Performance analysis of an in-line optical fiber analysis system for well crude oil

Dehuan Meng; Haifeng Xuan; Min Zhang; Shurong Lai; Yanbiao Liao

doi:10.1117/12.726604

5 March 2007 Performance analysis of an in-line optical fiber analysis system for well crude oil

Dehuan Meng, Haifeng Xuan, Min Zhang, Shurong Lai, Yanbiao Liao

Proceedings Volume 6595, Fundamental Problems of Optoelectronics and Microelectronics III; 65953S (2007) https://doi.org/10.1117/12.726604
Event: Fundamental Problems of Optoelectronics and Microelectronics III, 2006, Harbin, China

Abstract

In this paper, an in-line optical fiber spectral analysis system is presented and analyzed, which will be used in the field for measuring the mount of components of oil, water and gas in down-well. Instead of full spectrum analysis of crude oil with a spectroscopy on the ground, this system uses a disperse-spectrum-selecting algorithm, which makes the system in small and compact size and easy to use in down-well. The correlation of the model of disperse wavelengths is equivalent to the model of full range wavelengths and the system measurement accuracy reaches 2 percent by experiments. In addition, the math's model of the system is established, and several regression methods such as Multivariate linear regression (MLR) and Principle components regression (PCR) are discussed and compared in detail. The performance of the system is analyzed with the math's model also. The result indicates that the PCR has a higher accuracy then MLR and 6 channels are enough for practical system used in the field. Besides, an accuracy of less than 1 percent may be got by the results of performance analysis.

Citation Download Citation

Dehuan Meng, Haifeng Xuan, Min Zhang, Shurong Lai, and Yanbiao Liao "Performance analysis of an in-line optical fiber analysis system for well crude oil", Proc. SPIE 6595, Fundamental Problems of Optoelectronics and Microelectronics III, 65953S (5 March 2007); https://doi.org/10.1117/12.726604

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available