(72d) Improved Methodology to Handle Meteorological Data for LNG Projects | AIChE

(72d) Improved Methodology to Handle Meteorological Data for LNG Projects

Authors 

Chapeaux, M. - Presenter, Chevron Energy Technology Company
Huang, S. - Presenter, Chevron Energy Technology Company


For an LNG plant, on schedule delivery of contractual quantities of LNG is of critical importance due to the possible severe penalties for late or non-delivery. Ambient temperature variation can significantly influence LNG production and therefore, during the design phase of the project, it is important to include sufficient margins to account for these variations. However, overly generous margins can result in an inefficient plant and negatively impact the overall project economics. Nowadays, every project is faced with this difficult challenge of interpreting site ambient temperature variations and determining the impact it will have on its facilities.

Detailed site temperature data can be acquired from meteorological records. However, because LNG production is sensitive to ambient temperature conditions and not necessarily to the corresponding time period of the year, the respective meteorological data should be converted to temperature distribution functions. To carry out his procedure, most LNG projects will use average monthly temperatures and assume a normal distribution of the data throughout the year. However, more rigorous modeling of monthly average temperatures shows that the resulting annual distribution is not necessarily normal.

This work presents a new methodology to simplify the conversion of available average monthly temperatures to temperature distribution and exceedance curves. It shows that the temperature extremes have the highest probability of appearance because they represent seasonal changes in contrast to the annual average temperature which only represents a transitional period. The results of this methodology produce much sharper cumulative temperature distribution curves and therefore a smaller temperature distribution for the same probability of exceedance. Validation of this theory is done using meteorological data from LNG plant sites in each of the main climate regions: tropical, desert and arctic. As expected, for the observed cases, moderation of the temperature extremes is observed.

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