تعیین نقطه کارکرد چاههای نفتی با استفاده از مدل سازی حرکت سیال در مخزن و چاه

چکیده

پیشگویی رابطه بین دبی جریان چاه و افت فشار مخزن برای بهینه سازی تولید پیوسته از مخزن، بسیار حائز اهمیت است. مدل عملکرد جریان ورودی یا (IPR) برای این منظور به کار گرفته   می شود. این مدل بررسی شرایط مختلف عملیاتی مانند تعیین روند تولید بهینه، طراحی تجهیزات تولید و سیستم های بالا آورنده مصنوعی و ... را امکان پذیر می سازد. چنانچه مدل IPR با به کارگیری روش "آنالیز گره"، با مدل چاه یا مدل عملکرد جریان خروجی ترکیب شود، شرایط تجزیه و تحلیل دبی تولیدی چاه را برای دست یابی به عملکرد بهینه فراهم خواهد کرد. در این کار مدل IPR ارائه شده توسط Vogel برای پیشگویی عملکرد جریان ورودی و مدل جریان دو فازی   Aziz-Govier-Fogarasi، برای پیشگویی عملکرد جریان خروجی به کار می روند. ترکیب این دو منحنی، دبی تولیدی یا نقطه کارکرد چاه را مشخص می کند. مقایسه نتایج پیشگویی شده با نتایج به دست آمده از نرم افزار ECLLIPSE-VFPi نشان می دهد که مدل ارائه شده از دقت بسیار خوبی برخوردار است

عنوان مقاله [English]

Determination of Operating Point of Oil Wells by Fluid Flow Modeling Through Reservoir and Well

چکیده [English]

Predicting the relationship between the flow rate and the pressure drop performance in the reservoir is very important for continuous production optimization in the field. An inflow performance relationship (IPR) model is typically used for this task. IPR models allow us to consider various operating conditions; determine the optimum production scheme, and design production equipment and artificial lift systems. IPR modeling (inflow) can be combined with tubing analysis (outflow) using "nodal analysis"   techniques   which  allow us   to monitor   well  flow   rate  and  to  choose  the proper remedial treatment options to restore optimum well performance. In this work we use Vogel-type correlation for predicting Inflow Performance and Aziz-Govier-Fogarasi two phase flow relationship to predict Outflow Performance. Combination of an Inflow and Outflow (a curve reflecting the tubing performance) curves identifies an operating point of wells. Comparison of predicting results and results obtained from ECLLIPSE-VFPi software indicates a good ability of proposed model.

 
                      

 

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