中国石化中原油田物探研究院,河南,郑州,450046
[ "晋达 (1986 —),女,硕士,工程师,碳酸盐岩储层预测。通讯地址:河南省郑州市郑东新区祥盛街绿地原盛国际2号3单元,中国石化中原油田物探研究院,邮政编码:450046。E-mail: 591467689@qq.com" ]
纸质出版:2019
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晋达. 普光地区上三叠统小塘子组泥岩分布地震预测[J]. 油气藏评价与开发, 2019,(4):6-11.
JIN Da. Prediction of mudstone distribution on top of middle Triassic Xiaotangzi formation in Puguang area[J]. Petroleum Reservoir Evaluation and Development, 2019, (4): 6-11.
晋达. 普光地区上三叠统小塘子组泥岩分布地震预测[J]. 油气藏评价与开发, 2019,(4):6-11. DOI: 10.13809/j.cnki.cn32-1825/te.2019.04.002.
JIN Da. Prediction of mudstone distribution on top of middle Triassic Xiaotangzi formation in Puguang area[J]. Petroleum Reservoir Evaluation and Development, 2019, (4): 6-11. DOI: 10.13809/j.cnki.cn32-1825/te.2019.04.002.
普光地区多井在雷口坡顶部气测显示较好
化验分析表明其上覆地层小塘子组发育优质烃源岩
因此
小塘子组作为重要的烃源层和盖层
其泥岩分布预测对普光地区雷口坡组顶部风化壳储层具有重要的意义。在明确小塘子组泥岩的岩石物理特征及测井响应特征的基础上
首先利用已钻井及三维地震资料
对泥岩进行精细井震标定、地质建模与正演模拟
明确小塘子组泥岩的地震反射特征;最终结合古地貌分析、属性分析等手段
确定泥岩发育的有利相带
并以此为基础
应用稀疏脉冲反演对泥岩厚度进行了定量预测
建立了一套适应于普光地区小塘子组泥岩的地震预测方法
预测了普光地区上三叠统小塘子组泥岩的分布
通过与已完钻井泥岩厚度的对比
证实了预测结果的可靠性。
Gas logging of multiple wells at the top of Leikoupo formation in Puguang area is better. The laboratory analysis shows that high quality source rocks are developed in Xiaotangzi formation of the overlying strata. Therefore
as an important hydrocarbon source layer and caprock
the mudstone distribution prediction of Xiaotangzi formation is of great significance to the top weathered crust reservoir of Leikoupo formation in Puguang area. On the basis of defining the petrophysical characteristics and logging response characteristics of mudstone in Xiaotangzi formation
the fine well-seismic calibration
geological modeling and forward modeling of mudstone were carried out by using the drilling and 3D seismic data
and the seismic reflection characteristics of mudstone in Xiaotangzi formation were clarified. Finally
combined with paleogeomorphology analysis
attribute analysis and other means
the favorable facies belt of mudstone development was determined. On this basis
the thickness of mudstone was quantitatively predicted by sparse pulse inversion
a set of seismic prediction method suitable for mudstone of Xiaotangzi formation in Puguang area was established
and the distribution of Upper Triassic was predicted. Then the comparison of mudstone thickness with that of completed drilling confirmed the reliability of the prediction results.
Morteza Raeesi,Ali Moradzadeh,Faramarz Doulati Ardejani,Mashallah Rahimi.Classification and identification of hydrocarbon reservoir lithofacies and their heterogeneity using seismic attributes, logs data and artificial neural networks[J].Journal of Petroleum Science and Engineering,2012.
刘国萍,游瑜春,冯琼,王丹.元坝长兴组生物礁储层精细雕刻技术[J].石油地球物理勘探,2017(03).
徐宝亮,臧殿光,李明杰,纪学武,王志勇,司国帅.岩溶储层综合预测技术在四川盆地Y地区的应用[J].石油地球物理勘探,2016(S1).
甯濛,刘殊,龚文平.川西坳陷三叠系雷口坡组顶部白云岩储层分布预测[J].中国石油勘探,2015(03).
杨光,石学文,黄东,汪华,丁伟.四川盆地龙岗气田雷四~3亚段风化壳气藏特征及其主控因素[J].天然气工业,2014(09).
缪志伟,别静,季春辉.川东北元坝地区飞仙关组二段鲕滩储层预测[J].石油地球物理勘探,2014(02).
许国明,宋晓波,冯霞,隆轲,王琼仙,石国山,朱兰.川西地区中三叠统雷口坡组天然气勘探潜力[J].天然气工业,2013(08).
宋晓波,王琼仙,隆轲,许国明,石国山,冯霞,邓强,蔡左花.川西地区中三叠统雷口坡组古岩溶储层特征及发育主控因素[J].海相油气地质,2013(02).
施振生,赵正望,金惠,宋海敬.四川盆地上三叠统小塘子组沉积特征及地质意义[J].古地理学报,2012(04).
钟怡江,陈洪德,林良彪,侯明才,李秀华,徐胜林,王峻.川东北地区中三叠统雷口坡组四段古岩溶作用与储层分布[J].岩石学报,2011(08).
陈学海,卢双舫,薛海涛,胡慧婷,陈学洋,韩雷.地震属性技术在北乌斯丘尔特盆地侏罗系泥岩预测中的应用[J].中国石油勘探,2011(02).
刘国萍,游瑜春,冯琼,王丹.元坝长兴组生物礁储层精细雕刻技术[J].石油地球物理勘探,2017(03).
徐宝亮,臧殿光,李明杰,纪学武,王志勇,司国帅.岩溶储层综合预测技术在四川盆地Y地区的应用[J].石油地球物理勘探,2016(S1).
甯濛,刘殊,龚文平.川西坳陷三叠系雷口坡组顶部白云岩储层分布预测[J].中国石油勘探,2015(03).
杨光,石学文,黄东,汪华,丁伟.四川盆地龙岗气田雷四~3亚段风化壳气藏特征及其主控因素[J].天然气工业,2014(09).
缪志伟,别静,季春辉.川东北元坝地区飞仙关组二段鲕滩储层预测[J].石油地球物理勘探,2014(02).
许国明,宋晓波,冯霞,隆轲,王琼仙,石国山,朱兰.川西地区中三叠统雷口坡组天然气勘探潜力[J].天然气工业,2013(08).
宋晓波,王琼仙,隆轲,许国明,石国山,冯霞,邓强,蔡左花.川西地区中三叠统雷口坡组古岩溶储层特征及发育主控因素[J].海相油气地质,2013(02).
施振生,赵正望,金惠,宋海敬.四川盆地上三叠统小塘子组沉积特征及地质意义[J].古地理学报,2012(04).
钟怡江,陈洪德,林良彪,侯明才,李秀华,徐胜林,王峻.川东北地区中三叠统雷口坡组四段古岩溶作用与储层分布[J].岩石学报,2011(08).
陈学海,卢双舫,薛海涛,胡慧婷,陈学洋,韩雷.地震属性技术在北乌斯丘尔特盆地侏罗系泥岩预测中的应用[J].中国石油勘探,2011(02).
Morteza Raeesi,Ali Moradzadeh,Faramarz Doulati Ardejani,Mashallah Rahimi.Classification and identification of hydrocarbon reservoir lithofacies and their heterogeneity using seismic attributes, logs data and artificial neural networks[J].Journal of Petroleum Science and Engineering,2012.
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