Stochastic characterization of discrete fractures in rock by hydraulic and tracer tomography

通过水力和示踪断层扫描对岩石中离散裂缝进行随机表征

• 批准号: 401048478
• 负责人: Professor Dr. Peter Bayer
• 金额: --
• 依托单位: Abteilung Ingenieurgeologie
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2018
• 资助国家: 德国
• 起止时间: 2017-12-31 至 2021-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/401048478?language=en
• 关键词: Stochastic; characterization; discrete; fractures; rock

Fractured rocks host productive aquifers and they are the target for enhanced geothermal systems (EGS). A major challenge shared by these subjects is the appropriate characterization of structural features or fracture systems that are relevant for flow and transport processes. The more accurate the characterization, the more reliable the processes can be simulated by numerical models. Recent developments in numerical modelling techniques are impressive, with growing capabilities in computationally efficient, realistic, high-resolution and coupled simulation. Still, the associated data hunger of numerical models is barely fed by available field measurements. Especially features unique for each site, such as fracture geometries, require attuned site investigation techniques. And even if a site is well investigated, methods are needed for integrating measured data in a model. This project proposes the use of tomographic borehole tests with water and tracer injection to identify and characterize fractures relevant for flow and transport. By combining the insight from cross well multi-level tests in several boreholes, the reconstruction of fracture geometries is facilitated. A major novel element is the inversion of recorded tomographic signals by a versatile Bayesian approach that adjusts iteratively fracture orientations, lengths and fracture density (inverse model). This is combined with a flexible and fast numerical implementation and simulation of the discrete fracture network (forward model). Motivated by promising preliminary results, the proposed tomographic discrete fracture inversion approach is here further developed for robust estimation of fracture probabilities in two- (2D) and three-dimensional (3D) systems. It is elaborated and demonstrated utilizing synthetic data from virtual borehole tests, as well as by means of pressure and heat tracer data from in-situ experiments in fractured rock.

破裂的岩石宿主生产含水层，它们是增强地热系统（例如）的目标。这些受试者分享的一个重大挑战是与流程和运输过程相关的结构特征或断裂系统的适当表征。表征越准确，可以通过数值模型来模拟该过程的可靠性。数值建模技术的最新发展令人印象深刻，在计算高效，现实，高分辨率和耦合模拟方面的能力越来越不断增长。尽管如此，数值模型的相关数据饥饿几乎没有通过可用的现场测量结果喂养。尤其是每个站点独特的特征，例如断裂几何形状，都需要调整的现场调查技术。即使对站点进行了充分的研究，也需要使用模型中的测量数据进行整合的方法。该项目建议使用水和示踪剂注入层造影孔测试来识别和表征与流量和运输相关的裂缝。通过在几个钻孔中结合跨井多层次测试的见解，促进了断裂几何形状的重建。一个主要的新元素是通过多功能的贝叶斯方法的记录层析成像信号反转，该方法可调节迭代断裂方向，长度和断裂密度（反向模型）。这与离散断裂网络（正向模型）的灵活且快速的数值实现和模拟相结合。在这里，在这里进一步开发了拟议的层析成像离散裂缝反演方法的动机，以促进两（2D）和三维（3D）系统中的断裂概率的稳健估计。它是通过虚拟钻孔测试的合成数据进行详细阐述和证明的，以及通过断裂岩石中的原位实验的压力和热示踪数据。