Oil & Gas companies, while facing the formidable challenges of the dropping of global oil prices, especially post Covid 19. With the new drive for climate change and alternate sources of fuel gaining momentum, there is little probability of regaining past peaks in the forcible. With this, the focus has now shifted to efficiency, sustainability & profitability. One of the clearest and most viable responses to these challenges is to accelerate digitization.

With Machine learning, artificial intelligence & IOT remain the bulk of the digitization initiatives being taken up by the O&G industry. Among these technologies, IoT applications have the potential of creating value through an integrated deployment strategy. IoT will allow the industry to digitize, optimize, and automate previously unconnected processes to save time, money and increase safety. According to McKinsey, IoT has a total potential economic impact of $3.9T to $11.1T by 2025.

Among the many applications here, IoT can impact the O&G industry, and one promising application is Industrial Oil Testing. Testing standards on characteristics and performance of materials, products, systems, and services; and the promotion of related knowledge.

While some of the O&G companies today use one or more of the below-testing methods –

• Secured SCADA or PLC or in-line instrument systems for “Testing: that offer real-time visibility.
• In-house or third party Lab services that can conduct “Testing.”

But the real question to ask is, are these systems able to respond to –

• What is being done with all the current data they get?
• What is the quality of the data that they get?
• Is there a track of the data collected?
• Can the data be interpreted by someone with the level of expertise available at different levels?
• Is the data trustworthy and comparable to a definitive reference value or the value before it?
• Are real-time correctness or decisions being made based on the data?
• What is the cost of laying wired or satellite connections to the SCADA systems?
• With the volume of data coming out of the sensors, how long will a satellite system process and action on it?
• Are we leveraging external data and human centric data transformations to capture both internal and external knowledge for better insights using advanced analytics?

CloudPrisma IoT, along with advanced analytics and Machine learning framework, is meant to unclutter, simplify & prioritize the different feeds, compare with historical data, industry parameters, a definitive reference value, and other quick ad parameters real time decision making. CloudPrisma can customize and create an IoT Testing Platform that can connect multiple data sources, including lab devices, in-line hardware, SCADA systems, and third-party lab reports. This data can be consolidated to form a global repository of information, connected live at all times. This platform can provide the following features -

• Complete visibility across all locations of all testing hardware and data inputs
• Quality of data with cleansing and ingest further internal and external sources of knowledge.
• An audit trail built to verify real-time readings and facilitate metrological traceability chain
• Centralizing lab testing expertise while supporting distributed operations
• Context while analyzing data from different sources
• Capability to make automatic decisions and actions based on approved data parameters (i.e., instrument calibration)

The fully-functional CloudPrisma IoT Testing Platform system would mean that:

1. You could be notified if your data results stray from the norm.
2. Connected hardware could take these results and automatically make corrections to the system.
3. All your historical (and live) testing data could be viewed, in aggregate, on the internet-connected platform of your choice (i.e., computer or smartphone).
4. Significant savings on physical cable laying, especially in remote areas, and satellite spectrum.
5. Quality of data important for advanced analytics and create “new possibilities.”

CloudPrisma Solution Framework

CloudPrisma approach at each stage of the framework

Stage 1. Sensors and actuators -

Wireless or already wired or hybrid of them based on the situation. Sensors will give the ability to convert the information from equipment’s etc., and the outside world into data for analysis. The actuators can control to intervene in the physical world and control back the equipment’s and other “things.” CloudPrisma works with established OEM’s and Service providers for the specifications of the sensors/actuators and the network layout, based n requirement.

Stage 2. Sensor data aggregation systems and analog-to-digital data conversion –

This layer connects to the sensor network and aggregate output, while Internet getaways work through Wi-Fi, wired LANs, and perform further processing. CloudPrisma uses its Ingestion algorithms and tools and performs conversion in terms of timing and structure to process the enormous amount of information collected and squeezes it to the optimal size for further analysis. The key benefit that CloudPrisma brings at this stage is the Quality of Data with cleansing techniques and algorithms filtering unwanted data and creating opportunities for the use of “untapped” data.

Stage 3. The appearance of edge IT systems -

CloudPrisma prepares the data to be transferred to the IT world. In particular, edge IT systems perform enhanced analytics and pre-processing here using machine learning and visualization technologies. As per requirement, some additional processing may happen here before entering the data center.

CloudPrisma works with various OEM’s and third-party providers to build a secured Edge Computing environment such as Multi-Cluster Orchestration Platform, Secured Global LAN (SG LAN), leverage Kubernetes/AWS Outpost/Azure On-Premises based microservice from cloud to the edge, etc.

Stage 4. Analysis, management, and storage of data -

CloudPrisma, in the last stage, enables in-depth processing at the data center or cloud. Leveraging our deep analytics skills and the customers/third party OT (operational technology) professionals to create algorithms to create insights into the data. Data from other sources may be included here to ensure an in-depth analysis.

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CloudPrisma IoT's innovative framework allows customers to expand their boundaries for better insights and create operational efficiencies.

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