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Rig State Identification and Equipment Optimization Using IoT Solutions

Hadi Mustapha

Rig State Identification and Equipment Optimization Using IoT Solutions.

Rel. Giovanni Andrea Blengini. Politecnico di Torino, Corso di laurea magistrale in Petroleum And Mining Engineering (Ingegneria Del Petrolio E Mineraria), 2022

Abstract:

The industrial digitalization and automation has been a trending subject in modern industries worldwide. The implementation of Industry 4.0 technologies has shifted traditional businesses into smarter ones by the applications of Artificial Intelligence (AI), Machine Learning (ML), and Internet of Things (IoT) solutions. The outcome of these applications is a more sustainable approach towards processes and operations in terms of having comprehensive benefits from the data collected. This paper discusses the implementation of an IoT data management system on modern drilling rigs with the focus of having an added benefit from the real-time data coming from the sensors mounted on the rig equipment. An automatic rig state tracker algorithm was developed that is capable of detecting the rig’s operational status through a set of parameters in real time. This service which was added to the existing system helped in improving equipment efficiencies by monitoring their data and correlating them to the status of the rig, resulting in a better understanding of how the different components of the rig are working under different conditions. Two case studies were made using the rig state tracker, each resulting in a solution that helped the clients of Drillmec Spa. in optimizing their rig operations and usage. The results of the case studies showed huge potential of the system in terms of analyzing big data and correlating them with the existing issues that are being faced in the everyday drilling activities.

Relatori: Giovanni Andrea Blengini
Anno accademico: 2021/22
Tipo di pubblicazione: Elettronica
Numero di pagine: 45
Informazioni aggiuntive: Tesi secretata. Fulltext non presente
Soggetti:
Corso di laurea: Corso di laurea magistrale in Petroleum And Mining Engineering (Ingegneria Del Petrolio E Mineraria)
Classe di laurea: Nuovo ordinamento > Laurea magistrale > LM-35 - INGEGNERIA PER L'AMBIENTE E IL TERRITORIO
Aziende collaboratrici: Drillmec Spa
URI: http://webthesis.biblio.polito.it/id/eprint/23052
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