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地震属性油气储层预测技术及其应用

Seismic attribute oil-gas reservoir prediction technology and its application

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【作者】 郝骞张晶晶李鑫毛婉慧张宇航

【Author】 HAO Qian1,ZHANG Jingjing2,LI Xin1,MAO Wanhui1,ZHANG Yuhang1(1.School of Earth Resources,China University of Geosciences,Wuhan 430074,China;2.School of Mechanical Engineering,Xi’an University of Science and Technology,Xi’an 710054,China)

【机构】 中国地质大学资源学院西安科技大学机械工程学院

【摘要】 按沿层方式对苏北盆地溱潼凹陷泰州组砂岩储层提取了20余种属性,经过优化并在最佳时窗段内通过井-震精细标定后可识别出三角洲前缘亚相沉积,指示出三角洲朵叶向凹陷深湖区的进积分布状况.对松辽盆地长岭断陷内营城组火山岩储层,按层间平均等分顶底时窗厚度作为约束界面的方式提取了30余种属性,从波阻抗及地震相的识别入手仔细区分火山岩储层地震属性平面展布特征,在已获工业油流的钻井指示下确定地震属性异常变化区域,从而有针对性圈定火山岩体储层的平面分布范围.

【Abstract】 Reservoir prediction and description is one of the complicate key technologies of oil-gas accumulation petroleum exploration and development in the modern times.In recent several years seismic attribute analysis has become a reservoir prediction technique which can prompt horizontal resolution accuracy and it has made great long-term development,and now it has been used in all steps of petroleum exploration and development.Twenty kinds of seismic attributes were extracted from Taizhou Formation sandstone reservoir of Qintong sag in Northern Jiangsu Basin,along the layer extraction method.After optimized,front delta subfacies sedimentary could be recognized by well–seismic fine calibration during window time,indicating the delta progradation distribution to deep lake.Over thirty kinds of seismic attributes were extracted from Yingcheng Formation volcanic rock reservoir of Changling fault depression in Songliao Basin,through the average attainment between the top and bottom layer time thickness as a constraint interface,identification of the impedance and seismic faces,we carefully distinguished characteristics of the planar distribution of seismic attributes of volcanic reservoir,delineated anomaly area of seismic attribute under the direction of the commercial oil flow drilling,and then delineated horizontal distribution of volcanic rock reservoir.

【基金】 国家自然科学基金(40972104)资助
  • 【文献出处】 湖北大学学报(自然科学版) ,Journal of Hubei University(Natural Science) , 编辑部邮箱 ,2010年03期
  • 【分类号】P618.13
  • 【被引频次】23
  • 【下载频次】430
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