Sweet spot prediction in tight sandstone reservoir based on well-bore rock physical simulation
Sweet spot prediction in tight sandstone reservoir based on well-bore rock physical simulation
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基于井筒岩石物理模拟的致密砂岩油藏甜点预测
DOI：
10.1007/s12182-019-00393-1
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发表时间：
2019-10
影响因子：
5.6
通讯作者：
Gong Wei
中科院分区：
文献类型：
--
作者：
Zhou Hai-ting;Li De-yong;Liu Xian-tai;Du Yu-shan;Gong Wei
为了建立储层特征与岩石物理参数之间的关系，首先考虑矿物成分、页岩含量、孔隙度、流体类型和饱和度等影响因素，构建井筒岩石物理模型。然后通过分析弹性参数随上述影响因素的变化规律以及弹性参数间的交会图，确定致密砂岩储层敏感弹性参数，构建甜点岩石物理模板指导叠前地震反演。研究结果表明，速度比和泊松阻抗是表征致密砂岩储层甜点岩性和含气性最敏感的弹性参数。高质量的最佳击球点的特点是较低的速度比和泊松阻抗。最后，选取实际地震资料对致密砂岩气藏甜点进行预测，验证岩石物理模拟结果的有效性。不同井相对测井曲线与反演结果的显着一致性表明，利用井筒岩石物理模拟可以指导致密砂岩气藏甜点预测。
To establish the relationship among reservoir characteristics and rock physical parameters, we construct the well-bore rock physical models firstly, considering the influence factors, such as mineral composition, shale content, porosity, fluid type and saturation. Then with analyzing the change rules of elastic parameters along with the above influence factors and the cross-plots among elastic parameters, the sensitive elastic parameters of tight sandstone reservoir are determined, and the rock physics template of sweet spot is constructed to guide pre-stack seismic inversion. The results show that velocity ratio and Poisson impedance are the most sensitive elastic parameters to indicate the lithologic and gas-bearing properties of sweet spot in tight sandstone reservoir. The high-quality sweet spot is characterized by the lower velocity ratio and Poisson impedance. Finally, the actual seismic data are selected to predict the sweet spots in tight sandstone gas reservoirs, so as to verify the validity of the rock physical simulation results. The significant consistency between the relative logging curves and inversion results in different wells implies that the utilization of well-bore rock physical simulation can guide the prediction of sweet spot in tight sandstone gas reservoirs.
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叠前地震相控储层弹性和岩石物理参数联合反演用于甜点预测
影响因子：
2.7
作者：
Zhang Sheng;Huang H;ong;Li Huijie;Wang Gaofei;Dong Yinping;Luo Yaneng
通讯作者：
Luo Yaneng
DOI：
--
发表时间：
2018
期刊：
--
影响因子：
--
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W. Qian;Tai-ju Yin;Guowei Hou
通讯作者：
W. Qian;Tai-ju Yin;Guowei Hou
影响因子：
3.3
作者：
R. Shuey
通讯作者：
R. Shuey
影响因子：
3.5
作者：
B. Hart
通讯作者：
B. Hart
影响因子：
4.2
作者：
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通讯作者：
J. Dai;Y. Ni;D. Gong;Ziqi Feng;Dan Liu;W. Peng;Wenxue Han