Abstract
Traditional methods for productivity surveillance of oil wells mainly are consisted of using test-separator units with expensive devices, protections, inspections, operations, facilities, infrastructures and repairing services. The objective of this work is to utilize a novel approach to predict the accurate productivity of oil wells using a single sample point at the line of blend oil. The present method is based upon performing multivariate regression of infrared spectra, which taken from the real samples of Iranian offshore oil wells. The experimental results revealed that the present approach is appropriate for precocious, quick and reliable surveillance of individual oil wells located in an oil field. The model has predicted the accurate productivity of real oil wells with respect to the current expensive techniques since 2010.
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