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Digital transformation
Digital transformation (abbreviation DT, or sometimes DX) is defined as "the transformation of business by revamping the business strategy or digital strategy, models, operations, products, marketing approach, objectives etc., by adopting digital technologies." [1]
Discussion
Transforming an enterprise, whether in Oil & Gas or any other sector, can be viewed as a more or less ambitious (or tactical vs. strategic) scale. One can distinguish three approaches, from the most conservative to the most disruptive:
- Using data captured from sensors to improve internal processes -- for example, to optimize the maintenance cycle of a pump.
- Finding new uses for data that is already captured, possibly by selling that data -- for example, by using geophysical or wireline information to set up a marketplace for subsurface data.
- Changing the business model of the enterprise, potentially abandoning a current business direction to open a new one -- as might be the case of a pump manufacturer who adopts a "servitization" strategy and rents the pump with a service contract on a pay-per-use basis instead of selling the pump outright to the operator.
Digital transformation is considered an umbrella term that covers a number of different approaches, listed below under "Topics" and described in separate pages.
Topics
- Internet of things (IoT)
- Blockchain
- Machine learning
- IT/OT convergence
- Cybersecurity
- Standards relevant to digital transformation
Resources
- Digital transformation study group (DTSG) of SPE-GCS
- Events related to digital transformation
- Calendar of DTSG lunch-and-learn events (working document)
References
- ↑ Wikipedia. 2018. Digital transformation (19 June 2018 revision). https://en.wikipedia.org/wiki/Digital_transformation (accessed 19 June 2018).
Noteworthy papers in OnePetro
Blockchain
Whitfield, S. (2018, May 1) Will Blockchain Become the New Operational Backbone in Energy? Society of Petroleum Engineers. doi:10.2118/0518-0030-JPT
Digital transformation
Berge J. (2018, April, 30) Digital Transformation and IIoT for Oil and Gas Production Offshore Technology Conference doi.org/10.4043/28643-MS
Brusset E. (2018 April, 18) Digital Transformation: Social Impact Assessment and Management Society of Petroleum Engineers doi.org/10.2118/190537-MS
Shaik, F., Abdullah, A., & Klein, S. (2017, January 1) Digital Transformation in Oil & Gas - Cyber Security and Approach To Safeguard Your Business World Petroleum Congress
Internet of things (IoT)
Crockett, B. J. (2016, September 6) How Can Decisions Be Made in Real-Time and Safely Manage Risk?Society of Petroleum Engineers. doi:10.2118/181052-MS
Elmer, W. G. (2017, October 9). Artificial Lift Applications for the Internet of Things. Society of Petroleum Engineers. doi:10.2118/187390-MS
Irons-Mclean, R., & Greengrass, J. (2016, September 6). The Internet of Things IoT and Security : A Practical Strategy to Secure an OT and IT Integrated Process Control Domain. Society of Petroleum Engineers. doi:10.2118/181002-MS
Temer, E., & Pehl, H.-J. (2017, November 13). Moving Toward Smart Monitoring and Predictive Maintenance of Downhole Tools Using the Industrial Internet of Things IIoT. Society of Petroleum Engineers. doi:10.2118/188382-MS
Zornio, P. (2018, April 30). The Control Room is Anywhere and Everywhere: Putting the Industrial Internet of Things to Work Offshore and Beyond. Offshore Technology Conference. doi:10.4043/28943-MS
Machine learning
Bowie, B. (2018, March 13). Machine Learning Applied to Optimize Duvernay Well Performance. Society of Petroleum Engineers. doi:10.2118/189823-MS
Pankaj, P., Geetan, S., MacDonald, R., Shukla, P., Sharma, A., Menasria, S., … Judd, T. (2018, April 30). Application of Data Science and Machine Learning for Well Completion Optimization. Offshore Technology Conference. doi:10.4043/28632-MS
Shadravan, A., Tarrahi, M., & Amani, M. (2015, November 17). Intelligent Cement Design: Utilizing Machine Learning Algorithms to Assure Effective Long-term Well Integrity. Carbon Management Technology Conference. doi:10.7122/440236-MS
Tian, C., & Horne, R. N. (2015, September 28). Machine Learning Applied to Multiwell Test Analysis and Flow Rate Reconstruction. Society of Petroleum Engineers. doi:10.2118/175059-MS
External links
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