Predictive Analytics for Risk Avoidance

该项目的目标是建立一个架构或框架结构，以便进行搜索和挖掘 化工和石油天然气工业基础设施安全相关事件的数据集。的工具 然后将应用预测性分析来提取关于潜在的厌恶识别情况和/或 基础设施未来运行中的可能状态。根据提取的信息，它可能是 可能以这样的方式实施、修改、操作或采取纠正措施 不良事件有可能被预防或避免。 该项目将侧重于识别、定义数据并将其转换为常见的结构化数据格式 来自化工和油气开采行业的所有不同数据来源。资料分析 技术将专注于构建算法和其他概率方法来执行预测 对从不同来源获得并整合用于基准测试的数据进行分析。有用的工作应该是 然后，允许查询数据、创建摘要、分布、趋势、预测、预测 综合可用数据的概率、报告和图表。引用印孚瑟斯公司的凯坦·普里的话： 石油和天然气行业的工作数据可以被描述为一个漏斗，原始数据在一端，可用 在这个项目中，对数据的正确解释将增加决策的确定性 培养安全管理人员/专业人员，使基础设施的运行更安全。 这项工作与公司的相关性在于，开发的软件将使公司能够提供 为工业设施提供的服务，该服务将预测设施中可能发生的不良事件 概率随附。

The aim of the project is to establish an architecture, or framework structure, to allow for searching and mining datasets of safety related events in the chemical and oil and gas industrial infrastructures. The tools of predictive analytic will then be applied to extract information on potential averse identified situations and/or probable states in future operations of the infrastructures. Based on the extracted information it might be possible to implement, modify, operations, or take corrective actions in such a manner that the predicted adverse events are potentially prevented or avoided. The project will focus on identifying, defining and transforming data into a common structured data formats coming from all different data sources in the chemical and oil and gas extraction industries. Data analysis techniques will focus on building algorithms, and other probabilistic methodologies to perform predictive analytic on the data that is obtained and integrated for benchmarking from various sources. Useful work should then be possible, allowing to query data, create summaries, distributions, trends, projections, predictive probabilities, reports and charts of the integrated available data. To quote Ketan Puri of Infosys: "The way the oil and gas industry works with data can be depicted as a funnel, with raw data going in one end and usable data coming out of the other". In this project the correct interpretation of data will increase certainty in decision making of safety managers / professionals resulting in safer operations of the infrastructures. The relevance of the work for the company is that the software developed will enable the company to offer a service for industrial facilities that will predict the potential occurrence of adverse events at the facilities with a probability attached.