沉积微相定量研究方法

Quantitative study on sedimentary microfacies

松辽盆地四五家子油田白垩系泉头组二段的Ⅰ—Ⅳ砂层组的自然电位及自然伽马曲线特征不很明显。在区域沉积背景、基本沉积特征及单井相分析的基础上 ,结合微相标志及测井曲线形态 ,认为该砂层组主要为曲流河沉积 ,发育曲流河点坝、决口扇、天然堤及泛滥平原等 4种沉积微相。优选出识别沉积微相类型的主要特征参数 (孔隙度、泥质含量及砂岩百分含量 ) ,应用Bayes逐步判别方法建立了各微相的判别函数 ,定量识别 13 6口非取心井的沉积微相 ,正判率达 90 %以上 ;继而应用顺序指示模拟方法预测井间沉积微相。在 13 6口井中抽取 8口作为检验井 ,用上述方法重新模拟 ,进行抽稀检验统计 ,7口井预测结果与实际相符合 ,证明此预测方法是行之有效的。图 3表 1参

The I IV sandstone units of Member 2, Quantou Formation (Cretaceous), Siwujiazi Oilfield in the Songliao Basin, is characterized by poorly defined spontaneous potential and gamma ray logs. By analysing the regional sedimentary environments, sedimentary structures, single well facies, as well as microfacies markers and logging curves, four microfacies are recognized, including meandering stream point bars, crevasse splays, natural levees and flood plains. Four important parameters have been selected as indicators of microfacies, including porosity, shaliness, and sand percentage; these are used to build a discriminance function for each microfacies by using Bayes Successive Discriminate Analysis. The quantitatively identified microfacies for 136 uncored wells of the Siwujiazi Oilfield are modeled and tested, attaining an accuracy exceeding 90%.