AI/machine learning
In the past year, publications on CO2, natural gas, and hydrogen storage have increasingly focused on the design, evaluation, and optimization of storage plans. These efforts encompass a broad spectrum of challenges and innovations, including the expansion of storage reservoirs from depleted gas fields and saline aquifers to stratified carbonate formations and heavy-o…
This paper introduces an agentic artificial-intelligence framework designed for offshore production surveillance and intervention.
Reaching further than dashboards and data lakes, the agentic oil field envisions artificial intelligence systems that reason, act, and optimize.
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For oil and gas companies to remain in existence in the second half of the 21st century, they must find ways to dramatically reduce, if not eliminate, their output of carbon dioxide and other greenhouse gases. Artificial intelligence technology could provide one tool to help the energy industry accomplish that staggeringly difficult goal. -
The new DeeperSense project, an international consortium led by the German Research Center for Artificial Intelligence, is working on technologies that combine the strengths of visual and acoustic sensors with the help of artificial intelligence. The aim is to significantly improve the perception of robotic underwater vehicles.
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Technology is advancing, and applications are growing, but scaling faces technological and human challenges.
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Algorithms are taking over the world, or so we are led to believe, given their growing pervasiveness in multiple fields of human endeavor such as consumer marketing, finance, design and manufacturing, health care, politics, and sports. The focus of this article is to examine where things stand in regard to the application of these techniques for managing subsurface en…
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Artificial intelligence is opening new ways to analyze data from microseismic events that occur during hydraulic fracturing. One researcher at Moscow’s Skolkovo Institute of Science and Technology is building a convolutional neural network to get a subsurface view of permeability after fracturing.
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Wintershall Dea set out to demystify digital for engineers with an informal network of staff experts who help fill the gaps in this new way of doing things and have a focus on maximizing the return on problems previously solved.
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In the spectrum of artificial intelligence (AI) technologies, those adopted to date in the oil and gas industry are task-focused, narrow applications. Taking AI to the next level cannot be done by Silicon Valley alone.
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In the complete paper, the authors generate a model by using an artificial-neural-network (ANN) technique to predict both capillary pressure and relative permeability from resistivity.
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ODDS—organization, due diligence, data, and scrub. These four important steps can make sure you are ready to implement artificial intelligence in a way that leads to a successful project.
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The Abu Dhabi National Oil Company announced that it has completed the first phase of its large-scale multiyear predictive maintenance project, which aims to maximize asset efficiency and integrity across its upstream and downstream operations.
