摘要
孔隙度是描述储层品质的一个重要参数,对生产开发和储量估计具有重要的意义。针对常规测井计算孔隙度准确率不高的情况,本文提出了利用逐步回归分析预测孔隙度,建立了一元回归与多元回归孔隙度预测模型,分析认为利用声波和密度建立的孔隙度预测模型为最佳的预测模型。结果表明,在川西地区岩性变化快、砂岩储层非均质性强、孔隙度值变化大的地质条件下,该模型获得了最佳的预测效果,与实际的地质情况吻合率较高〔1〕。
Porosity is a important parameter describing the quality of container rock, it is of far reaching importance to production development and estimation of reserves. Considering the low identification curacy of conventional well logging, the writer has adopted stepwise regression analysis to forecast porosity, and established porosity forecasting model of monadic regression and multielemental regression. Then, the writer believes that the best forecasting model is porosity forecasting model using sonic wave and density. The result shows that this model gains the best forecasting effect and largely fits for actual geologic conditions, on the geologic conditions of rapidly lithology changing, strong sandstone container rock anisotropic and big porosity value in west of Sichuan province.
出处
《内蒙古石油化工》
CAS
2006年第11期139-142,共4页
Inner Mongolia Petrochemical Industry
关键词
逐步回归
孔隙度预测
致密砂岩
岩芯归位
储层识别
stepwise regression
porosity forecasting
compact sandstone
core parked
identification of container rock