Username   Password       Forgot your password?  Forgot your username? 


On-line Detector and Inversion Algorithm of Suspended Particles

Volume 14, Number 6, June 2018, pp. 1213-1223
DOI: 10.23940/ijpe.18.06.p12.12131223

Deli Jiaa, Tong Guoa, Zhenkun Zhub, Quanbin Wanga, Yan Wanga, and Yanping Wangc

aPetroChina Research Institute of Petroleum Exploration & Development, PetroChina Company Limited, Beijing, 100000, China
bDaqing Research Institute of Oil Production Engineering, Daqing Oil & Gas Company Limited, Daqing, 163000, China
cXinli Oil Production Plant of Jilin Oilfield, Daqing Oil & Gas Company Limited, Songyuan,138000, China

(Submitted on March 5, 2018; Revised on April 16, 2018; Accepted on May 21, 2018)


Stratified waterflooding is the main technology for oilfield development. Continuously improving waterflooding control and utilization through fine waterflooding is a never-ending pursuit. Reinjecting the produced liquid into the formation after electrical dehydration is the main technical means for the waterflooding development of oilfields. Whether the suspended particle in the reinjection water meets the standards will directly affect the waterflooding development effect. This paper proposes and develops an on-line suspended particle detector and its inversion algorithm. In order to meet the downhole detection requirements of subsurface suspended particles in reinjection water, a laser on-line detector for suspended particle was developed based on the light scattering method, and an array structured light-induced ring detector was designed to realize the identification of scattered light. In order to meet the engineering requirements of on-line inspection, the genetic algorithm and least-squares algorithm are used to optimize the granularity inversion calculation. The detection error and response time of these algorithms are compared and analyzed. With an error below the allowed value of 4% and a response time of 0.22s, the least square algorithm has more engineering application value. In order to prevent the occurrence of negative numbers after iteration of the least squares algorithm, a non-negative least square granularity inversion algorithm was designed in the practical engineering application. Based on the actual engineering data and the simulation structure, it can be concluded that the simulation values are highly consistent with the theoretical values, which proves that the laser suspended particle on-line detector and its inversion algorithm are applicable to the on-line detection system of suspended particles in the reinjection water of oilfields.


References: 7

        1. Gao Jianchong, Li Haitao, Qiao Wenbo, Shan Jincheng, Zhang Ling, “The Compatibility between Suspended Solids Partice Size and Pore Throat during Water-Flooding in Qikuo 17-2 Oilfield”, Journal of Petrochemical Universities, vol.27, pp. 56-59, 89, 2014.
        2. Hu Zeng, Chen Jian, Zhou Danong, Sun Jiyong, “Development of a Liquid Particle Counter based on Light Scattering Structuce”, Analutical Instrumentation, No.5, pp.11-14, 2017.
        3. Huang Qiyu, Bi Quan, “Application of New Technology for Wastewater Trertment in Low Permeabilitey oilfield”. Journal of Petrochemical Universities, vol.28, pp. 69-73, 2015.
        4. Jia Deli, Pei Xiaohan, “Research on the Flow Control Strategy of Water Distributor in Water Injection Well”, The 33rd Chinese Control Conference, pp. 4993-4996, 2014.
        5. Jiang Wnalu, Lei Yafei, Dai Haodong, Ynag Chao, Zhang Sheng, “Hunidity Modified Light Scattering Method Applied in Field Dust Monitoring”, Chinese Journal of Scientific Instrument, vol.39, pp.200-207, 2018.
        6. Lin Y, Wang C, Ma C, et al: “A new combination method for multisensor conflict information,” Journal of Supercomputing, Vol.72, No.7, pp. 2874-2890 2016.
        7. Lin Y, Zhu X, Zheng Z, et al. “The individual identification method of wireless device based on dimensionality reduction and machine learning”. Journal of Supercomputing, No.5, pp.1-18 2017.
        8. Liu He, “High-efficiency measuring and adjusting technology and management for separated layer water injection”. Beijing: Petroleum Industry Press, 2016.
        9. Liu He, Pei Xiaohan, Jia Deli, Sun Fuchao, Guo Tong, “Connotation, application and prospect of the fourth-generation separated layer water injection technology”, Petroleum Exploration and Development, vol.44, pp. 608-614, 2017.
        10. Liu He, Pei Xiaohan, Luo Kai, Sun Fuchao,Zheng Licheng, Yang Qinghai, “Current status and trend of separated layer water flooding in china”. Petroleum Exploration and Development, vol.40, pp. 733-737, 2013.
        11. Liu He, Pei Xiaohan, Jia Deli, et al, “Real time monitoring technique of injection distribution in layered water injection”. Proceedings of the 14th annual conference of automation of petroleum and chemical industry of China, pp.531-534, 2015.
        12. Ma Jingjing, Jiang Xiaoping, Peng Lingshu, “Application of genetic algorithm in inversing particle size distribution”, Computer Engineering and Design, vol.33, pp.1051-1054, 2011.
        13. Shi C, Dou Z, Lin Y, et al. “Dynamic threshold-setting for RF-powered cognitive radio networks in non-Gaussian noise”. Physical Communication, Vol. 27, No. 4, pp. 99-105, 2018.
        14. Sun Fuchao, Pei Xiaohan, Jia Deli, et al, “Research and application of real time monitoring technology of high efficiency water injection matching”. Proceedings of the 14th annual conference of automation of petroleum and chemical industry of China, pp.523-526, 2015.
        15. Wang Qingquan, Li Xuyu, Zhang Maolin, “Different Turbidity Fast Detection Technology Based on CCD”, Instrument Technique and Sensor, No.1, pp.97-101, January 2013.
        16. Wang Wenjing, Liu Wei, Chen Wengang, John C, Thomas, Wang Yajing, Shen Jin, “The Conversion of Particle Size Distributions Based on Mie Theory”, The Journal of Light Scattering, vol.30, pp. 6-9, 2018.
        17. Wu Qi, “Matching technology for improving the effect of water injection”. Beijing: China Petrochemical Press, 2010.
        18. Wu Q, Li Y, Lin Y: “The application of nonlocal total variation in image denoising for mobile transmission,” Multimedia Tools & Applications, Vol.76, No.16, pp. 1-13 2016.
        19. Xie Fengqiang, “Expermental Evaluation of Formation Damage Caused by Particles in the Injected Water”. Journal of Petrochemical Universities, vol.29, pp. 43-46, 2016.
        20. Xu Yishu, Liu Xiaowei, Cui Jiang, Chen Dong, Han Jinke, Xu Minghou, “Mass Concentration Measurements of the Coal-derived Fiy Ash Particles Via Lsght Extinction Method”, Journal of Engineering Thermophysics, vol.38, pp.1496-1502, 2017.
        21. Xue Xiaokang, Li Xiaoyu, Ding Mao, “Spectrum Interpretation and Processing of Laser Raman Spectroscopy”, Chinese Journal of Inorganic Analytical Chemistry, vol.8, pp.66-70, April 2018.
        22. Yan Weipeng, Yang Tao, Li Xin, Huang Fuxi, Wu Xiaozhi, Tang Hui, “Geological Characteristics and Hydrocarbon Exploration Potential of Lacustrine Carbonate Rock in China”. China Petroleum Eeploration, vol.19,.pp. 11-17, 2014.
        23. Yin Yonghui, Yan Xinping, Xiao Hanliang, Wang Chengtao, “On Optic-scattering Measurement of Particle Size”, Journal of Wuhan University of Technology (Transportation Science & Engineering ), vol.27, pp.643-645, 2003.
        24. Zou Ruijie, Chen Yubang, Fang Yanjun, Zhao Youquan, “Research on online detection technology of mineral oil in water based on Mie scattering theory”, Chinese Journal of Scientific Instrument, vol.33, pp.655-660, 2018.
        25. Yun Lin, Chao Wang, Jiaxing Wang, Zheng Dou. “A Novel Dynamic Spectrum Access Framework Based on Reinforcement Learning for Cognitive Radio Sensor Networks”. Sensors, Vol.16, No.10, pp. 1-22, 2016.


        Please note : You will need Adobe Acrobat viewer to view the full articles.Get Free Adobe Reader

        This site uses encryption for transmitting your passwords.