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白55块储层预测研究方法及应用效果
引用本文:杨建春,李仁甫,张洪波,周杰.白55块储层预测研究方法及应用效果[J].石油物探,2004,43(6):595-598.
作者姓名:杨建春  李仁甫  张洪波  周杰
作者单位:1. 中国石化中原油田分公司勘探开发科学研究院,河南,濮阳,457001
2. 中国石化中原油田分公司勘探开发科学研究院,河南,濮阳,457001;中国地质大学,北京,100083
摘    要:从白55块砂泥岩薄互层的地层特点出发,研究了该区储层地球物理特征,分析了砂、泥岩的地震属性差异,如速度、波阻抗差异等,确定以砂组为单位进行储层预测。为了减少误差和多解性,对所使用的测井、地震资料进行了预处理。基于地震波阻抗反演理论,提出了相对波阻抗反演思路;采用最小二乘法子波反演GLI技术进行了层位标定;在精细构造解释的基础上,使用分形和波形相似内插方法构建复杂储层的地质模型;采用信息融合技术把地质、测井、地震等信息统一到同一模型中;采用全局寻优的快速反演算法进行了波阻抗反演;然后进行了相对波阻抗反演,并提取了相对波阻抗属性。最后对沙三中2砂组和3砂组储层分布进行了预测,并进行了有利储层检测。储层预测结果较好地反映了储层沉积规律。

关 键 词:波阻抗反演  储层预测  地球物理特征  测井  层位标定  泥岩  地震资料  精细构造  储层分布  地层特点
文章编号:1000-1441(2004)06-0595-04
收稿时间:2003-12-14
修稿时间:2004-2-25

The reservoir prediction method and application in block Bai 55 in Dongpu depression
Yang Jianchun Li Renfu Zhang Hongbo et al.The reservoir prediction method and application in block Bai 55 in Dongpu depression[J].Geophysical Prospecting For Petroleum,2004,43(6):595-598.
Authors:Yang Jianchun Li Renfu Zhang Hongbo
Affiliation:(1.Exploration and development science research institute , ZPEB, SINOPEC, Puyang 457001, China;2.China University of Geosciences, Beijing 100083, China)
Abstract:This paper present reservoir prediction method from stratigraphic characters of thin sand-shale alternating beds in Bai 55 block We researched geophysical character, analyzed sand-shale seismic attribute difference, such as velocity, impedance difference and make through reservoir prediction according to sand group. Log and seismic data was preprocessed for reducing errors and multi-solution. We put forward novel impedance inversion way with seismic impedance inversion theory, finished marking of horizon with wavelet inversion GLI technique of least square method, build the complex reservoir geological model with fractal and waveform similarity interpolation method on basis of fine construction interpretation and unified this model with multivariate geological information of geology, log and seismic by information introjections technique, finished impedance inversion with global optimization rapid inversion arithmetic and relative impedance inversion . Picking up relative impedance attribute, predict reservoir distribution of 2 and 3 sand groups in middle of S3, and then we worked in available reservoir prediction. The conclusion reflect reservoir sediment rule well.
Keywords:ngpu depression  reservoir prediction  impedance  relative impedance
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