No matter the commodity price, the equipment that produces, moves and processes crude and natural gas must be maintained.

“Ongoing maintenance is critical,” said Jake Loosararian, co-founder and chief executive officer of Gecko Robotics, in a phone interview.

The Pittsburgh-based robotics company he co-founded in 2013 utilizes artificial intelligence-enabled robots to gather data on infrastructure, from pipes to pressure vessels, tanks to boilers and silos to help determine what could fail or is failing and assist with maintenance.

“We’ve created this proactive way of maintaining critically important – and expensive – infrastructure,” said Loosararian, 28

“The robot I made in college was to address things that, if they failed, could have a negative impact,” he said.

Doing such inspections traditionally put people in danger, he said. “As I was building my robot, someone fell off a scaffolding and died,” he said.

When Gecko Robotics first started, he said it focused on the power space. But since then it has expanded “a fair amount” to work with government agencies such as the U.S. Navy, manufacturing and oil and gas companies. He listed BP, Chevron, Exxon, Marathon and Shell as among the customers using the machines to inspect the integrity of their infrastructure. The company recently raised $40 million in seed money, with Mark Cuban as a backer.

“We build these machines and platforms to identify integrity and help with assessments related to issues with infrastructure and predicting when things will fail,” he said.

“We’ve found the best way to understand structural integrity, whether it’s pipes or pipelines, digesters, oilers, tanks or silos, the way to identify integrity is through going out to those places and do spot checks with sensors,” he said.

For example, the company has developed a tubing integrity inspector with sensors that can perform inspections safely and a lot faster.

Beyond that, Loosararian said the company does not merely sell a customer a robot but uses its software to analyze the masses of data provided by the robots and artificial intelligence to identify when failures will happen, such as a refinery explosion or pipeline failure.

“We don’t know when things will happen or if the steps we’re taking are effective. We take the masses of data collected by the robots and utilize artificial intelligence and machine learning to predict failures,” he said.

While the company’s oil and gas work has been focused on the midstream and downstream sectors, primarily downstream, Loosararian said Gecko Robotics is getting involved in the onshore and offshore upstream sectors.

“We’re still looking at how we can be most effective,” he said. “We’re starting with the traditional infrastructure – pipes, tanks, and potentially piping for drilling.”

When the industry regains its footing from the double whammy of historic demand destruction because of the COVID-19 pandemic and oversupply as producing nations seek market share, Loosararian predicted a renewed push toward adoption of automation. He said the industry will see it as a way to reduce the footprint at well sites and a way to inspect infrastructure quickly, safely and obtain much more information.

The downturn is pushing the industry to adopt automation much faster, he said, noting that the company is already getting more inquiries from the industry.

“If we can predict when things will fail before they do, our customers will have the biggest competitive advantage. We will be reducing shutdowns, help the environment and safety and also extend the life of very expensive equipment,” he said.

The post Energy industry turning to robotics to inspect infrastructure appeared first on Artificial Intelligence.

Lowering energy consumption, looking for new sources of renewable energy and boosting energy efficiency are all integral Big Data goals to protect the environment as well as to sustain economic growth. Big volumes of data in motion are being increasingly monitored and analyzed in real time, which helps in achieving these goals. A lot of huge organizations and businesses use different measures to ascertain that they have energy resources they need today and in the future. Nontraditional energy sources, like solar farms, wind turbines and wave energy are getting to be more realistic options as prices and scarcity of fossil fuels remain to be an issue.

The same as numerous industries, Big Data science transforms the energy vertical, offering insights to cost reductions in down markets, as well as enabling oil producers to adjust to the demands in boom times. The recent oil prices decline have hit the economy of the world hard. With major fluctuations in the prices as well as the high cost of energy projects, quality information more than ever mattered more. Big Data could be used to boost energy efficiency as organizations are starting to use streaming data to increase energy efficiency. For instance, a big university monitors streaming data on its energy use and incorporates with weather data to perform real-time adjustments in energy utilization and production.

The field of energy uses data science for cutting costs, minimize risk and optimize investments. Minimizing costs with data science is a popular application in the energy industry. Optimization of investment decisions take several forms, such as assisting investors and a better internal resource. Moreover, data science contributes to the enhancement of public safety through providing better oversight and monitoring.

Big Data is valuable for numerous reasons. First and foremost, it provides the energy field with information and this is always valuable when used properly. It is being currently used to boost customer experience, for profit maximization and enhance efficiencies. Smart meters and real-time weather information systems are helpful in data gathering, decision-making and enhancing reliability. Moreover, it also allows investors to understand the impact of customer response weather, capital investment cycles, volatility of fuel price and other factors to influence investment decisions. The true value of Big Data is actually too big to fully comprehend, since more and more data becomes available, it would be those industries and businesses that are capable of harnessing information and making sense of it who would reap the benefits and stay ahead of the competition.

Members of a business community share and analyze streaming energy use data collectively. This allows organizations in the community to utilize energy more efficiently and minimize energy costs. Streaming data allows them to keep tabs of the supply and demand and make certain that changes in demand are anticipated and in balance with supply. Big Data is a great tool for the advancement of the production of alternative energy sources. The use of analytics and data science is expected to grow in the field of energy. In a low oil price scenario, management would seek cost reduction insights from data. In growth periods, data science would guide management decision making with better insights in improving production and to adjust to the market demand.

The post Big Data and Analytics Play an Important Role in the Energy Industry appeared first on Artificial Intelligence.