Reservoir characterization of petroleum reservoirs can be claimed as one of the most important parts of reservoir management for optimized production and future developments. Through reservoir evaluation, geological zoning for a better comprehension of subsurface structure is needed. For developing a model, porosity plays a vital role; there are two common methods for obtaining this parameter, core samples and well logging. However, the results of these methods are in well scale which cannot be used through field scale modeling. A solution can be the combining seismic field data well log data, which makes it possible to estimate the reservoir properties in field scale. In this study, multi-attribute analyses were applied based on multilayer perceptron to determine the reservoir facies alteration and heterogeneity in the Ghar reservoir of the Hendijan oil field located in the Persian Gulf. Facies modeling was done through the sequential indicator simulation (SIS) algorithm which coupled with the possible trend and indicator kriging (IK) as geostatistical methods. Within the comparison of these two generated models with core facies, the obtained accuracy of SIS algorithm coupled with the possible trend and indicator kriging are 94% and 72%, respectively. Porosity distribution was also done by the sequential Gaussian simulation (SGS) algorithm which resulted the average porosity of 18% in Ghar formation. The SIS method results are compatible with the porosity distribution model obtained from the SGS simulation. The final results prove the robustness of the applied methods for facies and porosity modeling.

中文翻译：

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油田地质统计模拟利用地震数据和测井资料进行储层相和孔隙度建模

石油储层的储层表征可以说是优化生产和未来开发的储层管理中最重要的部分之一。通过储层评价，需要进行地质分区以更好地了解地下结构。对于开发模型，孔隙度起着至关重要的作用；获取该参数有两种常用方法，岩心取样和测井。然而，这些方法的结果是井规模的，不能通过现场规模建模使用。一个解决方案可以是结合地震现场数据测井数据，这使得在现场规模上估计储层特性成为可能。在这项研究中，基于多层感知器的多属性分析，确定了位于波斯湾Hendijan油田Ghar储层的储层相变和非均质性。相建模是通过顺序指标模拟 (SIS) 算法与可能的趋势和指标克里金法 (IK) 结合作为地质统计方法完成的。在这两种生成模型与核心相的比较中，SIS 算法加上可能的趋势和指标克里金法得到的准确率分别为 94% 和 72%。孔隙度分布也由顺序高斯模拟 (SGS) 算法完成，该算法导致 Ghar 地层的平均孔隙度为 18%。SIS 方法的结果与从 SGS 模拟获得的孔隙度分布模型兼容。