Colonial Pipeline has partnered with Accenture to optimize utility rates using artificial intelligence (AI). Accenture is using a proprietary database powered by AI to help Colonial Pipeline, the largest refined products pipeline in the United States, reduce regulated and deregulated electric utility rates for its interstate pipeline system. The energy-management project leverages Accenture's Utility Tracking System (UTS), a proprietary database of approximately 30 million anonymized utility bills that the company has been aggregating for more than 20 years, according to a July 14 statement. Built to identify power tariff options around the world, UTS uses AI-powered insights and automation as part of Accenture's SynOps platform to continuously improve the efficiency and reliability of electricity rate-savings recommendations. Accenture is using insights generated by UTS to evaluate power bills for operations at approximately 80 Colonial Pipeline pump stations along its 5,500-mile pipeline system, which delivers approximately 100 million gallons of refined petroleum products daily to markets in the Southern and Eastern United States.

Scuba diving archaeologists are scouring the seabed where a gas pipeline is being built off Israel's coast in a bid to preserve ancient relics. The area lies near a 5,000-year-old port which once was a key trade hub for the Mediterranean's ancient civilisations. Scientists say the vestiges of marine traders throughout the ages - from the Phoenicians to the Romans - lie hidden beneath the seabed at the port of Dor. They have already found earthenware jugs, anchors and the remains of wrecked ships, setting new guidelines for similar future projects. Underwater robots are scouring the seabed where a gas pipeline is being built off Israel's coast in a bid to preserve ancient relics.

They have the sort of names that only teenage boys or aspiring Bond villains would dream up (REvil, Grief, Wizard Spider, Ragnar), they base themselves in countries that do not cooperate with international law enforcement and they don't care whether they attack a hospital or a multinational corporation. Ransomware gangs are suddenly everywhere, seemingly unstoppable – and very successful. In June, meat producer JBS, which supplies over a fifth of all the beef in the US, paid a £7.8m ransom to regain access to its computer systems. The same month, the US's largest national fuel pipeline, Colonial Pipeline, paid £3.1m to ransomware hackers after they locked the company's systems, causing days of fuel shortages and paralysing the east coast. "It was the hardest decision I've made in my 39 years in the energy industry," said a deflated-looking Colonial CEO Joseph Blount in an evidence session before Congress. In July, hackers attacked software firm Kaseya, demanding £50m.

A variety of computationally challenging constrained optimization problems in several engineering disciplines are solved repeatedly under different scenarios. In many cases, they would benefit from fast and accurate approximations, either to support real-time operations or large-scale simulation studies. This paper aims at exploring how to leverage the substantial data being accumulated by repeatedly solving instances of these applications over time. It introduces a deep learning model that exploits Lagrangian duality to encourage the satisfaction of hard constraints. The proposed method is evaluated on a collection of realistic energy networks, by enforcing non-discriminatory decisions on a variety of datasets, and on a transprecision computing application. The results illustrate the effectiveness of the proposed method that dramatically decreases constraint violations by the predictors and, in some applications, increases the prediction accuracy.

Drones are all the rage today. Not a day goes by that we don't read about someone using a drone for something (good or bad) somewhere on Earth. AI or Artificial Intelligence has also made a resurgence. I say that because there was a time, not too long ago (about 7 years ago) when AI was also very popular and a number of movies featuring AI were produced by Hollywood. Now if we combine the two, what do we get?

Prism Courage, a 134,000-tonne commercial tanker, recently sailed from the Gulf of Mexico to South Korea while controlled mostly by an artificial intelligence system called HiNAS 2.0. Avikus, a subsidiary of South Korean technology giant Hyundai, recently announced that Prism Courage, a tanker designed to transport natural gas, had become the first large ship to make an ocean passage of over 10,000 km (6,210 miles) autonomously. The key to this incredible achievement was HiNAS 2.0, an AI-powered system capable of analyzing different kinds of sensor readings in real-time and responding to them swiftly, efficiently, and, most importantly, in accordance with the rules of maritime laws. Just like airplanes, ships have very advanced auto-pilots capable of keeping them on a steady course, responding to GPS waypoints and currents, and even bringing them into harbor in case the human crew is no longer present on board or capable of doing it. However, sailing autonomously for tens of thousands of kilometers through the Atlantic is a lot more complex than putting a ship on autopilot. Apart from steering the tanker in real0-time, Avikus' HiNAS 2.0 system is capable of picking the optimal routes and best speeds to reach its destination, by analyzing data collected through advanced sensors.

The US company, Orbital Insight, is using AI to analyze satellite images and identify and quantify crude oil storage tanks. The tanks have floating roofs, so the volume of oil is visible. Orbital Insight is using shadow-detection technology and calculates how full a storage tank is by the size of the crescent-shaped shadow on the tank roof.

My colleagues and I had the privilege of attending Tata Consultancy Services' (TCS) Analyst Day event held in Boston on September 21, 2017. There were several interesting and informative presentations covering topics such as the concept of Business 4.0 and how TCS is deploying Digital, deep domain expertise and its deep and vast portfolio of services and solutions to provide its customers with exponential value through mass customization, leveraging ecosystems to help its customers embrace and manage risk while maximizing business outcomes. As one of the ARC Analysts focused on upstream and midstream oil & gas it was great to learn more about how TCS is leveraging'cognitive automation' through its solutions such as Ignio, an product that provides some very powerful horsepower through its self-learning capability, empowered by machine learning and artificial intelligence (AI), that can move customers from predictive maintenance to prescriptive maintenance, thereby extending the life (and availability) of an asset such as a pump or compressor and also optimizing that asset's performance and the process for which it is being utilized. I know first-hand that TCS is successfully helping customers in Australia with pump optimization and increasing pump availability as well as, more importantly, helping to increase the customer's gas processing operations by saving over 100-man days per year, reducing pump downtime and increasing production. Harrick Vin, Global Head of Digitate, explained that he envisions advanced analytics platforms such as Ignio as being technology being augmented by people and one that is capable of learning over time.

Edmonton, Alberta, Feb. 07, 2018 (GLOBE NEWSWIRE) -- OneSoft Solutions Inc. (the --Company-- or --OneSoft--) (TSX-V:OSS, OTC:OSSIF)--is pleased to announce that its wholly owned subsidiary, OneBridge Solutions, Inc. (--OneBridge--), has entered into a Pilot Program agreement with another U.S.-based, Fortune 500 natural gas, oil and petrochemical company (the --Client--). The Client, whose operations include natural gas gathering, treating, processing, transportation and storage, primarily in the United States, will evaluate OneBridge--s Cognitive Integrity ManagementTM (--CIM--) SaaS solution.

In this blog post we will look at some of the achievements during a 5-day machine learning hackathon we arranged recently. We were curious about one of the key concepts in our current strategy – could we manage to become a bit more "data smart" on integrity management and maintenance planning on pipelines? We wanted to learn more about the opportunities and maturity level with technologies like big data, machine learning, artificial intelligence and the internet of things. How easy was it to apply and how could it potentially fit into our current product portfolio? In our hackathon, we set up a mixed team of business representatives, experienced developers, data scientists and domain (pipeline) experts.