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三角洲外前缘薄砂体地震综合预测方法
肖佃师1,2,卢双舫1,王海生3,陆正元2,郭思祺1,张鲁川1
(1.中国石油大学非常规油气与新能源研究院,山东青岛 266580;2.成都理工大学油气藏地质与开发工程国家重点实验室,四川成都 610059;3.中国石油辽河油田公司,辽宁盘锦 124010)
摘要:
针对三角洲外前缘储层单砂体薄、砂泥岩波阻抗值差异小的特点,结合曲线重构、地震正演等技术,分别对适用于薄储层的地震反演及属性分析方法进行研究。结果表明:声波与自然伽马曲线重构、稀疏脉冲波阻抗与地质统计学反演的联合是实现薄储层精细预测的有效手段,前者提高了波阻抗反演的岩性分辨能力,后者降低了储层预测的不确定性;三角洲外前缘薄砂体的厚度与地震属性间关系较分散,依据地震属性对不同规模砂体的分辨能力指导属性优选及阈值选取,可以定性刻画砂层组内薄砂体的空间展布;将地震反演及属性分析的成果进行交互验证,指导油田井位部署方案的调整,区块内钻探成功率由65%提高至82%。
关键词:  曲线重构  地质统计学反演  属性分析  薄砂体  三角洲外前缘
DOI:10.3969/j.issn.1673-5005.2015.04.008
分类号::TE 122.2
基金项目:山东省优秀中青年科学家科研奖励基金(2014BSE28018);黑龙江省教育厅科学技术研究项目(ky120102)
Comprehensive prediction method of seismic to thin sandstone reservoir in delta-frontal
XIAO Dianshi1,2, LU Shuangfang1, WANG Haisheng3, LU Zhengyuan2, GUO Siqi1, ZHANG Luchuan1
(1.Institute of Unconventional Oil & Gas and New Energy in China University of Petroleum,Qingdao 266580,China;2.State Key Laboratory of Oil & Gas Reservoir Geology and Exploitation in Chengdu University of Technology, Chengdu 610059, China;3.Liaohe Oilfield Company, PetroChina, Panjin 124010,China)
Abstract:
The reservoirs of delta-frontal subfacies are characterized by single thin sandstone and there are no obvious impendence difference between sandstone and shale. Based on curve reconstruction and seismic forward modeling, the seismic inversion and attribute analysis technology suitable to such thin reservoirs were studied respectively. The results indicate that fine prediction of thin reservoirs can be accomplished by two effective methods:pseudo-sonic curve reconstruction with origin sonic and gamma ray curve which can improve the reservoir identification ability of impedance inversion; and the combination of sparse spike impedance and geostatistics stochastic inversion which contributes to decrease uncertainty in reservoir prediction. Due to the scattered relationship between thickness of thin reservoirs and seismic attributes in the delta-frontal subfacies, the spatial distribution of thin sand bodies in sand groups can be qualitatively characterized by optimizing attributes and selecting threshold based on the identification ability of seismic attributes in different scale of sand bodies. Results obtained by the proposed seismic inversion and attributes analysis are cross-validated, and are applied to guide adjustment of well deployment scheme in oilfield, resulting in a significant improvement of drilling success rate from 65% to 82%.
Key words:  curve reconstruction  geostatistics inversion  attributes analysis  thin reservoir  delta-frontal subfacies
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