光谱学与光谱分析 |
|
|
|
|
|
Prediction of the Side-Cut Product Yield of Atmospheric/Vacuum Distillation Unit by NIR Crude Oil Rapid Assay |
WANG Yan-bin1, HU Yu-zhong2, LI Wen-le1, ZHANG Wei-song2, ZHOU Feng1, LUO Zhi3 |
1. Petrochemical Research Institute, Beijing 100175, China2. PetroChina Guangxi Petrochemical Company, Qinzhou 535008, China3. Nanjing Richisland Information Technology Co., Ltd., Nanjing 210061, China |
|
|
Abstract In the present paper, based on the fast evaluation technique of near infrared, a method to predict the yield of atmospheric and vacuum line was developed, combined with H/CAMS software. Firstly, the near-infrared(NIR) spectroscopy method for rapidly determining the true boiling point of crude oil was developed. With commercially available crude oil spectroscopy database and experiments test from Guangxi Petrochemical Company, calibration model was established and a topological method was used as the calibration. The model can be employed to predict the true boiling point of crude oil. Secondly, the true boiling point based on NIR rapid assay was converted to the side-cut product yield of atmospheric/vacuum distillation unit by H/CAMS software. The predicted yield and the actual yield of distillation product for naphtha, diesel, wax and residual oil were compared in a 7-month period. The result showed that the NIR rapid crude assay can predict the side-cut product yield accurately. The near infrared analytic method for predicting yield has the advantages of fast analysis, reliable results, and being easy to online operate, and it can provide elementary data for refinery planning optimization and crude oil blending.
|
Received: 2014-05-08
Accepted: 2014-07-21
|
|
Corresponding Authors:
WANG Yan-bin
E-mail: wangyanbin1@petrochina.com.cn
|
|
[1] LU Wan-zhen(陆婉珍). Modern Near Infrared Spectroscopy Analytical Technology(现代近红外光谱分析技术). Beijing: China Petrochemical Press(北京:中国石化出版社),2006. 7, 306. [2] Hoeil Chung. Applied Spectroscopy Reviews, 2007, 42: 251. [3] Chu Xiaoli, Xu Yupeng, Tian Songbai, et al. Chemometrics and Intelligent Laboratory Systems, 2011, 107(1): 44. [4] LI Jian-hua, CUI Hong-wei(李建华,崔鸿伟). Modern Scientific Instruments(现代仪器分析),2011,1:123. [5] WANG Yan-bin, LIU Wei, YUAN Hong-fu, et al(王艳斌,刘 伟,袁洪福,等). Petroleum Processing and Petrocheimcals(石油炼制与化工),2002,33(7):62. [6] Falla F S, Larini C, Le Roux G A C, et al. Journal of Petroleum Science and Engineering, 2006, 51: 127. [7] LU Wan-zhen, CHU Xiao-li(陆婉珍,褚小立). J. of Southwest Petroleum University·Science and Technology Edition(西南石油大学学报·自然科学版),2012,34(1):1. [8] Lambert D, Descales B, Linas J R, et al. Analysis, 1995, 23(4): M9. [9] Pasquini C, Bueno A. Fuel, 2007, 86: 1927. [10] CHU Xiao-li, TIAN Song-bai, XU Yu-peng, et al(褚小立,田松柏,许育鹏,等). Petroleum Processing and Petrochemicals(石油炼制与化工),2012,43(1):72. |
[1] |
WANG Wen-xiu, PENG Yan-kun*, FANG Xiao-qian, BU Xiao-pu. Characteristic Variables Optimization for TVB-N in Pork Based on Two-Dimensional Correlation Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2094-2100. |
[2] |
LE Ba Tuan1, 3, XIAO Dong1*, MAO Ya-chun2, SONG Liang2, HE Da-kuo1, LIU Shan-jun2. Coal Classification Based on Visible, Near-Infrared Spectroscopy and CNN-ELM Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2107-2112. |
[3] |
LIU Jin, LUAN Xiao-li*, LIU Fei. Near Infrared Spectroscopic Modelling of Sodium Content in Oil Sands Based on Lasso Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2274-2278. |
[4] |
YU Hui-ling1, MEN Hong-sheng2, LIANG Hao2, ZHANG Yi-zhuo2*. Near Infrared Spectroscopy Identification Method of Wood Surface Defects Based on SA-PBT-SVM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(06): 1724-1728. |
[5] |
XU Wei-jie1, WU Zhong-chen1, 2*, ZHU Xiang-ping2, ZHANG Jiang1, LING Zong-cheng1, NI Yu-heng1, GUO Kai-chen1. Classification and Discrimination of Martian-Related Minerals Using Spectral Fusion Methods[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(06): 1926-1932. |
[6] |
LI Ying1, LI Yao-xiang1*, LI Wen-bin2, JIANG Li-chun3. Model Optimization of Wood Property and Quality Tracing Based on Wavelet Transform and NIR Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(05): 1384-1392. |
[7] |
DU Jian1, 2, HU Bing-liang1*, LIU Yong-zheng1, WEI Cui-yu1, ZHANG Geng1, TANG Xing-jia1. Study on Quality Identification of Macadamia nut Based on Convolutional Neural Networks and Spectral Features[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(05): 1514-1519. |
[8] |
HAN Guang, LIU Rong*, XU Ke-xin. Extraction of Effective Signal in Non-Invasive Blood Glucose Sensing with Near-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(05): 1599-1604. |
[9] |
WANG Li-shuang, ZHANG Wen-bo*, TONG Li. Studies on Dimensional Stability of Wood under Different Moisture Conditions by Near Infrared Spectroscopy Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(04): 1066-1069. |
[10] |
HUANG Hua1, WU Xi-yu2, ZHU Shi-ping1*. Feature Wavelength Selection and Efficiency Analysis for Paddy Moisture Content Prediction by Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(04): 1070-1075. |
[11] |
LI Hao-guang1,2, YU Yun-hua1,2, PANG Yan1, SHEN Xue-feng1,2. Study of Maize Haploid Identification Based on Oil Content Detection with Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(04): 1089-1094. |
[12] |
PENG Cheng1, FENG Xu-ping2*, HE Yong2, ZHANG Chu2, ZHAO Yi-ying2, XU Jun-feng1. Discrimination of Transgenic Maize Containing the Cry1Ab/Cry2Aj and G10evo Genes Using Near Infrared Spectroscopy (NIR)[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(04): 1095-1100. |
[13] |
XIA Ji-an1, YANG Yu-wang1*, CAO Hong-xin2, HAN Chen1, GE Dao-kuo2, ZHANG Wen-yu2. Classification of Broad Bean Pest of Visible-Near Infrared Spectroscopy Based on Cloud Computing[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(03): 756-760. |
[14] |
MAO Ya-chun, WANG Dong, WANG Yue, LIU Shan-jun*. A FeO/TFe Determination Method of BIF Based on the Visible and Near-Infrared Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(03): 765-770. |
[15] |
LAI Tian-yue1, CAI Feng-huang1*, PENG Xin2*, CHAI Qin-qin1, LI Yu-rong1, 3, WANG Wu1, 3. Identification of Tetrastigma hemsleyanum from Different Places with FT-NIR Combined with Kernel Density Estimation Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(03): 794-799. |
|
|
|
|