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The video game industry grew from about 10 billion in 2007 to more than 135 billion in 2018. Many industries including the oil and gas industry have been monitoring new and emerging technologies in this space as the capability evolves. The result of years of research, investigation into latest technologies, and proving the use cases for our industry have been a fit-for-purpose design. Key collaboration enabled the utilization of gamification for training, increased data visualization, improved operations, and the ability to create virtual twin of worksites. These improved capabilities increase safety and efficiency. This paper aims to share lessons learned and key points to consider when utilizing gamification and extended reality (XR) to deliver these solutions. This will be done by discussing several technologies investigated and their application to real cases. Specifically, products in use today as well as many proof-of-concept projects already in production will be highlighted. Gamification is not about creating video games. Gamification is about adding gaming elements to nongaming environments. Gamification can engage consumers, employees, and partners to inspire, collaborate, share, and interact. Gamification has the potential to address specific industry concerns. The industry can translate technologies previously thought only to be of value to the gaming industry into valuable energy industry applications. Like many other industries now utilizing gaming technology to adapt their own solutions, it is time for the energy sector to realize the potential applications of gamification. The potential upside to gamification is billions of dollars saved, and immeasurable increases in safety and operational efficiency. One example of this will center around training. This can be achieved with a game engine to create the learning environment and target a specific set of goals. All the tools to create a gamified system can be achieved with the right technology, but strong collaborations with technology leaders in other fields are necessary. Today, with the support of game engine partners, we can push the exercise to any platform be it mobile, desktop computer or virtual reality (VR). The gamification process can greatly enrich two-dimensional and three-dimensional experiences. We can easily use a tablet for three-dimensional learning experiences. A personal computer can be used for the most in-depth training process. Virtual reality can be an option to add muscle memory to the learning process as well. Collaboration is another example of an important function we will showcase. We will show the solution built as a multiuser experience that can bring experts from many domains together in one workspace on their platform of choice. In this example, we will show how these functions can be integrated with already existing software.
The video game industry grew from about 10 billion in 2007 to more than 135 billion in 2018. Many industries including the oil and gas industry have been monitoring new and emerging technologies in this space as the capability evolves. The result of years of research, investigation into latest technologies, and proving the use cases for our industry have been a fit-for-purpose design. Key collaboration enabled the utilization of gamification for training, increased data visualization, improved operations, and the ability to create virtual twin of worksites. These improved capabilities increase safety and efficiency. This paper aims to share lessons learned and key points to consider when utilizing gamification and extended reality (XR) to deliver these solutions. This will be done by discussing several technologies investigated and their application to real cases. Specifically, products in use today as well as many proof-of-concept projects already in production will be highlighted. Gamification is not about creating video games. Gamification is about adding gaming elements to nongaming environments. Gamification can engage consumers, employees, and partners to inspire, collaborate, share, and interact. Gamification has the potential to address specific industry concerns. The industry can translate technologies previously thought only to be of value to the gaming industry into valuable energy industry applications. Like many other industries now utilizing gaming technology to adapt their own solutions, it is time for the energy sector to realize the potential applications of gamification. The potential upside to gamification is billions of dollars saved, and immeasurable increases in safety and operational efficiency. One example of this will center around training. This can be achieved with a game engine to create the learning environment and target a specific set of goals. All the tools to create a gamified system can be achieved with the right technology, but strong collaborations with technology leaders in other fields are necessary. Today, with the support of game engine partners, we can push the exercise to any platform be it mobile, desktop computer or virtual reality (VR). The gamification process can greatly enrich two-dimensional and three-dimensional experiences. We can easily use a tablet for three-dimensional learning experiences. A personal computer can be used for the most in-depth training process. Virtual reality can be an option to add muscle memory to the learning process as well. Collaboration is another example of an important function we will showcase. We will show the solution built as a multiuser experience that can bring experts from many domains together in one workspace on their platform of choice. In this example, we will show how these functions can be integrated with already existing software.
Automatic prediction of drilling incidents can be conducted through either a purely data-driven approach or a hybrid approach. In the first approach, the variable space is typically limited to surface measurements and downhole sensor data, while in the second approach, the variable space is expanded to include information from physics-based models. This paper analyzes the additional value of incorporating physics-based information to predict drilling incidents such as stuck pipe, illustrated using data from the Utah FORGE geothermal wells. In our study, we trained three anomaly detection models with two distinct variables spaces. In the first one, we considered the real-time signals only, while in the second one, we included physics-based information derived from cuttings-transport, tortuosity, and torque-and-drag models. We selected three models that showed promising results in recent studies and represent the taxonomy of machine-learning-based anomaly detection algorithms. Specifically, we utilized recurrent neural networks, autoencoders, and clustering. Finally, a comparison between the two approaches was performed in terms of the fidelity of the warnings they generated. We observed that the inclusion of physics-based information is key to improving the performance of models for predicting drilling incidents. Specifically, we noted a reduction in the number of false alarms, which, in turn, increases the reliability of the models. In addition, we found that physics information can guide the selection of prediction time windows when drilling anomalies develop, thereby eliminating bias in the models' construction. Finally, we observed that some drilling anomalies, which were previously believed to occur suddenly with little warning, can, in fact, be predicted in a timely manner with hybrid models. These observations demonstrate that the use of hybrid models can significantly increase the performance of drilling anomaly predictions, providing sufficient forewarning time for their prevention and associated NPT avoidance. State-of-the-art methods that implement purely data-driven and hybrid approaches have individually demonstrated high accuracy in predicting incidents on specific datasets. However, no previous comparative study has been conducted to analyze the value of incorporating physics-based information. This paper is the first to perform such an analysis for models aiming at the early detection of drilling anomalies. The results from this study provide valuable guidance for future NPT avoidance in drilling operations.
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