How underground lithologies respond to thermo-mechanical coupling during energy extraction/storage.

在我们寻求使能源资源脱碳的过程中，地下热能储存是一个关键因素。然而，长期频繁的循环热机械(TM)应力变化的影响仍然知之甚少，并可能威胁到系统的寿命。该项目旨在通过在相关循环TM载荷条件下进行实验室和数值实验来填补这一空白，以调查此类系统中目标岩性的稳定性。为了应对能源转型的挑战，新的地下解决方案要么侧重于新资源的开采(地热)，要么侧重于储存(放射性废物、热能和/或天然气-地下储气、压缩空气储能、氢、二氧化碳)。所有这些应用都会引起新的、浅层的、周期性的局部热机械应力变化。这个PHD项目的范围是使用不同尺度的观测来模拟和预测地下复杂系统中目标岩性的稳定性，当这些系统受到长时间周期性TM应力变化时。这项研究工作试图了解颗粒尺度的变形如何有助于地下系统的全球响应，以及如何控制这种响应以减少任何伴随的诱发灾害。将采用一种创新的方法，结合实验室和数值实验，扩大对多孔岩石中热敏性脆性变形过程的理解。这些数据将为涉及周期性TM应力变化的野外操作条件提供信息，并揭示潜在的层叠浅层地质灾害。目标：O1：检查微构造变形与TM应力之间的关系。O2：收集、分析和建模TM数据。03：将现有的DEM代码从UDEC转移和改进到开源，并进行粒度敏感性分析。O4：提供相关数据，以了解地下地质存储条件下与TM应力相关的风险。实验室实验将在不同的尺度(从颗粒到样本尺度)进行。岩心样品将在HWU进行X射线扫描，以了解其内部3D微结构，并在TM实验前后(O1)评估其传输特性(孔隙率和渗透率)。TM实验将在BGS进行，以模拟升高的环境条件。将调查几种变形情况，以涵盖不同的工业现场操作。这些实验室规模的全球传感数据将与岩相学分析(O2)相结合，以将实验室诱导的损伤在测试材料中的时空分布与微观结构演变相关联。此外，可能还计划用同步变形监测(x射线)进行类似的颗粒尺度实验，以揭示微观过程。目前，数值建模和机器学习技术被更频繁地用来预测次表面系统的行为。TM耦合校准的Voronoi颗粒模型(GBM)可以捕捉微裂纹作为渐进损伤的一种机制，再现实验室测试的应力-应变行为。发展这样的模型将有助于理解TM脆性损伤是如何跨尺度发展的，从颗粒尺寸破裂到岩石破裂，以及它的时间依赖性。这个博士项目将建立在伍德曼等人开发的DEM基础上。(2021)主要进行热-机械模拟(O3)中的颗粒大小和分布敏感性分析，以进一步评估将实验室数据放大到现场尺度(O4)。

On our quest to decarbonise our energy resources, underground heat energy storage is a key player. However, the impact of frequent cyclic thermo-mechanical (TM) stress changes over prolonged periods remains poorly understood and may threatened the longevity of the systems. This project aims to fill this gap by performing laboratory and numerical experiments under relevant cyclic TM loading conditions to investigate the stability of targeted lithologies in such systems. To address the energy transition challenges, new subsurface solutions focus either on new resources exploitation (geothermal) or storage (radioactive waste, heat and/or gas -underground gas storage, compressed-air energy storage, H, CO2). All these applications have in common to induce new, shallow, periodic, local thermo-mechanical stress changes. The scope of this PhD project is to use different-scale observations to model and predict the stability of targeted lithologies in underground complex systems when those are subjected to cyclic TM stress changes over prolonged periods. This research work seeks to understand how grain-scale deformation can contribute to the global response of the underground systems and how this response can be controlled to reduce any accompanied induced hazards. An innovative methodology, combining laboratory and numerical experiments, will be applied to extend the understanding of the thermo-sensitive brittle deformation processes in porous rocks. The data will provide information to support field-scale operational conditions involving periodic TM stress changes as well as shed light on potential cascading shallow geohazards.Objectives:O1: Examine the relationship between microstructural deformation and TM stresses.O2: Collect, analyse and model TM data together.O3: Transfer and improve existing DEM code from UDEC to open source and undertake grain size sensitivity analysis.O4: Provide relevant data to inform on risks associated to TM stresses in underground geological storage conditions.Laboratory experiments will be performed at different scales (from grain to sample scales). Core samples will be x-ray scanned at HWU to understand their internal 3D microstructure and assess their transport properties (porosity and permeability) at pre- and post-TM experiments (O1). TM experiments will be performed at BGS to simulate elevated environmental conditions. Several deformation scenarios will be investigated to cover different industrial field operations. This lab-scale global sensing data will be combined to petrographical analysis (O2) to correlate the spatiotemporal distribution of the lab-induced damage within the tested materials with the microstructural evolution. Moreover, similar grain-scale experiments with syn-deformation monitoring (x-rays) are possibly planned to unravel the micro-scale processes. Numerical modelling and machine learning techniques are nowadays used more frequently to predict the subsurfacesystem behavior. TM coupling calibrated Voronoi Grain Based Modelling (GBM) can capture micro-cracking as a mechanism of progressive damage, reproducing the stress-strain behavior of laboratory tests. Developing such models will help to understand how TM brittle damage develops across the scales, from grain-size cracking to rock mass fracturing, and its time dependency. This PhD project will build on the DEM developed by Woodman et al. (2021) to undertake notably a grain size and distribution sensitivity analyses in thermo-mechanical simulations (O3) to further assess the up scaling of laboratory data to field scale (O4).