Capturing Today’s Knowledge and Pioneering Geoscience Tools to Empower Tomorrow’s Workforce
To invest in the future of geoscience, we must invest in forthcoming technology and the next generation of innovators.
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Harnessing the latest technologies and creative minds is crucial in our ever-evolving industry.
The challenge of securing sustainable energy to power our lives requires innovation and talent. Building geoscience-based energy solutions begins at the subsurface, and emerging AI technologies can assist and empower the future workforce. These technologies will continue to help geoscientists develop the tools we need for open exploration.
Emerging AI Solutions
Implementing new technologies and continuing to grow our collective knowledge base are vital to the success of tomorrow’s workforce. When we have easy access to data, as well as technologies that enable cross-industry collaboration, we broaden the potential workforce of the future.
The subsurface is an area that is ripe for emerging technologies and innovation. By beginning at the subsurface, we can unlock a wealth of data and dive deep into new learning techniques and data automation and augmentation. Innovating at the subsurface allows us to fine-tune our exploration workflows so that we have the tools we need to find energy solutions for our future.
Subsurface data analysis is a large unsolved problem in the energy sector. Currently, professionals spend the vast majority of their time loading and organizing data. AI can automate and unlock the searchable content based on domain centric search of all facets of information in these documents.
This means geoscientists no longer need to look for content manually — instead they will have a Google-style search for subsurface information at their fingertips.
Well Log Automation and Seismic Segmentation
There is immense data to be found in wells, but we only evaluate a handful of wells to understand the subsurface. With well log automation, geoscientists can pre-process, merge, and classify the world’s well databases. When coupled with three-dimensional seismic data, this will unlock new capabilities and depth of understanding.
Automated seismic segmentation allows us to see and interpret what is invisible to the eye. Using machine learning to infer depositional systems and tectonic features is driving exploration and key to subsurface feature extraction.
The Next Generation
The exploration space has a high barrier to entry and requires a serious level of domain expertise. That means that talented young people with innovative ideas outside of industry norms have a hard time getting their foot in the door. If we create tools that capture today’s knowledge, the next generation can be far more successful in making faster, more precise decisions in the future. By tapping into tech-focused and digital native talent, and by expanding their knowledge and data capabilities, the energy industry can pave a more intelligent and resilient path forward for exploration.
The Future of Work in Exploration
By encouraging outside-in perspectives and leveraging automation and cloud computing, processes can be streamlined significantly — and doing so should be a top priority. Many current manual processes are time consuming, leading to slower exploration cycles, limiting scope, and an overall reduction of workforce efficiency. Automating the world’s data into a global knowledge capture tool, such as knowledge graphs, can alleviate transient knowledge gaps in the workforce and accelerate the learning process when bringing new talent into the industry.
This network of knowledge, combined with AI, will continue to transform business paradigms and how geoscientists work across the world, moving subsurface evaluation and characterization into a global knowledge framework, with potential new insights from unexplored data connections.
At Studio X, we believe great ideas can be sourced from anyone and anywhere — what we call open innovation. Open innovation breaks down silos to promote collaboration and increased sharing of knowledge. By building an ecosystem around that approach, we can crowdsource talent and ideas to transform what the future of work looks like for exploration.
Want to learn more? Watch Kenton Prindle, Head of Data Science & Geoscience at Studio X, and his take on the future of work in exploration in his latest keynote presentation during EAGE’s Going Beyond Machine Learning virtual conference.