This course will give an overview of all the topics we shall be looking at in this course. We shall begin by describing the oil value chain – the exploration and development, how oil is produced, shipped, and marketed. Moving further, we will learn about the importance of oil in the industry, both as a fuel and as a raw material in various forms in the global economy. Then, we will go through a brief history of oil – how it all began, and the different'kinds' of oil discoverers. We will be introduced to the major players in the oil market – the top producers and the major consumers. We will then see how oil is formed, how it sits deep within the earth and how we discover and refine it. We will learn about the different types of oils, and the methods employed to extract them. This will be followed by a brief overview of the different means of transporting oil, and the risks and benefits associated with the different methods of oil transport. Lastly, we shall look into the different oil benchmarks that prevail globally.

Daniel Faggella: So, Lorena, I want to be able to dive into these various use cases of how artificial intelligence can start to unlock the value of data in the oil and gas space, and make this really tangible. I know the first category we wanted to talk about was really around the value of subsurface data, that there's a lot of subsurface data, obviously in the oil and oil and gas domain. Lorena Pelegrín: And we see that AI or our ML can help these teams find the data and process the data much, much faster. Yeah, and I imagine a good deal of this has to do with, tell me if I'm wrong here, Lorena, but having an understanding of your company from working with you guys for a little while, I would imagine that the digitization of these myriad, somewhat chunky paper forms is one part of the process here, using some kind of optical character recognition stuff and working with historical records and maybe congealing and digitizing that. Daniel Faggella: But you let me know, Lorena, where does M&A, where does this data come in, in terms of the real value for potential M&A? Daniel Faggella: So Drone Deploy, for example, was on talking about what they do in the energy space with drones and video data to look at and inspect assets.

So maybe you can make it more tangible. But that's the understanding I have. Where do you really see digital twins driving value in terms of day-to-day decisions for executives who really need to steer the company?

The role of artificial intelligence (AI) is evolving, especially in industrial organizations such as oil and gas, where data acts as a critical enabler to provide a competitive advantage. Industrial organizations operating in the fields of mining, oil, and gas; and marine, are going through a radical transformation and seeking innovative ways to optimize performance with minimized risk. The volatile and ever-competitive nature of the industrial companies demands them to identify new and innovative sustainable models to stay profitable, grow and unlock efficiencies. The situation has become more challenging in the wake of the coronavirus pandemic. According to a Capgemini research, over 50% of the European manufacturers, 30% in Japan, 28% in the USA, and 25% in South Korea implement AI solutions.

This article is a summary of a three-hour discussion at Stanford University in September 2019 among the authors. It has been written with combined experiences at and with organizations such as Zilog, Altera, Xilinx, Achronix, Intel, IBM, Stanford, MIT, Berkeley, University of Wisconsin, the Technion, Fairchild, Bell Labs, Bigstream, Google, DIGITAL (DEC), SUN, Nokia, SRI, Hitachi, Silicom, Maxeler Technologies, VMware, Xerox PARC, Cisco, and many others. These organizations are not responsible for the content, but may have inspired the authors in some ways, to arrive at the colorful ride through FPGA space described here. Field-programmable gate arrays (FPGAs) have been hitting a nerve in the ASIC community since their inception. In the mid-1980s, Ross Freeman and his colleagues bought the technology from Zilog and started Xilinx, targeting the ASIC emulation and education markets.

The oil and gas industry is massive and highly-diversified in its operational characteristics between the upstream, mid-stream and downstream sectors of the industry. Even within each sector, there are distinct differences; offshore gas/oil rigs have a completely different set of requirements to onshore well pads in the fracking industry. However, every sector is susceptible to the boom and bust cycles that have traditionally characterised the oil and gas industry. All of this makes oil and gas ideal for adopting IOT technologies to address a whole range of problems and risks, and to smooth out the ups and downs of the business cycle. Where are oil and gas companies today with edge computing adoption?

The potential of Artificial Intelligence is already being discovered by many industries, including the Oil and Gas, which is investing majorly in Artificial Intelligence and other data technologies with a goal to secure their future competitiveness in a fast-changing environment. Oil is one of the most precious commodities in the energy sector. With the rise in the oil prices and depleting crude oil levels globally, organizations involved in the oil and gas industry are now turning towards modern technologies, specifically Artificial Intelligence, to maximize and optimize their efficiency and revenues. Companies involved in the oil and gas industry leverage AI to drill and mine raw hydrocarbons and other products required to produce fuel. AI helps these companies by developing algorithms that provide accurate and precise intelligence to guide drills on water and land.

Businesses in the oil and gas arena have been able to use a wide variety of technological products and solutions. Along with oil and gas software, the field has started using drones, electronic monitoring, internet of things (IoT), data analysis tools, and artificial intelligence. All of these origins of technology have become a discovery in the oil and gas industry in recent years. With the combination of this technology, many oil and gas companies have been able to reach their composition goals and improve their overall facilities management services. Technology, alongside oil and gas software solutions, has been able to help companies increase their safety measures.

The oil and gas industry's technological innovation over the last 150 years is truly astonishing, which is why its lackadaisical adoption of artificial intelligence is so surprising. Geologists have figured out how to vibrate the earth and use seismic imaging to describe rocks thousands of feet below the surface. Mechanical engineers have designed tools that can steer a drill bit through a narrow band of oil for more than a mile. Likewise, petroleum engineers have collected billions of data points from hundreds of devices to design the most productive wells. But when it comes to using that data to train an artificial intelligence to generate insights, the industry is still dabbling.

It's no secret - oil and gas industry leaders acknowledge they have been slow to embrace digital technologies. A recent Boston Consulting Group report sums it up well: "The oil and gas industry is not an easy place to go digital." Digitisation brings with it the promise of improved safety and efficiency, yet many companies still have a long way to go. It may be surprising to learn that some businesses even lack the technology to locate their workers ‒ which has clear and potentially dire implications for emergency situations. This is partly because most of the industry is still deeply rooted in 20th-century methodologies, systems and processes.