Methodology to predict natural gas in loading and unloading of compressed natural gas (CNG) operations

Beronich, Erika (2014) Methodology to predict natural gas in loading and unloading of compressed natural gas (CNG) operations. Doctoral (PhD) thesis, Memorial University of Newfoundland.

[img] [English] PDF - Accepted Version
Available under License - The author retains copyright ownership and moral rights in this thesis. Neither the thesis nor substantial extracts from it may be printed or otherwise reproduced without the author's permission.

Download (3MB)

Abstract

Exploiting stranded gas reservoirs, associate gas from offshore production platforms, condensate gas reservoirs may not be feasible using traditional approaches (i.e. pipelines) due to gas volumes, composition, location and/or climate. Marine Compressed Natural Gas (CNG) technology is a possible alternative; however, the required gas quality for CNG remains a challenge in commercial deployment. The optimal design conditions to safely and efficiently load, store, and unload CNG vessels are highly dependent on the quality of the gas. The objective of this work was to evaluate the impact of moderate/rich gases in CNG technology by performing dynamic simulations of the loading and unloading operations. It was demonstrated that existing Equations of State (EOS) are limited in accurately predicting the behaviour of the gas under load/unload conditions, particularly for gases with large heavy hydrocarbons content. Experiments with laboratory-synthesized gas samples were conducted using a PVT cell. The accuracy of the EOSs in predicting dew points, liquid dropout percentages, and gas densities was evaluated using the experimental data from the laboratory and literature. After tuning Peng-Robinson (PR) and Soave-Redlich-Kwong (SRK) equations to improve their predictions, their performance was evaluated using the HYSYS process simulator. A marked improvement in the EOS predictions was achieved by modifying a few EOS parameters. Dew point predictions were improved by adjusting binary interaction parameters (kij), the density predictions were improved by modifying the Peneloux parameters, and modifying both kij and Peneloux parameters enhanced the liquid dropout predictions. Dynamic simulations of the loading and unloading operations of a CNG tank were then performed to evaluate the effect of the heavy hydrocarbon content of the gases. Overall, removing all the heavier hydrocarbons appeared to produce very low temperatures during the unloading operation, while not removing these components caused an accumulation of liquids inside the tank at keel pressure. In addition, the simulation of the loading and unloading of a CNG tank was attempted in the laboratory using the PVT system; however, the attempt was unsuccessful as the system would require major modifications.

Item Type: Thesis (Doctoral (PhD))
URI: http://research.library.mun.ca/id/eprint/8092
Item ID: 8092
Additional Information: Includes bibliographical references (pages 194-201).
Keywords: Compressed Natural Gas (CNG), Peng-Robinson (PR), Soave-Redlich-Kwong (SRK), Tuning, EOS parameters, PVT cell
Department(s): Engineering and Applied Science, Faculty of
Date: October 2014
Date Type: Submission
Library of Congress Subject Heading: Compressed natural gas--Transportation--Mathematical models; Tankers--Loading and unloading--Mathematical models; Equations of state

Actions (login required)

View Item View Item

Downloads

Downloads per month over the past year

View more statistics