How can E&P companies leverage cloud computing and edge computing to optimize operations and reduce costs?

Cloud computing allow engineers assess the tools, software, data from anywhere, anyway and anytime, minimize the local storage and allow for collaborative work.

Cloud computing to the Oil Industry used to be a fax machine. A device to send information over a network. Well it has come a long way. In non-industrial sectors cloud computing is sending, storing, & retrieving information. In the Industrial Sector such as Oil & Gas that is just about 1/3 of it. Another 1/3 are the devices (IIOT) that track, measure, & control operations. The other 1/3 is computational power such as modeling, warehousing, visualization, & now augmentation. Clouding computing in the Oil Industry is the future.

The biggest advantage of cloud computing in the E&P companies is no need to invest in software applications or infrastructure for the fluctuating demands. It helps E &P companies to implement the model of "Pay for use" instead of spending millions on maintaining the regular stuff for fluctuating demands.

E&P companies can optimize operations and cut costs by leveraging cloud computing (1) and edge computing (2). Cloud computing centralizes data storage and processing, enabling advanced data analysis and collaboration, improving exploration (4) and production (5) efficiency. Edge computing (2) processes data closer to the source, reducing latency and enhancing real-time decision-making in remote locations. This integration of cloud and edge solutions streamlines operations (6), reduces costs, and boosts productivity. #CloudComputing #EdgeComputing #EnergyTech #EandP #OilAndGas #CostOptimization

Edge computing is the concept of processing data as close to the source as possible. A cell phone is an example of an edge device. It runs models and processes and stores data locally while also pushing important information about that data up to the cloud. Think of a security system in a retail store. It would be very expensive to store all the video camera footage from all the stores in the world particularly if there weren't even people in the footage. So you can use edge to store all footage locally, while also using computer vision to automatically push only the video with humans in it up to the cloud for longer storage.

Achieving the Net-zero and Carbon neutrality targets is the primary concern of E&P companies. In this scenario implementing green operational technologies is advantageous. Continuous data recording, data transmission, and data processing emit a lot of carbon in the environment. To reduce the carbon footprints during E&P operations it is necessary to implement edge computing through which data is analyzed and interpreted at the recording site itself instead of transmitting and processing it at the remotely located servers.

Cloud computing centralizes resources in distant data centers, providing scalability for E&P data-intensive tasks. Whereas Edge computing distributes resources closer to the data source, minimizing latency for real-time applications like IoT/ IIoT. Cloud relies on internet connectivity, potentially causing delays, while Edge processes data locally, reducing bandwidth needs.

Most people don't realize this but edge computing has been used in the upstream exploration side for decades. The EDR on a drilling rig or the stage reports from a frac job. All that is done via edge computing. The new, exciting part of all this is the connectivity piece. Now that you can connect the edge and the cloud you can enable a number of possibilities. The ultimate goal of most of these applications will be to run automations or models on the local devices that send their learnings up to a "mother" cloud model. This will quickly accelerate training of ML models which should lead to more automation. Automated drilling and frac operations are coming in the not so distant future

Cloud computing aids in storing and processing large seismic datasets from exploration sites, ensuring scalability for analysis. Edge computing brings real-time processing to the field, reducing delays in seismic data interpretation. This combination enables efficient exploration, enhancing seismic data acquisition, processing, and interpretation. For drilling operations, cloud computing facilitates centralized management of drilling-related data, while edge computing supports on-site decision-making, improving overall exploration efficiency and outcomes.

The best applications on the production side are around a few things. Production/lift optimization. The other is maintenance. Edge already kind of exists in production when you think about a SCADA system. But now with better edge hardware, you'll be able to run much more than basic ladder logic. You can run full ML models on the edge that will optimize your lift while also monitoring and making suggestions related to equipment preventative maintenance. You'll soon be able to automate a number of operations that happen in remote command centers or in the field. But a strategy should be put together to understand how you compound applications (lift optimization, computer vision, maint, safety, etc)beyond the basics for better ROI.

Cloud computing centralizes data for streamlined management in oil & gas production. It handles extensive analytics and resource planning. Edge computing processes data on-site, aiding real-time monitoring and decision-making, enhancing efficiency. Together, they optimize production operations by combining centralized control with immediate insights at the production site.