综合利用测井资料划分河流沉积微相

IDENTIFYING FLUVIAL MICROFACIES BY SYNTHETICALLY USING LOG DATA

通过比较关键井的测井数据，取心资料及其它地质信息，提出了识别河流沉积5种微相的测井曲线形态，利用高分辨率倾角测井和人工神经网络技术，处理了研究区的测井资料，结合曲线形态分析，对河流沉积微相的测井识别提出了一些新的方法和观点，并与地质家的结论吻合较好。

Comparing key wells log data with the core description and other geological information. Authors figure out five microfacies of fluvial deposition. By means of curve image identification, high resolution dip log data process and artificial nerval network techniques,the log data of research area are succesfully processed and interpreted. Some methods and opinons concerning to fluvial faceies identification are provided ,which coincide very well with the results from geologist.