IN THE INDUSTRY
Capital Projects Struggle To Implement Digitalization
The Independent Project Analysis recently reached out to its clients to understand why digitalization tools are so burdensome for projects organizations to implement.
Moving to the Edge Is Crucial for Oil and Gas Companies To Make Better Use of Data
The oil and gas industry already lives on the edge when it comes to the remote and often inhospitable geographic locations that it operates in, but now it is moving its computing to the edge to gain valuable business insights that can increase operational efficiency and profitability.
Schlumberger Introduces Digital Exploration Platform
Schlumberger introduced the GAIA digital exploration platform, which it says enables exploration teams to rapidly discover and access basin-scale data and manage their exploration opportunities.
Hamiltonian Neural Networks Show Benefits Over Regular Neural Networks
Hamiltonian neural networks draw inspiration from Hamiltonian mechanics, a branch of physics concerned with conservation laws and invariances. By construction, these models learn conservation laws from data, revealing major advantages over regular neural networks on a variety of physics problems.
Random Forests Vs. Neural Networks: Which Is Better and When?
Random Forest and Neural Network are the two widely used machine-learning algorithms. What is the difference between the two approaches? When should one use Neural Network or Random Forest?
Katy, Texas, Is Now Home to One of the World’s Fastest Supercomputers
The 21st century oil and gas industry thrives on hardcore computing power, crunching data derived from seismic testing to find oil deep in the ground and below the sea. Now, an Australian company will fire up a digital behemoth in a data center near the Houston suburb.
Digital Transformation Increases Value in an Omani Thermal EOR Asset
A thermal asset in Oman is characterized by a large-scale steam-drive/cyclic-steam-soak (CSS) development project, underpinned by extensive data gathering.
Surface Drilling Data Can Help Optimize Fracture Treatment in Real Time
This paper presents a unique work flow that addresses in real time the challenges of perforation and fracture-treatment design while accounting for the lithologic and stress variability along the wellbore and its surroundings.
Computational Model Predicts Breakdown Pressures in Unconventional Plays
This paper presents a newly developed model to predict the breakdown pressures in cased and perforated wells.
Training a Single AI Model Can Emit as Much Carbon as Five Cars in Their Lifetimes
Researchers at the University of Massachusetts, Amherst, performed a life-cycle assessment for training several common large AI models. They found that the process can emit more than 626,000 lbm of carbon dioxide equivalent—nearly five times the lifetime emissions of the average American car.
Strengthening the Energy Sector’s Cyber Preparedness
The reality is that threats continue to outrun the sector’s security evolution, primarily because organizations are increasingly connecting operational technology, such as supervisory control and data acquisition systems and industrial control systems, to their information technology networks.
AI-Generating Algorithms: An Alternate Paradigm for Producing General Artificial Intelligence
This paper describes a path to general artificial intelligence (AI) (i.e., AI that is as smart or smarter than humans) based on the trend in machine learning that hand-designed solutions eventually are replaced by more-effective, learned solutions.
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04 June 2019