Enterprise modeling and operational technologies (OT) application in the oil and gas industry

Abstract

Abstract When modeling enterprises, it is necessary to capture, simplify, abstract, and organize a vast number of key organizational elements. These elements (e.g., organizational units, human resources, production processes, and IT systems) are frequently organized and modeled in the business and IT domains. The focus on modeling these domains casts aside other important domains for asset-intensive industries such as operational technologies (OT), which is directly responsible for producing and delivering a company's goods and services. The information produced with OT can be used to generate insight into the production performance, which allows a more accurate decision-making process regarding productivity, its strategy, and within the business. With the rise of trends such as industrial Internet of Things (IoT) and cloud manufacturing, that seek convergence of IT technologies in OT networks, OT and IT analysis are highly sought after in today's industries striving for real-time analysis of data. To analyze the data in the OT and IT domain it is necessary to use models, which not only focus on describing both domains but can also show the relationship between them. In this paper, we present a technique that uses the operational data, produced in an organization, in order to model OT, with the purpose of applying analysis methods as those applied to enterprise modeling. To do so, the technique classifies, structures, and characterizes the information, measurements, and indicators, in a catalog, which is then used to complement an OT metamodel. We illustrate this technique for the oil and gas sector, for which we built an OT indicator catalog, based on an OT metamodel, and created corresponding analysis methods.