Dr. Satyam Priyadarshy, Chief Data Scientist, Halliburton
Internet of things (IoTs) provides almost unlimited opportunities in the consumer space and industrial arena as it enables connectivity of reality with the digital world. In other words, IoT refers to a new paradigm that combines many technological innovations to build a connected and communicating network of emerging devices and sensors to create a smart product or service. IoTs used in industrial settings are referred to as the Industrial Internet of Things (IIoTs). They provide an ecosystem that comprises networked smart devices, cyber-physical assets, enabling information technologies and computing platforms like cloud, fog and edge and advanced analytics to provide actionable insights for real-time resource optimization.
IIoT solutions provide excellent opportunities for the oil and gas industry by enabling connectivity from the field and operational systems to digital solutions. For example, traditional SCADA (Supervisory Control and Data Acquisition) systems are one of the components of the oil and gas industry and monitoring and analyzing the data from SCADA is time-consuming and inefficient. With IIoTs it is now possible to build real-time prescriptive insights from SCADA and other operational sensors and asset data. A typical oil and gas field has thousands of equipment sensors deployed at the site to perform drilling or production operations.
To deliver cost-efficiency with minimal to zero downtime, it is good to monitor the performance and operations of these devices, resources and equipment and take resulting action at the proper time.
The oil and gas industry is seeking to take advantage of this sensor data, as described in a McKinsey report that stated only one percent of sensor data was made available for decision making. However, in the last two years many companies increased their big data analytics efforts to harness their sensor and legacy data. Still, most of the initiatives are focused on pilot or proof of concept projects. The proof of concept projects have demonstrated that significant economic value can be realized from data, but the full transformation of the industry will come when value creation from data is accelerated in pace and scale.
The need for scalable, data-driven innovation is being discussed in operations like the Libra project, one of the world’s largest deepwater oil fields and operations across Norway. The success of these projects and cost effectiveness lies in utilizing well operational and maintenance data, supply chain data, health, safety and environmental data and other information.
Consider that data generated from sensors, devices and equipment in remote areas can be analyzed in real-time and quickly to help reduce the cost of operations across the oil-well lifecycle. The implementation of such a system is now possible with Voice of the Oilfield, a Halliburton approach that takes computing to the edge in the oilfields and includes data ingestion, processing and artificial intelligence applications to help provide real-time insights in the field or at office.
A good way to achieve benefits with this approach is to build integrated, scalable and agile edge platforms such as the Landmark Field Appliance. It can be deployed in harsh conditions with significant processing ability and connectivity in the field, as well as to the back office through fog or cloud infrastructure. There are many challenges in building scalable, agile and integrated platforms due to multiple taxonomies associated with devices, IoT, IIoT’s and domains (exploration, drilling and completion). However, many frameworks exist to address today’s challenges including the use of field appliances.
Now is the right time for the oil and gas industry to expand integrated solutions by taking advantage of the full IIoT ecosystem. The IIoT ecosystem, along with artificial intelligence applications, new communication technologies embedded in 5G networks, cloud computing paradigm and immersive reality will help transform the oil and gas industry. Projects can become significantly more cost effective and efficient by seeking to remove hidden inefficiencies in real-time or near real-time and taking advantage of the IIoT enabled transformation.