相似油田定量筛选的方法及应用

doi:10.13809/j.cnki.cn32-1825/te.2021.05.015

Abstract

Abstract:

During the development of oil and gas field, the analogy method is often used to study the development technology policy and predict the development index for the undeveloped or early stage reservoir. The selection of analogy samples, i.e. similar oil and gas fields, determines the reliability of analogy results. Therefore, gray correlation and geological factor analysis are used to determine the analogy parameters and weights quantitatively on the basis of the essential correlation between analogy parameters and analogy objectives. According to the reservoir type of the studied object, the parameter thresholds are introduced to calculate the similarity of the samples, and the oilfields with high similarity are selected as the reference samples for the technical policy research and index prediction, so as to make the basic conditions of the objective basis of analogy analysis are more reasonable, and further improve the efficiency of screening and the reliability of analogy results.

Key words: grey relation, basic parameters, threshold, similarity, quantitative analogy

CLC Number:

TE32

FAN Yumei,ZHAO Qingfei,ZHANG Yingli. Quantitative screening methods of similar oil fields and their application[J].Petroleum Reservoir Evaluation and Development, 2021, 11(5): 766-771.

Figures/Tables 8

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Table 1

References 20

[1]	李忠春, 杨兆平, 王天奇, 等. 美国SEC新准则下油气藏类比方法研究[J]. 特种油气藏, 2014, 21(4):113-115.
	LI Zhongchun, YANG Zhaoping, WANG Tianqi, et al. Research on analogous methods under new American SEC rules[J]. Special Oil & Gas Reservoirs, 2014, 21(4):113-115.
[2]	丁祖鹏, 田冀, 张晓量. 稠油油藏类比方法研究[J]. 特种油气藏, 2013, 20(4):102-105.
	DING Zupeng, TIAN Ji, ZHANG Xiaoliang. Analogy method for heavy oil reservoirs[J]. Special Oil & Gas Reservoirs, 2013, 20(4):102-105.
[3]	李斌, 张欣赏, 刘丹江. 类比法定量模型及在油田开发中的应用[J]. 承德石油高等专科学校学报, 2006, 8(3):24-27.
	LI bin, ZHANG Xinshang, LIU Danjiang. Application of analogy fix quantity model in exploration and exploitation in oilfields[J]. Journal of Chengde Petroleum College, 2006, 8(3):24-27.
[4]	游秀玲, 张玲, 罗云秀. 原油采收率影响因素探讨及油藏综合分类[J]. 石油与天然气地质, 2004, 25(3):314-318.
	YOU Xiuling, ZHANG Ling, LUO Yunxiu. Factors influencing oil recovery efficiency and comprehensive classification of oil reservoirs[J]. Oil & Gas Geology, 2004, 25(3):314-318.
[5]	袁自学, 王靖云, 李淑珣, 等. 特低渗透注水砂岩油藏采收率确定方法[J]. 石油勘探与开发, 2014, 41(3):341-348.
	YUAN Zixue, WANG Jingyun, LI Shuxun, et al. A new approach to estimating recovery factor for extra-low permeability water-flooding sandstone reservoir[J]. Petroleum Exploration and Development, 2014, 41(3):341-348.
[6]	袁希娟, 龚耘. 浅谈类比法[J]. 河北理工学院学报:社会科学版, 2003, 3(1):84-88.
	YUAN Xijuan, GONG Yun. A brief study on the method of analogy[J]. Journal of Hebei Institute of Technology(Social Science Edition), 2003, 3(1):84-88.
[7]	计秉玉, 王友启, 张莉. 基于地质储量结构变化的采收率演变趋势[J]. 石油与天然气地质, 2020, 41(6):1257-1262.
	JI Bingyu, WANG Youqi, ZHANG Li. Research on overall recovery rate variations of dynamically changing OOIP[J]. Oil & Gas Geology, 2020, 41(6):1257-1262.
[8]	周林碧, 秦冰, 李伟, 等. 国内外稠油降黏开采技术发展与应用[J]. 油田化学, 2020, 37(3):557-563.
	ZHOU Linbi, QIN Bing, LI Wei, et al. Development and application of heavy oil viscosity reduction technology at home and abroad[J]. Oilfield Chemistry, 2020, 37(3):557-563.
[9]	曹明霞. 灰色关联分析模型及其应用的研究[D]. 南京:南京航空航天大学, 2007.
	CAO Mingxia. Research on grey incidence analysis model and its application[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2007.
[10]	苏志欣. 加权灰色关联理想解法在多属性决策中的应用研究——以洛带JP气藏增压开采方案技术经济评价为例[D]. 成都: 成都理工大学, 2007.
	SU Zhixin. Research on the application of WGC-TOPSIS in multiple attribute decision-making: Taking Comprehensive evaluation on technology and economy of the JP Gas Pool’s turbo-charged schemes in Luodai Natural Gas Field as a case[D]. Chengdu: Chengdu University of Technology, 2007.
[11]	宁宝权, 陕振沛. 基于改进熵和灰关联分析的模糊物元分析模型及应用[J]. 数学的实践与认识, 2016, 46(20):280-284.
	NING Baoquan, SHAN Zhenpei. Fuzzy matter-element analysis model based on improved entropy and grey relational analysis and its application[J]. Mathematics in Practice and Theory, 2016, 46(20):280-284.
[12]	邬光辉, 吉云刚, 赵仁德, 等. 一种油气资源量计算新方法及其应用[J]. 天然气地球科学, 2007, 18(1):41-44.
	WU Guanghui, JI Yungang, ZHAO Rende, et al. A new method of oil and gas resource evaluation and its application in Tarim Basin[J]. Natural Gas Geoscience, 2007, 18(1):41-44.
[13]	王大星, 翟明清. 数据处理和建模方法在数学建模教学中的应用[J]. 北京教育学院学报:自然科学版, 2014, 9(1):5-10.
	WANG Daxing, ZHAI Mingqing. Application of data processing and modeling method in mathematical modeling teaching[J]. Journal of Beijing Institute of Education(Natural Science Edition), 2014, 9(1):5-10.
[14]	刘舒野. 模糊聚类分析方法在油藏分类中的应用研究[D]. 长春:东北师范大学, 2007.
	LIU Shuye. The application research of fuzzy cluster analysis method in reservoir classification[D]. Changchun: Northeast Normal University, 2007.
[15]	吕远. 水驱油藏单井控制可采储量影响因素定量研究[D]. 青岛:中国石油大学(华东),2010.
	LYU Yuan. Quantitative study of water drive recovery single well controlled recoverable reserve[D]. Qingdao: China University of Petroleum(East China), 2010.
[16]	柳广弟, 喻顺, 孙明亮. 海相碳酸盐岩层系油气资源类比评价方法与参数体系——以塔里木盆地奥陶系为例[J]. 石油学报, 2012, 22(S2):125-134.
	LIU Guangdi, YU Shun, SUN Mingliang. Methods and parameter systems for analog assessment of petroleum resources in marine carbonate strata: A case study of the Ordovician in Tarim Basin, China[J]. Acta Petrolei Sinica, 2012, 22(S2):125-134.
[17]	罗义科, 张俊廷, 张彩旗, 等. 渤海稠油注水开发油田提高采收率技术研究[J]. 长江大学学报:自然科学版, 2016, 13(29):59-63.
	LUO Yike, ZHANG Junting, ZHANG Caiqi, et al. Technology of enhance oil recovery in heavy oil reservoir of water flooding development in Bohai Area[J]. Journal of Yangtze University(Natural Science Edition), 2016, 13(29):59-63.
[18]	孙焕泉, 王海涛, 吴光焕, 等. 稠油油藏注CO₂提高采收率影响因素研究[J]. 石油实验地质, 2020, 42(6):1009-1023.
	SUN Huanquan, WANG Haitao, WU Guanghuan, et al. CO₂ EOR factors in heavy oil reservoirs[J]. Petroleum Geology & Experiment, 2020, 42(6):1009-1023.
[19]	申乃敏, 张连锋, 张小静, 等. 普通稠油油藏聚合物驱技术应用——以古城油田泌125区块为例[J]. 石油地质与工程, 2020, 34(4):60-63.
	SHEN Naimin, ZHANG Lianfeng, ZHANG Xiaojing, et al. Application of polymer flooding technology in conventional heavy oil reservoir: By taking Bi125 block of Gucheng oilfield as an example[J]. Petroleum Geology and Engineering, 2020, 34(4):60-63.
[20]	杜渊, 秦懿. 实验标准偏差和算数平均值实验票标准偏差的差别辨析和应用分析[J]. 计量与测试技术, 2014, 41(11):8-9.
	DU Yuan, QIN Yi. The diference di scrimination and application analysis of experimental standard deviation of the average value of the experimental standard deviation and count[J]. Metrology and Measurement Technique, 2014, 41(11):8-9.

检验方式	筛选方式	油藏埋深（m）	孔隙度（%）	渗透率（10^-3μm²）	重度（API^o）	气油比（m³/t）
标准偏差	1	749.5	3.9	1 818	3.4	33.3
标准偏差	2	1 300.2	7.0	2 179	6.0	112.2

Quantitative screening methods of similar oil fields and their application

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 8

References 20

Related Articles 4

Metrics

Comments

Recommended 10

[1]	ZHAO Jun,ZHANG Tao,HE Shenglin,ZHANG Huanrong,HAN Dong,TANG Di. Prediction of reservoir permeability by deep belief network based on optimized parameters [J]. Petroleum Reservoir Evaluation and Development, 2021, 11(4): 577-585.
[2]	Li Yongming,Zhou Wenwu,Zhao Jinzhou,Zhang Lingling. Semi-analytical productivity calculation and sensitive factors for the multi-stage fractured horizontal well in low permeability reservoirs [J]. Reservoir Evaluation and Development, 2018, 8(2): 52-57.
[3]	Yin Peng,Wei Jun,Zhang Zhijun,Wu Dongming,Wu Shenqu,Xu Hao,Xu Liang,Hua Keliang. Analysis of low permeability gas reservoir fracturing well productivity equation considering multi-factors [J]. Reservoir Evaluation and Development, 2018, 8(1): 34-37.
[4]	Wang Sihang,Tian Xiaolin,Wang Chuke,Feng Yongguang,Wu Deqiang,Bai Jiaquan,Li Hui,Kong Decai. Application of fuzzy similarity methods for evaluating the district of shale gas: A case of marine shale gas in Sichuan Basin [J]. Reservoir Evaluation and Development, 2018, 8(1): 71-75.