基于模糊聚类分析方法的层系优化研究
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摘要
针对H油藏开发现状的不足和剩余油分布规律,应用模糊聚类分析方法和数值模拟技术进行层系优化,对储层的多个影响因素进行评价,最终得到一个综合评价指标,并据此优化层系,以达到减少层间矛盾,提高水驱动用程度的目的。首先,利用灰色关联分析法确定出油藏小层的采出程度、水驱动用程度、含水率、剩余油储量丰度、孔隙度、渗透率变异系数、储层深度、含油面积和渗透率9个特征参数为评价指标,基于模糊聚类分析方法将小层进行重组分类,得到层系优化后的三套方案,每套方案分为两套层系。再利用数值模拟方法预测10年后3套方案的年产油量、采出程度、含水率对比情况,得出最佳方案。实例结果证明了模糊聚类分析方法在层系优化中的实际应用可行性。
According to the deficiency of the development status and the distribution law of the remaining oil in the reservoir-H, we used the fuzzy clustering analysis and numerical simulation technique to optimize the layers, evaluated the factors influencing the reservoir, and ultimately, got the comprehensive evaluation index, by which we could optimize the layers to reduce the contradiction between the layers and increase the water drive degree. Firstly, we determined 9 feature parameters as the evaluation indexes by the gray correlation analysis, that is, the water extraction degree, water flooding degree, abundance of remaining oil storage, porosity, variable coefficient of permeability, reservoir depth, oil content, and permeability. Based on the fuzzy clustering analysis, we classified the small layers into three groups. Each set of schemes was divided into two sets of layers. Then, we used the numerical simulation to predict and contrast the annual oil production, recovery, and moisture content of three schemes in 10 years later to get the preferred plan. The experimental results confirmed the feasiblility of the fuzzy clustering method in the optimization of the layer system.
According to the deficiency of the development status and the distribution law of the remaining oil in the reservoir-H, we used the fuzzy clustering analysis and numerical simulation technique to optimize the layers, evaluated the factors influencing the reservoir, and ultimately, got the comprehensive evaluation index, by which we could optimize the layers to reduce the contradiction between the layers and increase the water drive degree. Firstly, we determined 9 feature parameters as the evaluation indexes by the gray correlation analysis, that is, the water extraction degree, water flooding degree, abundance of remaining oil storage, porosity, variable coefficient of permeability, reservoir depth, oil content, and permeability. Based on the fuzzy clustering analysis, we classified the small layers into three groups. Each set of schemes was divided into two sets of layers. Then, we used the numerical simulation to predict and contrast the annual oil production, recovery, and moisture content of three schemes in 10 years later to get the preferred plan. The experimental results confirmed the feasiblility of the fuzzy clustering method in the optimization of the layer system.
引文
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[2]陈培元,谭秀成,杨辉廷,等.礁滩型储层层间非均质性定量表征[J].岩性油气藏,2013,25(4):27-32.
[3]李波,罗宪波,刘英,等.判断层间非均质性的新方法[J].中国海上油气,2007,19(2):93-95.
[4]吴胜和,熊琦华.油气储层地质学[M].北京:石油工业出版社,1998:113-128.
[5]于志钧,赵旭东.石油数学地质[M].北京:石油工业出版社,1986:50-60.
[6]肖冬荣,曹征军,康凯.模糊聚类分析方法在稠油开采中的应用[J].微计算机信息,2010,26(1):201-202.
[7]刘育骥,耿新宇,肖辞源.石油工程模糊数学[M].成都:成都科技大学出版社,1994.
[8]冯国庆,张烈辉,沈勇伟,等.应用模糊聚类分析方法评价油藏质量[J].西南石油大学学报(自然科学版),2004,26(3):33-36.
[9]Liu G F,Hou R,Li S S,et a1.Production Characteristics Study of Tight Gas Reservoir with Network Fracturing Using Numerical Simulation[J].Applied Mechanics and Materials,2014,3547(675-677):1556-1560.
[10]汪培庄.模糊集合论及其应用[M].上海:上海科技出版社,1983.
[11]于萍,李克.使用Microsoft Excel进行数据的灰关联分析[J].微型电脑应用,2011,27(3):29-30.
[12]Zhang Z X,Kang X F,Zhang F F.Application of grey theory for oil and gas reservoir evaluation program optimization[J].Advanced Materials Research,2013,2117(616-618):1008-1012.
[13]郑俊峰,金丽琼,靳晓军,等.宝浪油田宝北区块低渗透油藏层系优化研究[J].河南石油,2003,17(1):38-41.
[14]张立秋.南二区东部二类油层上返层系组合优化[J].岩性油气藏,2007,19(4):116-120.
[15]杨二龙,王景翠,高玉鑫.杏南开发区含钙特低渗透储层井网层系优化数值模拟研究[J].中外能源,2012,17(8):54-57.
[16]徐文斌.数值试井技术在孔隙型碳酸岩油藏初期开发中的应用[J].油气藏评价与开发,2014,4(6):21-24.
[17]万小迅,赵春明,陆正元.低渗透砂岩油藏高含水开发期加密调整研究[J].油气田地面工程,2010,29(3):20-21.
[18]覃建华,周锡生,唐春荣,等.克拉玛依砾岩油藏高含水区块井网加密潜力[J].新疆石油地质,2010,31(3):269-272.
[19]王峰.低渗透油藏井网加密试验研究[J].特种油气藏,2006,13(3):60-62.
[20]殷代印,季菊香,王国锋.新站油田井网加密调整方案的数值模拟[J].石油地质与工程,2008,22(2):57-59.