Abstract
The aim of this work was to develop a generic methodology for evaluating andselecting, at the conceptual design phase of a project, the best process technology for Natural Gas conditioning.
A generic approach would be simple and require less time and would give a better understanding of why one process is to be preferred over another. This will lead to a better understanding of the problem. Such a methodology would be useful in evaluating existing, novel and hybrid technologies. However, to date no information is available in the published literature on such a generic approach to gas processing.
It is believed that the generic methodology presented here is the first available for choosing the best or cheapest method of separation for natural gas dew-point control.
Process cost data are derived from evaluations carried out by the vendors. These evaluations are then modelled using a steady-state simulation package. From the results of the modelling the cost data received are correlated and defined with respect to the design or sizing parameters. This allows comparisons between different process systems to be made in terms of the overall process.
The generic methodology is based on the concept of a Comparative Separation Cost. This takes into account the efficiency of each process, the value of its products, and the associated costs. To illustrate the general applicability of the methodology, three different cases suggested by BP Exploration are evaluated.
This work has shown that it is possible to identify the most competitive process operations at the conceptual design phase and illustrate why one process has an advantage over another. Furthermore, the same methodology has been used to identify and evaluate hybrid processes. It has been determined here that in some cases they offer substantial advantages over the separate process techniques.
Date of Award | May 1997 |
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Original language | English |
Keywords
- generic selection methodology
- simulation
- natural gas separation processes
- hydrocarbon dew-pointing
- hybrid processes