Application of Simulated Annealing Technique to Non-Linear Optimization of PC-SAFT for Petroleum Reservoir Fluids
Publish place: 14th International Oil, Gas and Petrochemical Congress
Publish Year: 1389
نوع سند: مقاله کنفرانسی
زبان: English
View: 1,973
This Paper With 20 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
IOGPC17_012
تاریخ نمایه سازی: 3 آبان 1389
Abstract:
Equations of state should be tuned to reservoir conditions by PVT tests for phase behavior modeling. This tuning is achievable via an optimization method. In this work simulated annealing algorithm is applied as a global optimization method to parameters optimization for PC-SAFT from the statistical associating fluid theory incorporating hard chain as reference fluid . the optimization parameters are determined by minimizing the calculated phase behavior of a synthetic petroleum mixture and real petroleum fluids from iranian oil and gas reservoir, based on their PVT-tests.we examined several tests assumed to be representative of reservoir processes, such as differential liberation and constant composition expansion for oil samples and constant volume depletion for gas condensate sample. in petroleum systems new petroleum fraction characterizing correlations developed and validated according to PVT data and other equations of state. the results showed a high degree of accuracy for these newly developed correlations. it is observed that for the synthetic mixture and real reservoir fluids considering the parameters obtained using the annealing technique the solutions are theoretically justifiable for real samples of petroleum fluid the results are acceptable; such results provide a measure of confidence that the annealing method does convergeto the global minimum in the majority of the studied systems.
Keywords:
petroleum fluids , EOS tuning , PVT-test , non-linear parameter optimization simulated annealing , PC-SAFT
Authors
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :