SIGMA - Study of Industrial Gravity Measurement Applications

Sigma-“工业重力测量应用研究”项目是RSK和伯明翰大学(UOB)合作开展的一项可行性研究，旨在确定量子技术(QT)重力传感器在环境和工程应用中的潜力，如定位埋藏物和发现空洞。这些QT传感器目前还不存在，但它们是英国大学许多研究活动的重点，例如大华大学的GG-TOP项目开发了一种重力梯度传感器，如果获得资金，计划将更多的传感器开发作为大华大学领导的QT中心的一部分。QT传感器要实现加速商业化，关键是要确保其满足用户需求。因此，该项目将评估目前的地球物理传感技术，确定它们的局限性和操作参数。这将允许提供一个量化评估矩阵，可以根据该矩阵来判断QT传感器。在第二步，该项目将评估环境和仪器噪声，并将其纳入正演模型。这将提供有关QT传感器必要的灵敏度和可容忍的噪声水平的信息。最终，建立将测量信号与地下埋藏特征联系起来的反演模型将是有益的。寻求创建新的反演工具不在本项目的范围内，但是可以使用远期模型的输出来评估商业市场上现有的反演工具的能力，并规定

The SIGMA - 'Study of Industrial Gravity Measurement Applications' project is a collaboration between RSK and theUniversity of Birmingham (UoB) to carry out a feasibility study identifying the potential of Quantum Technology (QT) gravitysensors in geophysical surveys for environmental and engineering applications such as locating buried objects and findingvoids. These QT sensors currently do not exist, but are the focus of many research activities in UK universities such as theGG-TOP project at the UoB developing a gravity gradient sensors with many more sensor developments planned as part ofthe UoB led QT Hub, if funded. For the QT sensors to achieve an accelerated commercialization, it is vital to ensure thatthey meet user needs. Therefore, this project will assess the current geophysical sensing technologies, establish theirlimitations and also operational parameters. This will allow provide a quantitative assessment matrix against which the QTsensors can be judged. It will further provide those developing the QT sensors with a specification of capability to strive for.In a second step, this project will assess environmental and instrument noise and incorporate these into a forward model.This will provide information on the necessary sensitivity and tolerable noise levels for the QT sensors. Ultimately, it will benecessary to develop inversion models, which relate the measured signals to buried features in the ground. It is not withinthe scope of this project to seek to create new inversion tools, however it is possible to use the output from the forwardmodels to evaluate the capability of existing inversion tools available in the commercial market, and to prescribe theadditional requirements of a