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.

断裂岩石承载生产性含水层，它们是增强型地热系统（EGS）的目标。这些学科共同面临的一个主要挑战是对与流动和运输过程相关的结构特征或断裂系统进行适当的表征。表征越准确，通过数值模型模拟的过程就越可靠。数值模拟技术的最新发展令人印象深刻，在计算效率、现实、高分辨率和耦合模拟方面的能力不断提高。尽管如此，数值模式的相关数据饥饿几乎没有得到可用的实地测量。特别是每个现场的独特特征，如裂缝几何形状，需要协调现场调查技术。即使对一个地点进行了充分的调查，也需要将测量数据整合到模型中的方法。该项目建议使用层析成像钻孔测试，并注入水和示踪剂，以识别和表征与流动和运输相关的裂缝。通过结合多个井孔的跨井多级测试的见解，促进了裂缝几何形状的重建。一个主要的新元素是反演记录的层析成像信号的多功能贝叶斯方法，反复调整裂缝的方向，长度和裂缝密度（逆模型）。这与离散裂缝网络（正演模型）的灵活和快速的数值实现和模拟相结合。受到有前途的初步结果，建议的层析离散裂缝反演方法在这里进一步发展的两个（2D）和三维（3D）系统中的断裂概率的鲁棒估计。利用虚拟钻孔测试的合成数据以及裂缝岩石原位实验的压力和热示踪数据，对该方法进行了阐述和论证。