摘要
叙述了深层特殊岩性致密高阻薄层油气层的岩石学特征和储集类型,并指出深层高温高压环境下成岩中后期的脱碳酸盐化作用是该类储层次生孔隙发育的有利条件。分析了该类油气层的测井响应及成因机制,同时提出该类储层有效孔隙度的计算和流体性质的评价方法。利用神经网络技术,计算了储层的渗透率和束缚水饱和度,并从相对性原理出发,编制了该类储层测井资料数字处理软件。
Describes the petrophysical property of deep thin tight reservoir with special lithology and high resistivity and points out that epigenetic decarbonation promotes the development of deep formation secondary porosity in the environment of high temperature and high pressure. Also analyses its log response, reservoir type and its genetic mechanism; and provides the calculation method of effective porosity and the evaluation method of fluid property. At the same time, calculates reservoir permeability and irreducible water saturation using neural network technique and develops data processing software for this kind of reservoir based on relative theorem. Evaluation method mentioned above is applied to the deep reservoir in Dagang Oilfield and the result is quite good.
出处
《测井技术》
CAS
CSCD
北大核心
1999年第5期350-354,共5页
Well Logging Technology
关键词
测井解释
深层
神经网络
储量
油气层
探井
岩性
log interpretation deep reservoir thin bed neural network reserve evaluation tight formation