地质统计学反演方法在杭锦旗区块煤系地层储层预测中的应用

杭锦旗区块J井区储层薄且具有岩性致密、非均质性强的特点,地震资料分辨率较低,砂岩顶底界面难以分开,同时受煤层强反射的影响,加上砂、泥岩波阻抗差异较小,造成砂体的地震响应特征不明显,储层预测难度极大。为此,提出了一套针对该区煤系地层薄砂岩的储层预测流程。首先,通过钻井、测井和地震资料的综合分析,确定岩性解释的敏感参数,建立岩性解释模板;其次,基于马尔科夫链-蒙特卡洛算法的地质统计学反演方法从地震强反射中定位煤层的厚度及空间展布,再通过云变换中子属性协模拟得到岩性数据体;最后,结合岩性解释模板,实现对煤系地层薄储层的有效预测。

Application of geostatistical inversion method in reservoir prediction of coal measure strata in Hangjinqi area

The reservoir in well J of Hangjinqi block is thin and characterized by dense lithology and strong heterogeneity. The resolution of seismic data is low and it is difficult to separate the top and bottom interfaces of sandstone. Meanwhile, due to the strong reflection of coal measure strata and the small difference of wave impedance between sand and mudstone, the seismic response characteristics of sand body are not obvious and the reservoir prediction is extremely difficult. Therefore, a set of reservoir prediction process for coal measure strata in thin sandstone of this area is proposed. Firstly, through the comprehensive analysis of drilling, logging and seismic data, the sensitive parameters of interpretation lithology were determined and the lithology interpretation template was established. Secondly, the geostatistical inversion method based on Markov chainMonte Carlo algorithm was used to locate the thickness and spatial distribution of coal seam from strong reflection, and then the lithology data body was obtained through the neutron attribute co-simulation of cloud transformation. Finally, combined with the lithology interpretation template, the effective prediction of thin reservoirs in coal measures was realized.