10 فروردین 1403
شهريار عصفوري

شهریار عصفوری

مرتبه علمی: استاد
نشانی: دانشکده مهندسی نفت، گاز و پتروشیمی - گروه مهندسی شیمی
تحصیلات: دکترای تخصصی / مهندسی شیمی
تلفن: 88019360
دانشکده: دانشکده مهندسی نفت، گاز و پتروشیمی

مشخصات پژوهش

عنوان
ارائه راهبرد بهینه برای کنترل کیفیت داده های PVT، مشخصه سازی سیال و تنظیم معادلات حالت برای سیالات گاز میعانی
نوع پژوهش پارسا
کلیدواژه‌ها
gas condensate, statistical hypothesis test, plus fraction, regression, EOS tuning
پژوهشگران سیده فاطمه موسوی (دانشجو) ، شهریار عصفوری (استاد راهنما) ، رضا آذین (استاد راهنما) ، مسعود مفرحی (استاد مشاور)

چکیده

The proper reservoir management requires accurate knowledge about reservoir characterization. It is possible by having valid samples from reservoir fluid. Therefore it is necessary that be sure to quality of prepared samples. In this thesis, different steps of quality control of gas condensate fluid sampling are checked and these steps are developed. First step in quality control of samples is assurance of well conditioning before sampling. Here by use of statistical hypothesis test, confidental ranges are determined for variation of effective parameters on stability of wells. After this step, standing plot is used for specification of gas and liquid samples equilibrium. Considerable differences exist between calculated results and measurement values especially for plus fraction. So by data of several gas condensate wells, this plot is optimized and calculation errors are reduced. After passing of samples from these two steps and assurance about their quality, reservoir fluid is prepared by recombination. Then PVT experiments are implemented on it. CVD test is one of an important PVT experiments that be done on gas condensate fluids. Existence of error in this test is determined by material balance calculation and getting to condensate by negative composition. For correction of this test, two methods are applied. One of these methods is correction of exhausted gas composition by use of correction factors and other method is implementation of regression on samples in different senarios. Results of two methods are elimination or reduction of negative liquid composition. Finally EOS tuning by use of regression on plus fraction moleculare weight improve estimation of surface parameters.