Working towards a methodology for wellsite maintenance that was exception-based was a challenging reorientation of existing practices and WellTender was intended to usher forth a contemporary approach. After several initial iterations created by the internal team, developers at Chesapeake Energy recognized that any significant evolution of the software would require partnership with a world-class strategy, design, and development team. The internal team was aware of the potential of artificial intelligence but actual development was outside their skillset. Hypergiant provided its signature blend of expert design, holistic strategic directionality, and top-notch development resources throughout the lifecycle of the redesigned, reimagined product.
In an effort to usher workers towards greater efficiency, Hypergiant introduced Intelligent Incentives. This evolved version of gamification provides employees and management transparent records of site efforts, skills identification, and drives behavioral change in work item management. The program included dozens of different achievement badges acquired through efforts that mitigate problems or save Chesapeake money. Underlying game mechanics were defined and leaderboards were leveraged to encourage friendly competition between employees.
Chesapeake Energy developed the original iteration of WellTender from a user-centric perspective, so partnership with Hypergiant was natural and the relationship extremely productive. Collaboration across more than a year was intense and fruitful allowing for creation of a truly future-forward manifestation of the original promise of WellTender. Across vastly expanded capabilities, WellTender 2.0 incorporates multiple forms of artificial intelligence. Unsupervised learning is employed in analyzing maintenance and historical production. Computer vision is utilized for well information gathering and transmission, eliminating the need for every site employee to spend hours each week traveling to a central office location, scanning, and submitting documents to a central repository. Natural Language Processing (NLP) and sentiment analysis are leveraged to review user comments for efficacy which is coupled with user-driven supervised learning. Algorithmic work item matching ensures that the most appropriate employee addresses site challenges according to their own aptitudes, location, and past performance. Most significantly, AI-driven routing and telemetry ensures that site issues are addressed via the most efficient travel pathway. Finally, the Intelligent Incentives program tied together all of the disparate capabilities into a format that was intuitive, graceful, transparent and user-focused.
“Technological change is never an isolated phenomenon. This revolution takes place inside a complex ecosystem which comprises business, governmental and societal dimensions. To make a country fit for the new type of innovation-driven competition, the whole ecosystem has to be considered.”