures & multiphase system

Sayani

Khan²,

Pedapati

et al. 2022

Energy Reports

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Hydrate mitigation for subsea production multiphase pipeline by flow assurance approach

Cited by 3 publications

References 2 publications

Prediction of Optimum Hydrate Inhibitors Mass Percent for Hydrate Formation Prevention

Prediction of Optimum Hydrate Inhibitors Mass Percent for Hydrate Formation Prevention

Development of a Prediction Model for Gas Hydrate Formation in Multiphase Pipelines by Artificial Intelligence

Experimental investigation on the phase behaviour for gas hydrates in CO2 rich gas mixtures & multiphase system

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