致密砂砾岩岩性测井识别方法及应用

 以王府断陷小城子地区登娄库组和营城组为例，研究了致密砂砾岩岩性测井识别方法及其应用。利用录井岩性资料总结登娄库组、营城组各种岩性的组分，并提取2 个层组的主要岩性，登娄库组主要岩性为砂砾岩、砂岩和泥岩，营城组主要岩性为砾岩、砂砾岩和泥岩；分析不同岩性的测井响应特征，并提取2 个层组的岩性敏感参数，登娄库组为自然伽马、中子、声波时差和电阻率，营城组为自然伽马、中子和密度。利用SPSS 软件建立登娄库组和营城组的岩性Fisher 判别模型，将该模型应用于未参与建模的5 口井储层岩性的识别，识别准确率达86%，证明了该方法的可靠性。

Logging Lithology Identification of Tight Sandy Conglomerate and Its Application

Taking the sandy conglomerate reservoirs of Denglouku and Yingcheng Formations in Xiaochengzi area, Wangfu Fault as an example, the logging lithology identification is studied in this paper. Based on the logging lithology data, various lithologic compositions of objective intervals are analyzed and the main lithology components of Denglouku and Yingcheng Formations are extracted firstly. The main components of Denglouku Formation are the sandy conglomerate, the sandstone and the shale and those of Yingcheng Formation are the conglomerate, the sandy conglomerate and the shale. Then the logging response characteristics are analyzed, the lithologic parameters of these two formations are extracted and it is shown that the sensitive parameters of Denglouku Formation are the natural gamma ray (GR), the neutron (CNL),the interval transit time (AC) and the resistivity (RT) and that the parameters of Yingcheng Formation are the GR, the density (DEN) and the CNL. Finally, the Fisher model of the lithology identification is established by using the SPSS software, and the application of the model to the reservoir lithology identification of five wells not included in the process of building the model shows that the discriminant accuracy rate reaches 86%, which indicates a high reliability of the method.