Development of a hybrid quantum-classical reservoir simulator and evaluation of quantum computing hardware

该项目将研究量子计算的近期可行性和应用，以应对数值模拟的挑战。首席研究员Zhangxing（John）Chen博士在将数值技术和最近的机器学习应用于油藏模拟方面拥有广泛的专业知识，为能源行业带来了巨大的好处，实现了经济和对环境负责的资源利用，并增强了对数学的理解在地质力学、计算流体动力学和纳米颗粒等各个领域建立模型。陈博士将与量子计算专家巴里桑德斯博士合作，通过将非量子算法分解为模块，然后评估哪些量子算法显示了开发实际实现的潜在起点，以加速这些模块，从而研究量子计算在油藏模拟中的近期应用。这将决定不同技术的可行性，量子计算基础设施所需的容量以及量子计算必须运行多长时间才能解决水库问题。已经识别了几种量子算法，其可以适合于集成到储层模拟软件和储层模拟工作流程中以提供性能改进。该项目将推进这一初步研究，以验证量子计算在油藏模拟中的可行性。这将导致混合量子-经典加速油藏模拟器的设计和验证，该模拟器以有效的方式利用量子和经典计算。这不仅将为一个可以为加拿大能源行业提供许多好处的系统奠定基础，还将为将量子计算整合到许多其他科学学科提供模板，同时为应用量子计算领域提供方向和重要的参考工作。

This project will investigate the near-term viability and application of quantum computing to challenges in numerical simulation. The Principal Investigator, Dr. Zhangxing (John) Chen's extensive expertise in applying numerical techniques, and more recently machine learning, to reservoir simulation has greatly benefitted the energy industry, enabling economic and environmentally responsible utilization of resources, and enhancing the understanding of mathematical modelling in a variety of areas, such as geomechanics, computational fluid dynamics, and nanoparticles. Working with an expert in quantum computation, Dr. Barry Sanders, Dr. Chen will investigate the near-term application of quantum computing to reservoir simulation by decomposing non-quantum algorithms into modules, then assessing which quantum algorithms show potential starting points for development of practical implementations to accelerate these modules. This will determine the viability of different techniques, the required capacity of the quantum computing infrastructure and how long the quantum computation must run to solve a reservoir problem. Several quantum algorithms have been identified that may be suitable for integration into reservoir simulation software and the reservoir simulation workflow to provide performance improvements. This project will advance this preliminary research to proof-of-concept implementations that verify the viability of quantum computing for reservoir simulation. This will result in the design and validation of a hybrid quantum-classical accelerated reservoir simulator, that leverages both quantum and classical computing in an effective manner. Not only will this create a foundation for a system that can provide many benefits to the Canadian energy industry, it will also provide a template for integrating quantum computing into many other scientific disciplines, while providing direction and important reference work for the field of applied quantum computing.