Designing and Developing High-Confidence Petroleum Extraction Cyber-Physical System Using the Model-Driven Architecture
Huawei Zhai, Licheng Cui, Weishi Zhang, Lijia Zhou, Xiuguo Zhang · 2019
In modern petroleum extraction industry, Internet of Things (IoT) technology is widely used, and various of sensors constitute a typical cyber-physical systems (CPS). There are more requirements of interoperability and interaction between well site device systems. In such industrial critical domain, high-confidence is also important. This paper presents the requirements and running environment of developing high-confidence CPS. To satisfy the requirements of interoperability and data exchange among heterogeneous well site systems, a foundation framework with well defined interfaces and quality of service constraints was established. Based on this framework, designing high-confidence petroleum extraction CPS using Model-Driven Architecture approach is proposed, the long-lived models produced in the process that can be applied to any implementation technologies and platforms through model transformation which make the systems more portable. A case study shows the detail of the development process and using communication bridges to build relationships between models. At last some important problems which need to be paid more attention in model transformation process are discussed.