A Huge Driver Of U.S. Oil And Gas
In the world of oil and natural gas, engineers, geologists, and drilling and production departments tend to get the lion’s share of the credit when good things happen, and most of the blame when they don’t. That’s fair, given the crucial roles these groups of employees play within the thousands of companies that make up the U.S. oil and gas industry.
But in recent years, as overall domestic production has risen at a pace no one could have foreseen even five years ago, the credit has begun to shift. These human resources remain indispensable to the success of any company, but the deployment of a raft of advancing technologies has played an ever-advancing role over time in enabling companies to maximize recoveries and profits.
Advanced-intelligence (AI), machine-learning applications constitute one area of technology that is obtaining widespread use throughout the industry. Unplanned equipment outages and the resulting loss of production cost companies billions of dollars every year. Any technology that can help avoid such outages can have a major, positive impact on a company’s bottom line.
Last December, I wrote about one machine-learning tool – PRT, a recent acquisition of DrillingInfo – that enables companies to significantly reduce their electricity costs by accurately predicting weather and wind patterns up to two weeks in advance. Given that electricity is the single largest element of lease operating expenses industry-wide, that’s a big deal.
Indeed, machine-learning tools that can provide intelligence about future pending events can be massive money-savers . AspenTech, another company in the machine-learning business, has a new technology called Aspen Mtell that uses machine-learning to not only monitor machine degradation, but also actually predict when pieces of equipment are about to break down. According to the company’s literature, Mtell can provide users with up to two to four weeks of advance warning of impending equipment failures. AspenTech also markets a flow assurance application that enables companies to anticipate and avoid interruptions in their ability to get their production to market.
Another company I spoke with recently is Veros Systems out of Austin, Texas. Veros is a venture capital-funded company whose major investing partners include Shell Ventures and Chevron Technology Ventures. Veros offers an AI application that is able to learn the electrical waveform signature of any piece of pump or compressor equipment and use that knowledge to accurately predict future breakdowns well in advance of their actually taking place.
The ability to know weeks in advance when a pump is likely to break down enables the users to plan outages and make the needed repairs or equipment replacements in the most efficient means possible, thus minimizing the loss of production.
Right now, Veros manufactures a small sensor that it attaches to the pump’s electrical supply, but Jim Dechman, the company’s CEO, envisions a near future in which which his company’s monitoring sensors are integrated into the electrical supply itself. “Let’s say you need to replace a circuit breaker switch at your home,” Dechman says, “You go to Home Depot, and in the circuit breaker bin there’s a switch that costs a dollar, but in the bin next to it, there’s a switch that costs $2.50 that will allow you to know weeks in advance when your air conditioner is going to break down. That’s where we are going eventually.”
So, how valuable can this sort of advance warning tech be? Royal Dutch Shell, which is using the technology in its Gulf of Mexico operations, estimates that “Veros could deliver an additional $300 million a year of production that would otherwise have been lost by unplanned shutdowns.” That valuable.
Another area of technology that is saving companies very significant money is remote monitoring. As an example, Apache Corporation is making extensive use of aerial drones to enable its executives and other key personnel to monitor construction activities at its Delaware Basin Alpine High operations from its San Antonio office more than 300 miles to the east.
In December I was able to tour Apache’s San Antonio complex, including what the company calls its Fusion Room facility, which actually consists of several different rooms. While there, we watched as technicians monitored gas flows, well pressures, storage tank levels and many other elements of the oil field that in years past required human interaction in the field. At one point, we watched on a screen as a vacuum truck pulled up to a secured well site gate, and the technician had a short phone conversation with the driver 300 miles away to verify his credentials before clicking an onscreen button to open the gate and let him through.