As the oil and gas industry adopts new technologies, everyone gets more excited about the connected oil well.  Despite all this interest, it’s difficult to understand exactly what exactly is being connected and the overall value this connectivity can drive.

A smart oil pump is not just a sensor attached to a pump jack, but instead is an ecosystem of sensors being processed which creates data that informs a much larger context of capability.

Below we capture just four of the base systems each location will need to begin achieving the full value that IoT can offer.

1. Equipment Monitoring: is everything working as expected?  Does anything need maintenance? Is the maintenance something that will enhance the operational life of the equipment?  What can we learn from other locations about maintenance when we collect and correlate the data?

2. Consumables Tracking: do we have enough fuel, emulsifiers, and proppants? If not, how can we automatically order refills? Does anything else nearby also need refilling?  We just received an invoice from our consumable vendor, is it correct? Did I get as much as I expected, was it delivered on the day it said it was?

3. Dependencies: do we have the power necessary to keep things running, or is a certain machine or system running on battery power? What is the health of the power supply? Will forecasted weather events, fires or other environmental events cause disruptions? Are the tanks or pipelines working as designed, or do we risk an outage?  Are communications networks resilient? What are the conditions of physical roads?

4. Production: as the well works we gather back pressure on production rates. Alternative: What are the outputs for the well, based on history and forecasts? As oil is produced and release, based on planned flow rates, are we getting what is expected for this location? Is the viscosity and other quality metrics in line with standards?

While much of the data that is captured at a well comes from basic analog sensors streaming a number, or digital sensors sending back “true or false” machine health data, understanding how the how that data comes together can provide tremendous value.

How Industrial IoT implementations are set up depends on business goals.

If the goal is improving yields, the output should be measured continuously, and information should be generated showing planned vs. actual output.

If the goal is to reduce maintenance costs and the risk of downtime, the information should drive predictive measures.

In most cases, data generated by sensors can contribute to gains across the board, whether increasing revenue (through optimized production) while decreasing costs (through predictive maintenance) while also making job sites safer, which reduces overall operational and reputational risk.

Thinking comprehensively about how much data can be generated from a system of sensors (not just a single sensor) will allow oil wells and any industrial equipment, especially equipment in remote, distributed locations, to be run with optimal productivity and predictability.