【摘要】 致密碎屑岩储层与围岩地震波阻抗差异微弱,应用常规储层地震反演方法的有效性较差,精度较低。针对致密碎屑岩储层的地质、地球物理特点,本文提出了将神经网络和地质统计学结合起来的致密碎屑岩储层地震反演技术方案。在此方案中,通过神经网络地震反演获得地质涵义较为明确的但垂向精度较低的反演结果,以此结果为约束,以测井数据作为条件数据(硬数据)进行储层参数地质统计学随机反演/模拟,进而得到较为精细的、同时横向分布较为符合地质规律的储层参数反演成果。通过在D气田致密碎屑岩储层地震反演中的应用,提高了储层预测精度,达到了良好的应用效果。更多还原

【Abstract】 The feeble difference in acoustic impedance between reservoir and its adjacent rocks is unfavorable to use seismic inversion to characterize reservoirs,and the corresponding results are always invalid and coarse.Based on the knowledge of the geology and geophysics of tight clastic reservoir,this paper outlines a new program used for seismic inversion in tight clastic reservoir characterization.Firstly a coarse inversion result in accordance with geological pattern is obtained through artificial neural network.Then geo-statistics inversion is applied to integrate well data and the inversion data mentioned above,and to get the high-resolution inversion data honored with lateral geological pattern.This seismic inversion program is employed in D gas field,in which tight gas reservoir is the main type,and the high-resolution results are obtained which can be used for reservoir characterization.更多还原