
doi: 10.2523/21066-ms , 10.2118/21066-ms
ABSTRACT A major problem for the producers on a gas production site is encountered when a unit does not perform at its designed operating conditions. A consequence of this problem is, for example, a sales gas refused as not meeting specifications. This paper illustrates that it is possible to solve this problem, i.e. to identify the faulty equipment, and to optimize the gas treatment process. This was realized for some gas fields, with the help of a small appraisal on the site completed by fluids samplings and numerical simulations of the process (Peng Robinson equation of state). In one case, the sales gas was refused as not meeting specifications. An appraisal performed on the site by a small team showed that it was indeed the case and identified the faulty equipment. In an other case, a quality control of operating conditions was performed on the main separators of a production unit, comparing for each separator its operating efficiency to the designed one. In both cases, the experimental measurements justified fluid samplings on the site. Detailed analyses on the treated gas were then carried out in the laboratory, up to C18+ fraction, which permitted a quite successfull simulation of the process, especially at low liquids carry over. The results of this study is that optimization of the process has been obtained with the establishment of operating tables. Such a table gives to the operator, for a given separator and a given value of its efficiency, the operating pressure and temperature to be run in order to give to the treated gas its commercial specification.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
