Advanced Computing for
Energy, Oil and Gas
Until now, the abundance of research and simulation data has hindered the extraction of business value. However, the improvements in compute technology takes the data-related challenges that had, until recently, been considered impossible to overcome and transforms them into actionable insights, financial gain, and competitive advantage.
A major business priority in the oil and gas industry today is to improve the ROI of exploration. Many industry firms have found that they can dramatically reduce model processing cycle times and get sharper images of region-of-interest datasets via GPU-accelerated computing.
As a result, they now have more effective lease bidding, improved prospects for successful drilling, optimized well placement, increased drilling hit rates for striking oil, and much faster time to market.
Oil and gas companies can train models and use AI machine learning (ML) algorithms in many ways, including to determine the best way to save money, improve efficiency, and increase safety.
It can help them adjust operations as conditions change or extrapolate the value of the huge volumes of underground reservoirs by analyzing small rock core samples. These algorithms also increase prediction capability while also removing the risk of human error during complex calculations. In addition, machine learning techniques are also more repeatable and reliable than human interpretation.
