一种基于变骨架参数的孔隙度预测新方法

A new method for porosity prediction based on variable matrix parameters

申波 王刚 樊海涛 张金风 李彦普

Bo Shen Gang Wang Haitang Fan Jinfeng Zhang Yanpu Li

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，进而导致基于岩心刻度测井的单孔隙度模型以及基于多元统计方法的孔隙度解释结果存在一定的适用性问题。以体积物理模型为基础，以主成分分析为手段，根据岩石骨架参数降维结果提出一种基于变骨架参数的孔隙度预测方法。实际资料处理结果表明，该方法预测结果与岩心分析结果吻合较好，且简化了分层段处理的解释流程，对复杂岩石组分的孔隙度预测具有一定借鉴意义。

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.

10.11743/ogg20220319