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作 者:隋明阳 SUI Mingyang(Geophysical Research Institute of Sinopec Shengli Oilfield Branch,Dongying,Shandong 257099,China)
机构地区:[1]中国石油化工股份有限公司胜利油田分公司物探研究院,山东省东营市257099
出 处:《录井工程》2022年第1期116-122,共7页Mud Logging Engineering
基 金:中石化股份公司科研攻关项目“多资料联合解释及油藏建模一体化技术研究”(编号:P21038-4)。
摘 要:深薄致密砂岩储层具有埋藏深度大、单层厚度薄、储量丰度低的地质特点,储层定量描述是该类储层有效动用的关键制约因素。以渤南油田Y 184井区为例,通过开发相控去压实高分辨率反演技术,将中浅层的砂泥波阻抗差异引入到深层段,实现砂泥岩波阻抗的有效区分,准确落实储层发育范围,创建基于深度学习的多地震属性融合技术,充分挖掘地震属性与储层参数之间的非线性关系,融合形成储层敏感的新属性,实现储层物性的精细描述,明确有利储层展布范围。该套技术系列在渤南油田Y 184井区未动用储量区应用,精细刻画Y 184井区扇三角洲发育边界,定量描述储层厚度及物性,解决了长期困扰该区扇三角洲与滩坝砂岩发育边界认识不清的问题,为区块效益建产提供技术支撑。With the geological characteristics of large burial depth,thin single-layer and low reserves abundance,the quantitative description of reservoirs is a key constraint to the effective production of deep and thin tight sandstone reservoirs.Taking the Y 184 wellblock of Bonan Oilfield as an example,by developing high-resolution inversion technology of facies-controlled decompaction,the difference of sand and mud wave impedance in the middle and shallow layers is introduced into the deep layer to realize the effective distinction of sand and mudstone wave impedance and determine the development range of reservoirs.Fine description of reservoir physical properties is realized and favorable reservoir distribution range is clarified through a multi-seismic attribute fusion technology based on deep learning,fully exploitation of the nonlinear relationship between seismic attributes and reservoir parameters and new reservoir-sensitive attributes through fusion.Applied in the unproduced reserves of Y 184 wellblock of Bonan Oilfield,this set of technical sequences finely depicts the development boundary of Y 184 well block fan delta and quantitatively describes the thickness and physical properties of reservoirs,solving the unclear understanding of the development boundary between fan delta and beach-bar sandstone in this block for a long time,and providing technical support for the block benefit construction and production.
关 键 词:深薄致密砂岩 储层预测 波阻抗反演 地震属性 深度学习 渤南油田
分 类 号:TE132.1[石油与天然气工程—油气勘探]
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