The IoT largely solves the data accessibility problem by increasing the volume and usefulness of data, then making it available at an excitingly low price point.

Applying this IoT contribution to a range of energy industry problems will be a major factor in helping the industry return to profitability in the new, lower commodity price environment.

Here are some examples of how the IoT solves problems in the upstream energy industry.

1. Data collection frequency

Pre-IoT, the upstream energy industry was hampered by the sparse collection of data points (about one per day). With an IoT solution, the well flow rate, pressure and temperature data collection frequency can be every minute or even every second.

2. End-point sensor cost

Pre-IoT, the high end-point sensor cost (over $1,000 each) prevented their widespread installation. With new low-cost IoT end-point sensors, this technology can be implemented at all wells to optimize production.

3. Ubiquitous data networks

Pre-IoT, proprietary or non-existent data networks precluded gathering sensor data. With Internet ubiquity, IoT devices at remote field locations can remotely monitor wells and pipelines.

4. Cloud computing

Pre-IoT, the high cost of computing hardware together with the high operating cost of the computing environment hampered its widespread application. Use of lower-cost cloud computing consisting of IoT hardware and software enables the use of data analytics for production optimization.

5. Software for data management and data visualization

Pre-IoT, primitive and simplistic software for data storage, data management and data visualization precluded achieving much value from data. Advanced software now enables IoT data management and next generation data analytics for energy trading and risk management.