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一种基于变骨架参数的孔隙度预测新方法
引用本文:申波,王刚,樊海涛,张金风,李彦普. 一种基于变骨架参数的孔隙度预测新方法[J]. 石油与天然气地质, 2022, 43(3): 711-716. DOI: 10.11743/ogg20220319
作者姓名:申波  王刚  樊海涛  张金风  李彦普
作者单位:1.长江大学 油气资源与勘探技术教育部重点实验室,湖北 武汉 4300102.长江大学 地球物理与石油资源学院,湖北 武汉 4300103.中国石油 新疆油田分公司 勘探开发研究院,新疆 克拉玛依 8340004.中国石油 新疆油田分公司 吉庆油田作业区,新疆 吉木萨尔 83170025.中国石油 大港油田分公司 第一采油厂,天津 300280
基金项目:国家自然科学基金项目(41504103);
摘    要:利用测井资料计算储层孔隙度是测井定量评价的基础内容,储层孔隙度计算是否准确直接影响到后续的储层评价可靠性.对于岩矿组分复杂地层,如何快速、准确地开展孔隙度测井评价是复杂储层解释与评价的首要问题.A凹陷L组发育凝灰质砂岩储层,由于砂质成分复杂多变,且受后期成岩作用影响,导致不同层位骨架测井响应规律存在明显差异,进而导致基...

关 键 词:主成分分析  变骨架参数  复杂岩石组分  凝灰质砂岩  孔隙度预测  储层评价
收稿时间:2021-01-06

A new method for porosity prediction based on variable matrix parameters
Bo Shen,Gang Wang,Haitang Fan,Jinfeng Zhang,Yanpu Li. A new method for porosity prediction based on variable matrix parameters[J]. Oil & Gas Geology, 2022, 43(3): 711-716. DOI: 10.11743/ogg20220319
Authors:Bo Shen  Gang Wang  Haitang Fan  Jinfeng Zhang  Yanpu Li
Abstract:Porosity prediction from logging data is a common practice of quantitative evaluation of hydrocarbon reservoirs. The accuracy of reservoir porosity calculation directly affects the reliability of subsequent reservoir evaluation. For evaluating reservoirs with complex mineral components, the main challenge is how to quickly and accurately predict the porosity with logging data. One such example is the tuffaceous sandstone reservoir developed in L Formation of A Sag. Its complex and changeable sandy composition and late diagenesis result in logging responses varying significantly from one layer to another, making the applicability of the single-porosity model built based core-calibrated logging data and multivariate statistical method to porosity calculation of these layers rather questionable. To tackle the issue, this study proposes a porosity prediction method based on variable matrix parameters by using a volume physical model and through principal component analysis. Porosity prediction by using the method with actual logging data fits well with core analysis results and the workflow for separate-layer porosity interpretation is simplified. The method may serve as a certain reference for the prediction of porosity of rocks with complex components.
Keywords:principal component analysis  variable matrix parameter  complex rock component  tuffaceous sandstone  porosity prediction  reservoir evaluation  
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