upstream oil & gas


A Decade of Accelerated Computing Augurs Well For GPUs

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While accelerators have been around for some time to boost the performance of simulation and modeling applications, accelerated computing didn't gain traction for most people until the commercialization of the Tesla line of GPUs for general computing by Nvidia. This year marked the tenth annual Nvidia GPU Technology Conference (GTC). I have been to all but one starting with the inaugural event in 2009. Back then it was a much smaller group. Attendance has leaped 10X with this year's meeting attracting over 9,000 participants.


10 Applications of Machine Learning in Oil & Gas

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The modern world is becoming increasingly technology driven. Many areas, such as healthcare, have been quick to realise the possibilities. AI and machine learning in oil & gas focused sectors has been slower to establish itself. This is largely because the industry has been slow to realise the potential. However this is slowly changing. Machine learning in oil & gas can be used to enhance the capabilities of this increasingly competitive sector. Not only can it help to streamline the workforce. The technology can also be used to optimise extraction and deliver accurate models. These benefits are just some of the reasons why machine learning in oil & gas is becoming increasingly important. Here are 10 ways that the impact of machine learning in oil & gas industries is being felt. One of the most noticeable impacts of machine learning in oil & gas focused industries is how it transforms discovery processes. Applications employing machine learning in oil & gas enable computers to quickly and accurately analyse huge amounts of data. This includes being able to sift precisely through signals and noise in seismic data.


Robotics Austin Forum July 2019

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Dr. Mitchell Pryor earned is BSME at Southern Methodist University in 1993. After graduating, he taught math and science courses at St. James School in St. James Maryland before returning to Texas. He completed is Masters (1999) and PhD (2002) at UT Austin with an emphasis on the modeling, simulation, and operation of redundant manipulators. Since earning his PhD, Dr. Pryor has taught graduate and undergraduate courses in the mechanical and electrical engineering departments as well as led and conducted research in the area of robotics and automation in Mechanical Engineering, Petroleum Engineering and the Nuclear Engineering Teaching Laboratory. He has worked for numerous research sponsors including, NASA, DARPA, DOE, INL, LANL, ORNL, Y-12, and many industrial partners.


Artificial Intelligence Can Prevent Enormous Amounts Of Damage And Water Loss From Building Leaks

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Broken water pipes can lead to millions of dollars in damages. When it comes to building construction, all sorts of things can go wrong. The most common problem is water damage, according to insurance claim records. "It's the silent killer," says Yaron Dycian, chief product and strategy officer for WINT Water Intelligence. Water is also an increasingly scarce, and valuable, resource – a reality that is not lost on many big companies who are embracing sustainable practices.


Baker Hughes Enters JV to Deploy Artificial Intelligence

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Baker Hughes, a GE Company (BHGE) has entered into a joint venture with Artificial Intelligence (AI) software provider C3.ai to accelerate the digital transformation in the oil and gas industry. C3.ai's AI suite and applications will be deployed into BHGE's business and leverage the oilfield services company's existing digital portfolio. "The oil and gas industry is rapidly evolving, and digital technology is critical to achieving increased levels of productivity, efficiency and safety for ourselves and for our customers," BHGE CEO Lorenzo Simonelli said in a company statement. "This agreement is a mutual recognition of the technology leadership we each bring to the table and a willingness to work in new ways … integrating our strong digital capabilities and oil and gas industry expertise with C3.ai's unique AI solutions, we will accelerate the overall digital transformation of this industry." Under the terms of the joint venture agreement, BHGE will take a minority equity position in C3.ai and will have a seat on C3.ai's board of directors.


AI in Oil & Gas Market to Exceed $2.85 Billion by 2022 - Press Release - Digital Journal

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AI in Oil & Gas market is projected to grow from an estimated USD 1.57 Billion in 2017 to USD 2.85 Billion by 2022, at a CAGR of 12.66% from 2017 to 2022. Northbrook, IL -- (SBWIRE) -- 06/20/2019 -- AI in Oil & Gas market is expected to grow from an estimated USD 1.57 Billion in 2017 to USD 2.85 Billion by 2022, at a CAGR of 12.66%, during the forecast period. The growth of AI in Oil & Gas market will be mainly driven by the rise in adoption of the big data technology in the Oil & Gas industry to augment E&P capabilities, a significant increase in venture capital investments, and growing need for automation in the Oil & Gas industry, and tremendous pressure to reduce production costs. Software in AI in Oil & Gas market is applicable in upstream Oil & Gas exploration and production activities. The hardware segment in AI in Oil & Gas market is expected to grow swiftly during the forecast period (2017 to 2022), mainly due to the increasing requirement for sophisticated hardware system configurations and components capable of handling massive data, including, but not limited to Tensor Processor Unit (TPU), Graphic Processing Unit (GPU), Resistive Processing Unit (RPU), Field Programmable Gate Array (FPGA), and Visual Processing Unit (VPU) to install software-based AI capabilities.


AI in Oil & Gas Market to Exceed $2.85 Billion by 2022 - Press Release - Digital Journal

#artificialintelligence

AI in Oil & Gas market is projected to grow from an estimated USD 1.57 Billion in 2017 to USD 2.85 Billion by 2022, at a CAGR of 12.66% from 2017 to 2022. Northbrook, IL -- (SBWIRE) -- 06/20/2019 -- AI in Oil & Gas market is expected to grow from an estimated USD 1.57 Billion in 2017 to USD 2.85 Billion by 2022, at a CAGR of 12.66%, during the forecast period. The growth of AI in Oil & Gas market will be mainly driven by the rise in adoption of the big data technology in the Oil & Gas industry to augment E&P capabilities, a significant increase in venture capital investments, and growing need for automation in the Oil & Gas industry, and tremendous pressure to reduce production costs. Software in AI in Oil & Gas market is applicable in upstream Oil & Gas exploration and production activities. The hardware segment in AI in Oil & Gas market is expected to grow swiftly during the forecast period (2017 to 2022), mainly due to the increasing requirement for sophisticated hardware system configurations and components capable of handling massive data, including, but not limited to Tensor Processor Unit (TPU), Graphic Processing Unit (GPU), Resistive Processing Unit (RPU), Field Programmable Gate Array (FPGA), and Visual Processing Unit (VPU) to install software-based AI capabilities.


When Every Millisecond Matters in IoT

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One of the big promises of the Internet of Things (IoT) is understanding the physical world around us and taking action based on insights and observations. Over the last decade, we've gotten really good at the first part, using smart devices and sensors for monitoring and data collection. We have sensors everywhere, in consumer products, on the floor and embedded in manufacturing and industry, distributed across nature and remote areas of the world--always on and always streaming new readings as they happen. This has transformed our understanding of how we work and live because we have more up-to-the-second data and analysis than ever before. The next area ripe for innovation is what we do with that data.


How Can Artificial Intelligence Revamp Gas and Oil Industry?

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FREMONT, CA – Industries and organizations across the globe have realized the potential of artificial intelligence (AI), and the oil and gas industry is one of them. Petroleum oil is one of the most prominent resources in the energy sector and is the basis for many products such as wax, lubricant, kerosene, petroleum jelly, and so on. Over the last few years, the crude oil reserves are steadily reaching their limits. Also, the rise of alternative fuel sources has resulted in the reduction of oil prices, which has raised concerns in the oil and gas sector. To alleviate the adverse effects plaguing the industry, many organizations are turning toward modern technologies to increase productivity as well as revenue.


Neural network can explain the physics of an earthquake rupture

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Damage due to earthquakes poses a threat to humans worldwide. To estimate the hazard, scientists use historical earthquake data and ground motion recorded by seismometers at different locations. However, the current approaches are mostly empirical and may not capture the full range of ground shaking in future large earthquakes due to a lack of historical geological data. This leads to significant uncertainties in hazard estimates. Not only that, due to the lack of sufficient historical data, scientists mostly rely on simulated data, which is computationally expensive.