为了提高含泥质碳酸盐岩储层反演的精度,提出以波阻抗数据体作为背景约束进行基质孔隙度随机反演处理的方法.该方法首先统计分析大量测井资料,获得波阻抗和基质孔隙度的关系;然后以波阻抗反演数据体作为背景约束,对基质孔隙度进行随机反演处理;最后根据基质孔隙度与波阻抗数据交会设定门槛值来划分储层与非储层.研究结果表明,储层和非储层对应的基质孔隙度数值存在明显界限,最终反演的基质孔隙度数据体清晰显示了储层和非储层的分布情况.与储层的实际厚度相比,利用该方法反演的储层厚度误差在10%以下.
In order to increase inversion accuracy of clay-bearing carbonate reservoir,in this paper,we propose the matrix porosity random inversion processing method in which matrix porosity is constrained by wave impedance inversion database.Firstly,the relationship between wave impedance and matrix porosity was acquired based on a lot of statistical analysis of well-log data.Secondly,matrix porosity random inversion processing was finished by using wave impedance inversion database as constrained background.Finally,reservoir and non-reservoir were divided by setting threshold according to crosses between matrix porosity and wave impedance data.The results show that there is a clear boundary for the matrix porosity value between reservoir and non-reservoir.The reservoir and non-reservoir can be identified clearly from the final matrix porosity inversion profile.The results also show that the error is less than 10% contrasting inversion reservoir thickness by this inverse method with drilling thickness.