Using Machine Learning to locate geological deposits

使用机器学习来定位地质矿床

• 批准号: 571003-2021
• 负责人: Blum, SusanSC
• 金额: $ 5.46万
• 依托单位: Saskatchewan Polytechnic
• 依托单位国家: 加拿大
• 项目类别: Applied Research and Development Grants - Level 2
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=755288
• 关键词: Using; Machine; Learning; locate; geological

Saskatchewan Polytechnic (SP)'s Digital Integration Centre of Excellence (DICE) and geological experts at Peter Lucas Project Management Inc. (PL) will collaborate on the development of a digital system to locate aggregate sources with a large gravel content. Gravel is a non-renewable resource that is used in almost every aspect of construction. The identification of sources of gravel and the corresponding management of it is important to many different industries. The project will examine the use of machine learning (ML) and or neural network algorithms to determine the probability of a location on a map containing gravel. This resulting technology can help find more sources, will increase supply, save costs, and reduce greenhouse gases due to minimized hauling. The work done in this project expands on previous collaborations between SP DICE and PL that have shown promise.

萨斯喀彻温省理工学院(SP)S数字集成卓越中心(DICE)和Peter Lucas项目管理公司(PL)的地质专家将合作开发一个数字系统，以定位大砾石含量的集合体来源。砾石是一种不可再生资源，几乎用于建筑的方方面面。砾石来源的识别和相应的管理对许多不同的行业都很重要。该项目将研究机器学习(ML)和/或神经网络算法的使用，以确定包含砾石的地图上某个位置的概率。由此产生的技术可以帮助寻找更多的来源，将增加供应，节省成本，并由于最大限度地减少运输而减少温室气体。此项目中所做的工作扩展了SP DICE和PL之间以前的合作，这些合作显示了希望。