利用吸水剖面测试资料优化分层注水措施  

Optimizing Separated Layer Water-Flooding by Utilizing Injection Profile Test Data

作　　者：周琦[1] 姜汉桥[1] 李志刚[2] 吕凤滨[3] 

机构地区：[1]中国石油大学石油工程教育部重点实验室,北京102249 [2]华北油田采油四厂,河北廊坊065000 [3]天津石油职业技术学院,天津301607

出　　处：《油气井测试》2009年第3期11-14,共4页Well Testing

基　　金：中国石油天然气集团公司石油科技中青年创新基金(高含水期油藏大孔道动态变化机理与识别模型04E7029)资助

摘　　要：非均质油藏随注水开发时间的延长,层间干扰越来越严重,注水井吸水状况逐渐变差。分层注水是改善吸水剖面、提高油藏水驱动用程度的重要措施,需要采取科学合理的理论和方法来优化分层注水措施。利用层次分析方法计算不同地质开发因素对注水井吸水剖面变化的影响权重,量化不同因素的影响程度。在此基础上选择重点影响因素作为出入样本参数,以注水井小层相对吸水量作为输出样本,采用模糊神经网络方法,建立吸水剖面预测模型。根据预测模型预测不同分层条件下注水井吸水剖面变化,优化分层注水措施。In heterogeneous reservoirs,along with water-flooding,the interference between layers becomes more and more serious and so water-intaking efficiency of injection wells becomes worse and worse.Separated layer water-flooding is an important measure to improve injection profile and water drive efficiency,and needs to be optimized by scientific and reasonable theories and methods.The method is as follows:alculate the influence weights of various geological and development factors to injection profile variation of injection well and quantify the influence degree of various factors by hierarchical analysis method,and then on this basis select key influence factors to be input-output sample parameters,take relative water-intake rate of every layer as output sample,establish prediction model of injection profile by fuzzy neural network method,and finally optimize by analyzing prediction results of different variation of injection profile of injection wells under different separated layer water-floodings.

关 键 词：吸水剖面 分层注水 层次分析 自适应模糊神经网络 优化 

分 类 号：TE357.6[石油与天然气工程—油气田开发工程] TE353