Gas Processing Journal

Artificial Intelligence-based Modeling of Interfacial Tension for Carbon Dioxide Storage

Amir Hossein Hosseini; Hossein Ghadery-Fahliyany; David Wood; Abouzar Choubineh

Volume 8, Issue 1 , January 2020, , Pages 83-92

https://doi.org/10.22108/gpj.2020.119977.1069

Abstract

A key variable for determining carbon dioxide (CO2) storage capacity in sub-surface reservoirs is the interfacial tension (IFT) between formation water (brine) and injected gas. Establishing ... Read More

Transparent Machine Learning Algorithm Offers Useful Prediction Method for Natural Gas Density

David Wood; Abouzar Choubineh

Volume 6, Issue 2 , October 2018, , Pages 1-14

https://doi.org/10.22108/gpj.2018.112015.1035

Abstract

Machine-learning algorithms aid predictions for complex systems with multiple influencing variables. However, many neural-network related algorithms behave as black boxes in terms of ... Read More

Plant-wide Simulation of an Integrated Zero-Emission Process to ‎Convert Flare Gas to Gasoline

Mostafa Jafari; Sadaf Ashtab; Alireza Behroozsarand; Kamran Ghasemzadeh; David A Wood

Volume 6, Issue 1 , January 2018, , Pages 1-20

https://doi.org/10.22108/gpj.2018.111048.1028

Abstract

The Gas to Gasoline (GTG) process includes conversion of natural, flare, and associated gas into synthetic fuels that can be compositionally upgraded and adjusted into different useful ... Read More The Gas to Gasoline (GTG) process includes conversion of natural, flare, and associated gas into synthetic fuels that can be compositionally upgraded and adjusted into different useful hydrocarbon fuels including gasoline, liquid petroleum gas (LPG), and fuel gas. Commonly, the GTG process involves three stages: 1) Synthesis gas (syngas) production unit 2) Methanol production unit 3) Methanol to Gasoline production unit (MTG). In this study, an integrated Flare Gas to Gasoline (FGTG) process for converting flare gas to gasoline, LPG and fuel gas is simulated using the Aspen HYSYS v. 8.8 simulator. The steam methane reforming (SMR) unit, the syngas to methanol unit, and the MTG unit are configured for simulation as an integrated FGTG process. In order to reduce carbon dioxide gas emissions to the atmosphere, a novel closed arrangement for the FGTG process (recycling configuration) is described and simulated. The simulation results demonstrate that by recycling all gas emissions, such as flare and off gas from the methanol and MTG units back into the process cycle, gasoline and LPG productivity can be increased on average by about 53% and 10%, respectively, compared to a base FGTG configuration that does not involve such recycling. The integrated simulation is supported by sensitivity analysis based on FGTG plants of various natural gas capacities (from 70,000 to 130,000 lb./hr.) as the adjustable (independent) variable and gasoline, LPG, and fuel gas selectivity as the dependent variables. Results of the simulation cases reveal that the total productivity of the integrated FGTG process could be increased in terms of flare gas mass flow, with the selectivity of products remaining approximately fixed for different plant capacities (i.e., at 75% for the gasoline product). Moreover, the utilities and energy consumption of the FGTG process is compared for several sensitivity cases. The results reveal that by increasing the capacity of the gas feed (natural gas mass flow) the Energy Index (i.e., total utilities consumption to product flow rate) decreased by about 8% and 47% in the base and recycling configurations, respectively. This finding suggests that an FGTG plant becomes more energy efficient at in higher-capacity plants.

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Author = Wood, David A

Artificial Intelligence-based Modeling of Interfacial Tension for Carbon Dioxide Storage

Abstract

Transparent Machine Learning Algorithm Offers Useful Prediction Method for Natural Gas Density

Abstract

Plant-wide Simulation of an Integrated Zero-Emission Process to ‎Convert Flare Gas to Gasoline

Abstract