Detection of reservoir quality using Bayesian seismic inversion
Detection of reservoir quality using Bayesian seismic inversion
复制标题
DOI：
10.1190/1.2713043
复制
发表时间：
2007-04
期刊：
影响因子：
3.3
通讯作者：
J. Gunning;M. Glinsky
中科院分区：
文献类型：
--
作者：
J. Gunning;M. Glinsky
分选是渗透率的有用预测器。我们展示了如何反演地震数据的渗透性岩石分选参数，通过将概率岩石物理模型与浮动颗粒到贝叶斯地震反演代码，直接对岩石物理变量。贝叶斯先验包含弹性性质、孔隙度和浮动颗粒分选参数之间的耦合。反演使用基于地震振幅的似然和前向卷积模型来生成后验分布，该后验分布包含浮动颗粒参数及其不确定性的精确估计。后验分布使用马尔可夫链蒙特卡罗方法计算。我们检查的测试用例表明，即使在与边界岩性对比不强的困难情况下，只要数据的信噪比S/N有利，也可以从该反演中获得有关分选特征和孔隙度的重要信息。这些测试案例表明，对于峰值S/N为6：1的情况，孔隙度和浮粒含量的估计标准差分别提高了约25%和15%。浮粒含量的完整后验分布更具代表性，并显示出增强的分离，分为两组干净和分选不良的岩石。即使在我们检查的更困难的测试案例中也是如此，其中值得注意的是，分层的净-总比值没有通过反演过程得到显著提高。
Sorting is a useful predictor for permeability. We show how to invert seismic data for a permeable rock sorting parameter by incorporating a probabilistic rock-physics model with floating grains into a Bayesian seismic inversion code that operates directly on rock-physics variables. The Bayesian prior embeds the coupling between elastic properties, porosity, and the floating-grain sorting parameter.The inversion uses likelihoods based on seismic amplitudes and a forwardconvolutionalmodeltogenerateaposteriordistribution containing refined estimates of the floating-grain parameter anditsuncertainty.Theposteriordistributioniscomputedusing Markov Chain Monte Carlo methods. The test cases we examineshowthatsignificantinformationaboutbothsorting characteristics and porosity is available from this inversion, even in difficult cases where the contrasts with the bounding lithologies are not strong, provided the signal-to-noise ratio S/N of the data is favorable. These test cases show about 25% and 15% improvements in estimated standard deviationsforporosityandfloating-grainfraction,respectively,for peak S/N of6:1.The full posterior distribution offloatinggraincontentismoreinformative,andshowsenhancedseparationintotwoclustersofcleanandpoorlysortedrocks.This holds true even in the more difficult test case we examine, wherenotably,thelaminatedreservoirnet-to-grossisnotsignificantlyimprovedbytheinversionprocess.