以饱和度测井数据为油藏模型选择标准的改进历史拟合方法

Enhanced history matching process by incorporation of saturation logs as model selection criteria

提出了一种将储集层饱和度测井数据二元简化形式作为油藏模型选择标准的改进历史拟合方法,使用半合成开源油藏模型作为基础模型对提出的方法进行评估,并与常规方法进行了比较。历史拟合阶段引入流体饱和度测井数据,有助于调整或选择能够更好地表征近井地带水驱前缘推进的模型,从而有效降低水驱油藏后续井间干扰评价的不确定性。研究表明,对含水饱和度测井数据进行二元分类时,马修斯相关系数作为分类指标的效果最佳。与常规方法相比,根据提出的方法可以选出一组更可靠的储集层(特别是强非均质性储集层)模型,选出的模型历史拟合效果更好,对近井地带含水饱和度、生产井及其不同层位含水率的拟合质量更好。

This paper proposes a methodology for an alternative history matching process enhanced by the incorporation of a simplified binary interpretation of reservoir saturation logs(RST)as objective function.Incorporating fluids saturation logs during the history matching phase unlocks the possibility to adjust or select models that better represent the near wellbore waterfront movement,which is particularly important for uncertainty mitigation during future well interference assessments in water driven reservoirs.For the purposes of this study,a semi-synthetic open-source reservoir model was used as base case to evaluate the proposed methodology.The reservoir model represents a water driven,highly heterogenous sandstone reservoir from Namorado field in Brazil.To effectively compare the proposed methodology against the conventional methods,a commercial reservoir simulator was used in combination with a state-of-the-art benchmarking workflow based on the Big LoopTM approach.A well-known group of binary metrics were evaluated to be used as the objective function,and the Matthew correlation coefficient(MCC)has been proved to offer the best results when using binary data from water saturation logs.History matching results obtained with the proposed methodology allowed the selection of a more reliable group of reservoir models,especially for cases with high heterogeneity.The methodology also offers additional information and understanding of sweep behaviour behind the well casing at specific production zones,thus revealing full model potential to define new wells and reservoir development opportunities.