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安岳地区须二段水平井段随钻录井储层及流体判别方法

MUD LOGGING WHILE DRILLING TO IDENTIFY RESERVOIR AND RESERVOIR FLUID IN HORIZONTAL INTERVAL OF XUJIAHE 2 MEMBER, ANYUE AREA
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摘要 安岳气田须二段气藏多采用水平井进行开发,对须二段水平井段进行随钻录井储层解释及流体判别以提高录井解释符合率至关重要。利用钻井过程中的录井资料,采用BP神经网络的方法,建立录井孔隙度模型,计算随钻过程中储层孔隙度值,进而识别有效储层;通过气藏特征与钻井的气测及试油成果,建立适用于研究区的气测解释图版和判别分析图版;利用烃比值曲线判别法,对储层是否含油进行判别。综合上述方法,可实现随钻有效储层解释及流体性质判别,进一步提高水平井的录井解释符合率,指导井眼轨迹在有利储层中钻进。针对安岳地区须二段水平井段的随钻储层及流体判别方法,对其它气藏水平井随钻储层及流体识别的研究具有参考意义。 Horizontal-well drilling is often used to most Xujiahe 2 gas reservoirs, Anyue area. It is very critical to adopt mud logging while drilling to carry out reservoir interpretation and reservoir-fluid identification for horizontal intervals of Xujiahe 2 Member in order to increase a coincidence rate of mud-logging interpretation. In this study, a mud-logging porosity model was established by means of mud-logging data and BP neural network. And then, the reservoir porosity during drilling was calculated in order to further identify an effective reservoir. Thirdly, two charts of both gas-testing interpretation and identification analysis, which are suitable to the study area,were also developed according to reservoir property and some gas-testing and oil-testing data. Finally, whether reservoir is an oil-bearing one or might not be determined through an identification method of hydrocarbon ratio curve. After using these above-mentioned methods, both effective-reservoir interpretation while drilling and reservoir-fluid property identification may be realized in order to not only increase the coincidence rate of mud-logging interpretation for horizontal wells but also guide wellbore trajectory in a favorable reservoir. The methods, which have been used for the horizontal intervals of Xujiahe 2 Member, are also useful reference for identifying reservoir and reservoir fluid while drilling at the horizontal intervals of other reservoirs.
出处 《天然气勘探与开发》 2015年第3期22-26,7-8,共5页 Natural Gas Exploration and Development
关键词 四川盆地 安岳地区 水平井 神经网络 录井孔隙度 解释图版 储层解释 流体判别 Sichuan Basin,Anyue area,horizontal well,neural network,porosity from mud logging,interpretation chart,reservoir interpretation,
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