摘要
随着四川盆地龙岗、普光等大型礁滩型气藏的发现,礁滩型气藏的勘探受到越来越多的重视。但随着勘探的深入,发现该类气藏储层受沉积相、成岩作用等因素的影响存在储层非均质性强、孔隙结构复杂等特点,不同沉积相带储层品质差异较大,储层有效性评价存在困难,从而导致探井测井解释符合率偏低。为此,开展了针对龙岗地区礁滩型储层的测井评价技术攻关,从有利储层的主控因素入手,分析研究不同沉积相、不同岩性、不同孔隙结构储层的有效性,将常规测井与成像测井相结合,利用自然伽马、地层倾角、成像测井等方法识别沉积相,ECS元素俘获测井识别岩性,常规测井结合MDT流度、斯通利波流体移动指数等测井新技术评价储层有效性。该方法较之以往更注重沉积相的识别及储层渗透性评价,经勘探、开发实践验证,具有较好的应用效果,使该区测井储层解释符合率超过90%。
Along with the discovery of large reef/bank-type gas reservoirs such as Longgang and Puguang in the Sichuan Basin,more and more attention is paid to the exploration of such reservoirs.However,they are featured by strong heterogeneity and complex pore structures due to the influences of various factors including sedimentary facies and diagenesis.Reservoir quality varies greatly in different facies belts,which becomes a great challenge for the evaluation of reservoir effectiveness and logging interpretation of exploratory wells.In order to solve these problems,we performed a study on logging evaluation of reef/bank reservoirs in the Longgang area.Starting from the recognition of major controlling factors on favorable reservoirs,we analyzed the effectiveness of various sedimentary facies,lighologies and pore structures.Conventional logging and image logging data were integrated to identify sedimentary facies,ECS element capture logging data were used to identify lithologies,and new logging techniques such as MDT fluidity and the fluid mobility index of Stoneley wave were combined with conventional logging for the evaluation of reservoir effectiveness.Compared with the previous methods,these methods focus on the recognition of sedimentary facies and the evaluation of reservoir permeability.Practical application shows that the coincidence rate of logging interpretation is over 90%.
出处
《天然气工业》
EI
CAS
CSCD
北大核心
2011年第7期28-31,104,共4页
Natural Gas Industry
基金
国家科技重大专项"四川龙岗地区大型碳酸盐岩气田勘探开发示范工程"(编号:2008ZX05047)
中国石油测井工程技术攻关项目"四川盆地龙岗
磨溪地区礁滩储层测井评价攻关研究"的部分成果
关键词
四川盆地
龙岗地区
早三叠世
晚二叠世
生物礁
鲕滩
测井
符合率
Sichuan Basin,Longgang area,Early Triassic,Late Permian,bioherm,oolitic beach,logging,image logging evaluation