The following are some specific oil and gas use cases (upstream, midstream, downstream or in oil field services) that illustrate how oil and gas companies can deploy IIoT technology more quickly, securely, cost-effectively and with higher output.
Compressor Condition-Based Maintenance
The oil industry can improve availability and lower maintenance costs by moving from a reactionary maintenance program to a proactive program. Historically, each asset had to be visited in person to obtain maintenance information. In many cases, operators are only able to get to an asset once every six months. Not only is this expensive, but the live visits run the risk of missing critical conditions. Moving to a proactive maintenance program requires the ability to monitor in near real-time the condition of the compressors such that compressor experts can remotely analyze the data and make recommendations. This is true for anywhere compressors are used in the upstream, midstream and downstream areas.
Many times, the owner/operator would like to use a third-party monitoring service to help maintain their assets. However, granting the third party access to the data on each asset without compromising the security of the process network was very difficult if not impossible in the past. The industry required a pull and play solution that allows owners/ operators the ability to quickly and safely grant access to third parties without compromising existing infrastructure. Paramount to this is the ability to manage those connections remotely. You don’t want to have to be required to make costly and time-consuming visits to the field in order to implement or manage the connections.
Owners/operators wish to increase their production and their EUR by optimizing their artificial lift program (ESP, rod lift, gas lift, etc.). But real-time optimization has not historically been cost-effective in many situations due to expensive devices and even more real-time SCADA networks. By moving an artificial lift to IIoT where one can use commodity hardware and commercial networks, you can optimize artificial lift with a very cost-effective solution. Critical to this is the ability to run the optimization software locally—without the need to construct a very expensive real-time network. Also imperative to the solution is the ability to download a customized machine learning model for that particular well in order to maximize its unique and particular situation.
Improve Process Efficiency & Reduce Cost
IIoT networks enable assets (sources of data) to share information with decision applications (sinks of data). For example, a third-party operational consultant can securely access wellhead asset data across all sites so as to recommend structural changes to current operations. The same IoT infrastructure can also enable the operational teams to continuously monitor multiple elements and make tactical improvements. This enables data from multiple firewalled process controlled networks to be securely transmitted to third-party applications for analyses and syntheses.