Charles-Henri ClergetSebastien Mannai
Acoustic Wells
Production engineers rely upon a variety of data streams from the field to optimize production and maintain safe, environmentally responsible operations; without the reliable collection of this information, we cannot do our jobs. Given the challenges of operating assets spread over vast areas and the inadequacies of workflows relying upon manual measurements and communication, automated data gathering and telemetry have long been key focuses in the industry. Today, SCADA systems are the established standard to address those issues. They also interface with industrial controllers that allow operators to acquire data and take remote actions.
However, they suffer from severe drawbacks: mediocre data resolution and integrity, high implementation costs and complexity as well as siloed data streams leading most information to be lost or stranded on the field. This leads to major friction in the widespread roll-out of automation systems, which are typically only installed on high production assets, and often underutilized due to their excessive complexity. Low data resolution and overall quality also turn out to be major impediments to the feasibility of higher value-added data science use cases such as predictive maintenance. The primary cause of this situation is that these systems remain largely insulated from the trail blazing developments in more open-source technologies that have been fostered by the development of widespread internet services and consumer electronics.
In this presentation, we introduce state-of-the-art developments in terms of hardware and computing technologies that leverage those advances to allow low friction, turnkey, high-resolution data collection and field automation. These are combined with novel automated processing frameworks that provide high value insights without drowning users in impractical amounts of data. Ultimately, we show how these developments effectively leverage data points across the field to (1) reduce the cost of monitoring assets by an order of magnitude, (2) remove the need for routine in-person inspections of leases, and (3) increase production and equipment lifetime while reducing power consumption through optimization.