Fault zones in porous sandstones are commonly divided into two parts: a fault core and a damage zone. Both fault zone elements could influence sub-surface fluid flow and should be incorporated in a geologically realistic model. The fault core can be implemented in the model as a transmissibility multiplier (TM) while the damage zone can be implemented by modifying the grid permeability in the cells adjacent to the model faults. Each of the input parameters used in calculating the TM and damage zone permeability modification is subject to geological uncertainty. Here an iterative workflow is employed to define probability distribution functions for each of the input parameters, with the result being many fault model realisations. Here two methods are examined for ranking and selecting the fault model realisations for further analysis: i) calculating flow indicator fault properties (effective cross-fault transmissibility and effective cross-fault permeability) from the static model, and ii) employing a simplified flow-based connectivity calculation, returning dynamic measures of model connectivity. The aims are to outline the methodology and workflow used, evaluate the impact of the different input parameters on the results, and examine the results of the static and dynamic approaches to understand how the ranking and selection of models compares between the two. Our results are dependent on the structural model. In a strongly compartmentalised model based on the Gullfaks field, North Sea, fluid flow indicator fault properties are weakly correlated with measures of dynamic behaviour. In particular, models with low fault transmissibility show a much greater range of dynamic behaviour, and are less predictable, than models with high fault transmissibility. In a weakly compartmentalised model with strongly channelised fluvial facies based on the Whitley Bay area in northeast England, there was a strong correlation between flow indicator fault properties and measures of dynamic behaviour. We ascribe these results to the greater complexity of flow paths expected when a highly compartmentalized model contains faults that are likely to be baffles to cross-fault flow. Thematic collection: This article is part of the Fault and top seals collection available at: https://www.lyellcollection.org/cc/fault-and-top-seals-2019

中文翻译：

---

使用流量指示器故障属性和简单的流线模拟对故障模型进行排序和选择

多孔砂岩中的断层带通常分为两部分：断层核和损伤带。两个断层带元素都可能影响地下流体流动，应纳入地质现实模型中。断层核心可以在模型中作为传输系数 (TM) 来实现，而损坏区域可以通过修改与模型断层相邻的单元中的网格渗透率来实现。用于计算 TM 和损伤带渗透率修正的每个输入参数都受地质不确定性的影响。这里采用迭代工作流为每个输入参数定义概率分布函数，结果是许多故障模型实现。这里检查了两种用于对故障模型实现进行排序和选择以进行进一步分析的方法：i) 从静态模型计算流动指标故障特性（有效跨断层传导率和有效跨断层渗透率），以及 ii) 采用简化的基于流动的连通性计算，返回模型连通性的动态测量。目的是概述所使用的方法和工作流程，评估不同输入参数对结果的影响，并检查静态和动态方法的结果，以了解模型的排名和选择如何在两者之间进行比较。我们的结果取决于结构模型。在基于北海 Gullfaks 油田的强划分模型中，流体流动指标断层特性与动态行为的测量值相关性较弱。特别是，与具有高故障传递率的模型相比，具有低故障传递率的模型显示出更大范围的动态行为，并且更难预测。在基于英格兰东北部惠特利湾地区的具有强烈沟渠化河流相的弱分区模型中，流动指标断层特性与动态行为测量之间存在很强的相关性。我们将这些结果归因于当高度划分的模型包含可能成为交叉断层流的挡板的断层时，预期流动路径的更大复杂性。专题收藏：本文是断层和顶部海豹收藏的一部分，可在以下网址获取：https://www.lyellcollection.org/cc/fault-and-top-seals-2019 在基于英格兰东北部惠特利湾地区的具有强烈沟渠化河流相的弱分区模型中，流动指标断层特性与动态行为测量之间存在很强的相关性。我们将这些结果归因于当高度划分的模型包含可能成为交叉断层流的挡板的断层时，预期流动路径的更大复杂性。专题收藏：本文是断层和顶部海豹收藏的一部分，可在以下网址获取：https://www.lyellcollection.org/cc/fault-and-top-seals-2019 在基于英格兰东北部惠特利湾地区的具有强烈沟渠化河流相的弱分区模型中，流动指标断层特性与动态行为测量之间存在很强的相关性。我们将这些结果归因于当高度划分的模型包含可能成为交叉断层流的挡板的断层时，预期流动路径的更大复杂性。专题收藏：本文是断层和顶部海豹收藏的一部分，可在以下网址获取：https://www.lyellcollection.org/cc/fault-and-top-seals-2019 我们将这些结果归因于当高度划分的模型包含可能成为交叉断层流的挡板的断层时，预期流动路径的更大复杂性。专题收藏：本文是断层和顶部海豹收藏的一部分，可在以下网址获取：https://www.lyellcollection.org/cc/fault-and-top-seals-2019 我们将这些结果归因于当高度划分的模型包含可能成为交叉断层流的挡板的断层时，预期流动路径的更大复杂性。专题收藏：本文是断层和顶部海豹收藏的一部分，可在以下网址获取：https://www.lyellcollection.org/cc/fault-and-top-seals-2019