Flow Diagnostics for Fractured Carbonate Reservoirs

准确描述天然裂缝的静态和动态特征是从碳酸盐岩储层中成功开采油气的基础，因为(I)裂缝在碳酸盐岩地层中普遍存在，(Ii)裂缝可能导致早期见水和低最终采收率，以及(Iii)裂缝是不确定性的主要来源。支持油藏开发的经典产量预测方法是建立一个或多个静态模型，将选定的模型转换为动态模型，并根据生产数据进行黑油或成分油藏模拟。这是一种耗时的方法，往往不能解决由于资产团队固有的时间限制而产生的各种地质不确定性。因此，储集层模型往往具有有限的保质期，需要频繁修改，导致错失经济机会。该项目将以石油工程研究所的碳酸盐岩储集组(http://carbonates.hw.ac.uk/))为基础，结合挪威石油工程研究所和挪威国家石油工程研究所的长期研究工作。使用最先进的开源MatLab油藏模拟工具箱MRST(http://www.sintef.no/Projectweb/MRST/)，)，该项目将扩展和应用一种名为“流动诊断”的新技术，以改进裂缝性碳酸盐岩油藏的经典油藏特征和模拟工作流程。流动诊断技术可在数百万单元静态模型的网格块上直接计算和可视化关键的动态油藏属性(例如，排水和波及油藏体积、突破时间、递减率、甜蜜点、井位分配系数)，时间可以忽略不计。因此，流动诊断工具使我们能够快速近似多个静态油藏模型的动态响应，以估计它们的生产行为，而无需运行计算密集的全物理油藏模拟。流动诊断工具的结果可用于根据静态油藏模型的动态响应对其进行筛选、分级和分类，从而提供了一种稳健而有效的方法来识别生产趋势，同时考虑到不确定性。

The accurate static and dynamic characterisation of natural fractures is fundamental to successful hydrocarbon recovery from carbonate reservoirs because (i) fractures are ubiquitous in carbonate formations, (ii) fractures can cause early water breakthrough and low final recovery, and (iii) fractures are a primary source of uncertainty. The classical approach to production forecasting in support of reservoir development is to build one or more static models, translate selected models into dynamic models, and perform Black-Oil or compositional reservoir simulations that are tuned to production data. This is a time-consuming approach that often does not address the full range of geological uncertainties due to time limitations inherent to asset teams. Therefore, reservoir models tend to have limited shelve-life and require frequent modifications, leading to missed economic opportunities.This project will be based at the Carbonate Reservoir Group (http://carbonates.hw.ac.uk/) at the Institute of Petroleum Engineering (IPE) and combines long-standing research efforts from IPE and SINTEF in Norway. Using the state-of-the-art Open Source Matlab Reservoir Simulation Toolbox MRST (http://www.sintef.no/Projectweb/MRST/), the project will extend and apply a novel technology termed "flow diagnostics" to improve classical reservoir characterisation and simulation workflows for fractured carbonate reservoirs. Flow diagnostics calculate and visualise key dynamic reservoir properties (e.g. drained and swept reservoir volumes, time-to-breakthrough, decline rates, sweet spots, well-allocation factors) directly on the grid blocks of multi-million cell static models in negligible time. Flow diagnostic tools hence allow us to quickly approximate the dynamic response of multiple static reservoir models to estimate their production behaviour without running computationally intensive full-physics reservoir simulations. Results from flow diagnostics tools can be used to screen, rank, and cluster static reservoir models based on their dynamic response, offering a robust and efficient way to identify production trends while accounting for uncertainty.