New Inflow Performance Relationship for Iranian Reservoir

This research focuses on creating and testing a new equation that helps us understand how oil wells performunder different pressure conditions. While there are several existing models out there (developed byresearchers like Vogel, Wiggins, and others), each has its own shortcomings when applied to real-worldsituations. This study developed new equation using actual field data from oil wells in southwestern Iran. Tohelp us find the best mathematical relationship, we used Table Curve software, which allowed us to fine-tuneour equation to match the specific characteristics of these oil fields. This approach helped us better account forhow oil flows through the reservoir at different pressures. To make sure our new equation was reliable, we usedmachine learning - specifically linear regression - to see how it stacked up against traditional models. Wecompared the predictions from our equation with those from established methods, which helped us measure itsaccuracy. The results were encouraging, showing that our equation could predict well behavior more accuratelythan existing models, making it a useful tool for optimizing oil production.

کلیدواژه ها:

Inflow Performance Relationship (IPR) ، Vogel Equation ، Fetkovich Equation ، Wiggins Equation ، LinearRegression