Machine learning has become a game-changer in the drilling industry, offering a myriad of opportunities to transform processes and improve efficiency, safety, and sustainability in drilling technology.
A new Special Issue of the journal Applied Sciences, titled Application of Machine Learning in Drilling Technology, aims to showcase the innovative ways in which machine learning techniques are being applied in the field of drilling. The issue seeks to highlight the potential of machine learning algorithms in enhancing drilling processes, from real-time data analytics and anomaly detection to automation and decision support systems.
Researchers, engineers, and experts in drilling technology are invited to contribute their research, case studies, and reviews on the application of machine learning in drilling. The scope includes areas such as drilling automation, digitalization, data processing and analytics, control system design, advanced drilling technologies, and more.
The Special Issue aims to facilitate collaboration, share best practices, and promote the adoption of machine learning within the drilling industry. Manuscripts can be submitted online on the journal’s website, with accepted papers published continuously as soon as they are accepted. Authors are encouraged to submit well-formatted papers with good English, following the journal’s guidelines for submission.
Overall, the Special Issue on the Application of Machine Learning in Drilling Technology offers an exciting opportunity to explore the intersection of machine learning and drilling, driving innovation and progress in the field. Researchers are encouraged to contribute their insights and expertise to advance the use of machine learning in drilling technology for a more efficient and sustainable future.
