基于SOM的无井约束剩余油分布预测
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摘要
提出了基于SOM(自组织神经网络)的无井约束剩余油分布预测方法:利用RBF神经网络预测时移前的原始含油饱和度;利用SOM对含油饱和度敏感的多属性差异进行聚类;利用动态资料和岩石物理测试数据圈定各种变化区域,建立各个区域含油饱和度变化与多属性差异之间的关系,依据所建立的关系获得储层含油饱和度的变化;将时移前的原始含油饱和度与含油饱和度变化相减得到储层的剩余油分布。该方法在渤海S油田取得了比较好的应用效果。
A method to predict remaining oil distribution without drilled-well constraints has been developped on a basis of SOM(self-organization neural network).In this prediction,the original oil saturation before the time lapse is first predicted by using RBF neural networks,and then a cluster analysis is conducted for the multi-attribute differences sensitive to oil saturation by SOM.Thirdly,a relationship between oil saturation and multi-attribute difference can be established for various areas delineated by reservoir performance data and petrophysical data,and according to this relationship,the oil saturation change in reservoirs can be determined.Finally,the original oil saturation before the time lapse minus the oil saturation change would result in the remaining oil distribution in reservoirs.This method has led to better application results in Bohai S oilfield.
A method to predict remaining oil distribution without drilled-well constraints has been developped on a basis of SOM(self-organization neural network).In this prediction,the original oil saturation before the time lapse is first predicted by using RBF neural networks,and then a cluster analysis is conducted for the multi-attribute differences sensitive to oil saturation by SOM.Thirdly,a relationship between oil saturation and multi-attribute difference can be established for various areas delineated by reservoir performance data and petrophysical data,and according to this relationship,the oil saturation change in reservoirs can be determined.Finally,the original oil saturation before the time lapse minus the oil saturation change would result in the remaining oil distribution in reservoirs.This method has led to better application results in Bohai S oilfield.
引文
[1]张哲,刘锦霞,黎文超.应用吸水剖面进行油藏纵向剩余油分布定量研究[J].中国海上油气(地质),2001,15(5):345-350.
[2]戴长林.利用中子寿命测井进行剩余油饱和度评价[J].江汉石油职工大学学报,2005,18(2):22-24.
[3]徐加军,曹国峰,庞瑞,等.油藏数值模拟技术在剩余油分布中的研究与应用[J].中国青年科技(理论版),2007,(07):107-109.
[4]林博,戴俊生,冀国盛,等.河流相建筑结构随机建模与剩余油分布研究[J].石油学报,2007,28(4):81-85.
[5]王涛溪,左朝辉,宋福刚.利用地质方法研究小断块油藏剩余油分布[J],2005,27(4):673-674.
[6]刘建民,李阳,毕研鹏,等.应用驱油微观模拟实验技术研究储层剩余油微观分布特征[J].中国海上油气(地质),2000,14(1):51-54.
[7]SIGIT R,等.利用地震监测识别死油区[J].马连山,王丽君,译.石油物探译丛,2001,(2):86-89.
[8]易启维,李清仁,张国才,等.大庆TN油田时移地震研究与剩余油分布规律预测[J].勘探地球物理进展,2003,26(1):61-65.
[9]高兴军,于兴河,李胜利,等.利用神经网络技术预测剩余油分布[J].石油学报,2005,26(3):60-63.
[10]江文荣,张科.径向基函数神经网络在孔隙度预测中的应用[J].中国海上油气,2008,20(5):305-307.
[2]戴长林.利用中子寿命测井进行剩余油饱和度评价[J].江汉石油职工大学学报,2005,18(2):22-24.
[3]徐加军,曹国峰,庞瑞,等.油藏数值模拟技术在剩余油分布中的研究与应用[J].中国青年科技(理论版),2007,(07):107-109.
[4]林博,戴俊生,冀国盛,等.河流相建筑结构随机建模与剩余油分布研究[J].石油学报,2007,28(4):81-85.
[5]王涛溪,左朝辉,宋福刚.利用地质方法研究小断块油藏剩余油分布[J],2005,27(4):673-674.
[6]刘建民,李阳,毕研鹏,等.应用驱油微观模拟实验技术研究储层剩余油微观分布特征[J].中国海上油气(地质),2000,14(1):51-54.
[7]SIGIT R,等.利用地震监测识别死油区[J].马连山,王丽君,译.石油物探译丛,2001,(2):86-89.
[8]易启维,李清仁,张国才,等.大庆TN油田时移地震研究与剩余油分布规律预测[J].勘探地球物理进展,2003,26(1):61-65.
[9]高兴军,于兴河,李胜利,等.利用神经网络技术预测剩余油分布[J].石油学报,2005,26(3):60-63.
[10]江文荣,张科.径向基函数神经网络在孔隙度预测中的应用[J].中国海上油气,2008,20(5):305-307.
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