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Significance of the amplitude attribute in porosity prediction, Drava Depression Case Study

机译：振幅属性在孔隙度预测中的意义，德拉瓦凹陷案例研究

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摘要

All types of reservoirs are characterized by difficulties in predicting their petrophysical properties mainly due to frequent lithological heterogeneity. It is particularly valid for coarse-grained clastic reservoirs, which include different matrixes, granulometry and different portions of primary and secondary porosities. Several methods could help their description. One of them is the several physical attributes seismic analysis , which provides more or less reliable rock, pore space and pore fluid description. The seismic amplitude, as well as reflection strength, is one of the most frequently used attributes in the analysis. This attribute is especially useful in porosity prediction. It may be applied in different geostatistical and neural interpolation methods as a very valuable secondary source of information. This article describes the amplitude attribute analysis performed in the main reservoir of the Benicanci oil field. The reflection strength attribute was used as a secondary variable, applied in cokriging interpolation of porosity selected as the primary variable. Spearman rank correlation was r=-0.64 calculated for the pair porosity-reflection strength. The use of secondary information led to significantly better porosity prediction. Such analysis may be considered a very favorable procedure for describing the clastic reservoir in the Drava depression.
机译：所有类型的储层的特征在于，由于频繁的岩性非均质性，很难预测其岩石物理性质。对于粗粒状碎屑储层尤其有效，该储层包括不同的基质，粒度以及初次和二次孔隙的不同部分。有几种方法可以帮助描述它们。其中之一是地震分析的几种物理属性，它或多或少提供了可靠的岩石，孔隙空间和孔隙流体描述。地震幅度以及反射强度是分析中最常用的属性之一。此属性在孔隙率预测中特别有用。它可以作为非常有价值的次要信息来源应用于不同的地统计学和神经插值方法中。本文介绍了在Benicanci油田主油藏中进行的振幅属性分析。反射强度属性用作辅助变量，应用于选定的主要变量的孔隙度的cokriging插值。对于成对的孔隙率-反射强度，Spearman等级相关性为r ＝ -0.64。使用次要信息可以显着改善孔隙率预测。这样的分析可以被认为是描述德拉瓦洼地碎屑岩储层的非常有利的过程。

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