碳酸盐岩地层划分及类型识别方法

Automatic segmentation and type identification of carbonate Formation

四川盆地普光地区碳酸盐岩储层具有溶蚀孔洞发育、裂缝较发育和常规测井响应特征不明显等特点,目前,利用常规测井资料进行地层划分及地层类型识别存在困难,并且现有方法仅仅只能确定地层界面,并不能有效识别地层类型。为此,文中提出了基于成像测井资料的地层划分及类型识别方法。成像电阻率数据经过处理生成平均电阻率曲线,并与自然伽马曲线进行融合,生成反映地层信息的融合曲线,进行初始地层划分;从电成像测井图像中提取熵、能量等纹理特征,与图片数据库中的电成像测井图像进行欧式距离匹配,微调初始分层界面,并确定地层类型。实例应用表明,该方法融合多种测井信息划分地层,确定地层类型,效果良好。

Due to the dissolved pores development, evolution of fractures and no obvious response of conventional well logging in Puguang Area, Sichuan Basin, layers can not be effectively segmented using conventional well logging data. Since the conventional methods can only segment layers and can not recognize layer types, so an approach in this paper for automatic segmentation and layer type identification was proposed by imaging logging data. First, resistivity data is processed to generate average resistivity curve, then it is fused with GR curve to generate a fusion curve that can reflect formation information to conduct initial segmentation. Entropy and energy that extracted from resistivity logging image are matched with Euclidean distance to slightly move boundaries and confirm layer types. Results of practical examples show this method is effective and feasible.