油气藏评价与开发
油氣藏評價與開髮
유기장평개여개발
Reservoir Evaluation and Development
2015年
5期
11-16
,共6页
火山岩%FMI%岩性识别%测井参数%交会图
火山巖%FMI%巖性識彆%測井參數%交會圖
화산암%FMI%암성식별%측정삼수%교회도
volcanic rock%full bore microscan imager(FMI)%lithology identification%log parameter%cross plot
中拐地区火山岩岩性复杂多样、纵横向变化快，火山岩与火山碎屑岩互层，且发生蚀变，测井响应特征与正常火山岩差别较大，与火山岩碎屑岩特征相似，岩性识别极其困难，需要针对共性及个性特征研究相应的火山岩测井识别方法。首先利用微电阻率扫描成像测井（FMI）上不同的图像纹理类型能较好反映岩石结构、构造特点，将FMI与岩心资料相结合，分析总结不同火山岩FMI图像模式，识别出岩石类型有火山角砾岩、英安岩、凝灰岩、玄武安山岩及花岗岩等，以火山角砾岩、玄武安山岩为主。然后分析出常规测井对FMI标定的岩性响应敏感的测井参数，并建立交会图岩性识别法，最后将识别结果与薄片资料对比，符合率高达88%，提高测井岩性解释精度。
中枴地區火山巖巖性複雜多樣、縱橫嚮變化快，火山巖與火山碎屑巖互層，且髮生蝕變，測井響應特徵與正常火山巖差彆較大，與火山巖碎屑巖特徵相似，巖性識彆極其睏難，需要針對共性及箇性特徵研究相應的火山巖測井識彆方法。首先利用微電阻率掃描成像測井（FMI）上不同的圖像紋理類型能較好反映巖石結構、構造特點，將FMI與巖心資料相結閤，分析總結不同火山巖FMI圖像模式，識彆齣巖石類型有火山角礫巖、英安巖、凝灰巖、玄武安山巖及花崗巖等，以火山角礫巖、玄武安山巖為主。然後分析齣常規測井對FMI標定的巖性響應敏感的測井參數，併建立交會圖巖性識彆法，最後將識彆結果與薄片資料對比，符閤率高達88%，提高測井巖性解釋精度。
중괴지구화산암암성복잡다양、종횡향변화쾌，화산암여화산쇄설암호층，차발생식변，측정향응특정여정상화산암차별교대，여화산암쇄설암특정상사，암성식별겁기곤난，수요침대공성급개성특정연구상응적화산암측정식별방법。수선이용미전조솔소묘성상측정（FMI）상불동적도상문리류형능교호반영암석결구、구조특점，장FMI여암심자료상결합，분석총결불동화산암FMI도상모식，식별출암석류형유화산각력암、영안암、응회암、현무안산암급화강암등，이화산각력암、현무안산암위주。연후분석출상규측정대FMI표정적암성향응민감적측정삼수，병건입교회도암성식별법，최후장식별결과여박편자료대비，부합솔고체88%，제고측정암성해석정도。
In Zhongguai area, lithology of volcanic rocks is complex and changes rapidly in vertical horizontal direction. Volcanic rocks interbed with pyroclastic rocks and form alteration. Log response characteristic has a great difference from normal volcanic rocks; however it is similar to pyroclastic rocks. Due to the extremely difficult lithology identification, aiming at common and per?sonality features, it needs to research corresponding volcanic rock logging recognition method. Firstly, micro resistivity was used to scan different image texture types of full bore microscan imager(FMI), which could preferably reflect rock texture and structure. Combined with FMI and core data, different FMI image patterns of volcanic rock were summarized, and rock types were identified. The rock types are volcanic breccia, dacite, tuff, andesibasalt and ganite, among them, volcanic breccia and andesibasalt are the main types. Secondly, logging parameters of conventional logging to lithological response sensitive marked by FMI were analyzed, and cross plot lithology identification method were established. Finally, compared with recognition results and thin slices, the coin?cidence rate reached 88 %, thereby, the interpretation accuracy of logging lithology was greatly improved.
