Traditionally, the oil and gas industry has been slow to adopt new technology, yet the tumbling oil prices that sent a tidal wave through the industry have dramatically changed the mindset of oil producers.
by Nav Dhunay
December 14, 2016

Big data and the Internet of Things (IoT) are being lauded in many industries as the new frontier for business and, with seemingly groundbreaking solutions being rolled out for innumerable uses daily, it is certainly not all hyperbole. Presently, an estimated 4.9 billion sensors are connected to the internet, and that number is expected to rocket to between 38 billion and 50 billion in the next five years.

Big data and IoT are positioned to change everything from the way we eat and exercise to how we manufacture the things we want and produce the energy we depend on. Smart technology in medicine is beginning to refine and improve treatments and global health, saving millions of lives and billions of dollars, and the agricultural industry’s adoption of connected devices is reforming the way food producers are planting, growing and harvesting the world’s food supply. So what is the next stop for big data? Oil and gas.

Traditionally, the oil and gas industry has been slow to adopt new technology, yet the tumbling oil prices that sent a tidal wave through the industry have dramatically changed the mindset of oil producers.

With margins eye-wateringly tight at current prices, there is a renewed appetite and determination to rethink the industry’s sustainability and find ways to achieve the efficiency levels needed to remain competitive and profitable.

To find the clearest path toward this type of future-proof oil production, many are turning to technology with aspirations of doing more with less—squeezing more barrels of oil from every well and cutting down on the sky-high operational costs that can hemorrhage profits.

Optimization Technology

Using technology to optimize oil well performance is not new to the industry. Established solutions for artificial lift wells—able to track a well’s performance and suggest efficiencies—have existed for several years. The systems available were aimed squarely at top-tier, high-performing wells since they were uneconomical to apply to older or less prolific wells because of significant costs relating to hardware installation and consistent manual monitoring. This is true despite the fact that these lower-performing wells constitute approximately 80 percent of the overall market.

Every well in operation could benefit significantly from technology-powered optimization. Operators have not held back from universal adoption because of the principle but rather the restricted nature of the applications available.

The Power of Connection & Communication

Accenture defines the Industrial Internet of Things (IIoT) as “a universe of intelligent industrial products, processes and services that communicate with each other and with people over a global network.” Connecting machinery is a phenomenon that is gaining significant traction across a wide range of industries. Applications that can harness the power and potential of connected machines within the oil patch are now at the forefront of the move toward more intelligent production.

Much like a new state-of-the-art smartphone, and delivered with a similar price tag (approximately $1,500), new out-of-the-box solutions that provide real-time well monitoring, remote control and autonomous optimization are ushering in a new era of self-driving production. No longer do decisions need to be made on which wells to install these optimization systems on. New technology can cost-effectively be fitted to every well.

Next Generation Technology for Monitoring

Next-generation monitoring solutions work on a continuous cycle of data capture, transmission, analysis and reporting. To enable this process, a lightweight sensor is self-installed directly on the pump jack, where it immediately begins to capture rich, raw data from each individual pump stroke.

Using a satellite-enabled wireless network—which prevents reliance on patchy network infrastructure or cellular networks in remote areas—this data is transmitted in real time to a cloud-based analysis engine. Next, it is processed through proprietary algorithms to extract meaningful insight. This is then reported to well operators, providing them with constant remote visibility of their pumping operations via a mobile or web app.

Well managers can set notification alerts to be triggered in the event of any anomaly in a well’s operations, such as unscheduled shutdowns or blockages. In these situations, corrective measures will be suggested within the alert, and resolutions can be planned and often implemented using the app, which enables remote well control. Having remote, 24/7 insight and control drastically reduces the need for scheduled site visits from service teams and allows problems to be corrected quickly, minimizing lost production resulting from machine downtime and expensive equipment workovers.

Big Data Powering the Self-Driving Pump Jack

The ability to harness intelligence gained through sophisticated analysis of raw machine data means that the reality of self-driving pump jacks is closer than many might think. New machine learning algorithms can learn from a pump jack, understanding its optimal performance and initiating micro-correctional adjustments directly to a pump stroke itself if a deviation from top-line performance is detected.

Moreover, by monitoring the wear on machinery, algorithms can preempt possible equipment failure or malfunctions, alerting operators of pending disruption so that they can minimize machine downtime and increase site safety.

In essence, machine learning and predictive algorithms are creating self-driving wells that can intelligently optimize, predict and report their operations. They are also able to bring in numerous additional data points, adapting to their environment, operating at peak intensity during times of lower energy costs and adjusting operations based on the known below-ground dynamics associated with specific drilling locations.

This data-led movement within oil and gas presents a very real opportunity for the industry to move beyond many of the inefficient legacy practices that were allowed to exist in a booming market but now have the potential to cripple a battered industry. For oil producers, intelligent technology now has the potential to become an integral tool in the move toward a more sustainable industry. Able to provide real-time, alerts, predictions and optimization, this technology has the power to shift a once-staid industry to one that is lean, progressive and future-proof.