OilPrice.com recently reported that if the Oil & Gas Industry fully leveraged the latest advances in IoT and advanced analytics, they could cut CapEx by 20%, and reduce operating expenses up to 5%.1 Currently only 1 percent of the data collected from sensors on offshore rigs is used in decision-making and only 3-5 percent of oilfield equipment is connected, leaving lots of opportunity.
The newer competitive options for energy are taking a much more aggressive approach and are much further along with digital strategies. Renewable energy solutions providers are already offering smart solutions and real-time services made possible by IoT analytics and cloud computing.
There are several fertile areas to target in Upstream, Midstream and Downstream Oil Field Operations. Below are some examples such as monitoring equipment & predictive maintenance, intelligent dispatch operations for support technicians and engineers, operational visibility in supply chain, but there are many more.
Monitoring Equipment & Predictive Maintenance
The cost of lost production due to equipment breakdown or failure is high. Equipment technicians need to have the earliest possible signals when failure may occur – finding out after a failure is usually too late to avoid significant expense and hassle.
Oil Equipment Manufacturers are often committed to providing ongoing and effective preventative maintenance for their equipment, even if they are monitoring thousands of locations spread around the globe. Monitoring, predicting, and acting to prevent failures on the complete installed base of machines is an extraordinary analytical challenge that requires new ways to capture, monitor, and act on information in real- time. IoT Advanced Analytics can unify historical and streaming real-time data to produce predictive analytics that can identify problems before they occur, and prescriptive analytics that recommend specific action steps that can be taken to prevent problems before they occur and become more expensive.
Intelligent Dispatch Operations for Support Technicians and Engineers
Dispatch Operations Management entails scheduling, optimizing, and dispatching teams of technicians into the field to manage service and repairs of equipment. It is a challenge to be able to optimally prioritize, schedule, and dispatch service personnel from a variety of internal and external organizations to different locations, while minimizing cost and maintaining high response time.
Oil and Gas firms face many challenges that impact dispatch operations, including the cost of fuel, vehicle maintenance costs, carrying the correct inventory, remote locations, missing analytical and service data, and a lack of real-time communication.
Mobility solutions simplify many field service processes like data collection with features such as barcode scanners, SCADA sensors, utility line sensors, RFID, and GPS. Being able to combine real-time weather information with the location of known assets, such as support equipment and personnel, allows for targeted alerts and notifications based on real-time correlation of data using geospatial intelligence. These types of alerts are extremely effective for optimizing routes and reduce vehicle turn.
With the use of IoT Analytics, organization can addresses this challenge with Smart Actions that provide support operations a solution for scheduling, dispatching, and managing inventory in real-time. This helps Oil & Gas firms to optimally plan and dispatch field engineers and their properly stocked vehicles to a customer’s location in a timely manner in order to deliver against their service-level agreements (SLAs).
Operational Visibility in the Supply Chain
It is a struggle for equipment providers or oil gas operations to get the most current status of supply, inventory, or orders in their supply chain and even more importantly, to know if there is a problem. Why? Because there are so many entities involved, each with their own “siloed” systems. It is difficult to pull information together from several disparate systems that are often using outdated information and different information structures. Using supplemental available IoT sources and Advance Analytics, organizations are able to track and trace all supply chain activities in real time, provide alerts as soon as problems occur, and prescribe Smart Actions and automated workflows that can route resources to address the problem in the most expedient manner.
The IoT Analytics Maturity Model
The irony of the IoT era for manufacturers is that while it offers great promise because of the ability to leverage the high volume of data and interactions, it is also difficult to put it all in context and take meaningful action that will have an economic impact. The applications outlined above offer strong potential for analytics applications, but a methodology is needed to sort through and prioritize the projects.
This blog began by asking if advanced analytics can drive business value for the Oil & Gas Industry. The methodology we like to use at Vitria is to think about it in terms of an IoT Analytics Maturity model – as shown in Figure 1 below.
Enterprise systems provide snapshots of limited information but the data is often outdated as soon as it is published. This problem gets magnified if there are multiple enterprise systems connected together across a supply chain.
Connectivity – By ingesting IoT data streams at speed and volume throughout the maturity model, and combining it with information coming from enterprises systems, a robust IoT Analytics platform enables equipment & logistics monitoring at “live” speeds.
Operational Intelligence– Real-time Streaming Analytics processes incoming streams of data from sensors and devices and is then correlated with contextual and historical data to provide a baseline for advanced analytics. Contextual data can include information like environmental factors or historical performance of suppliers.
Predictive Analytics and Machine Learning: The next step is to predict failures, anomalies, or patterns using predictive analytics that are based on machine learning over situational data such as external events like the current plant utilization rate or the condition of production equipment.
Prescriptive Smart Actions – The final step in the analytics maturity model is to apply prescriptive analytics to determine the next best smart action to take. This next best action could be a wide variety of actions associated with lowering risks, such as addressing an equipment performance issues or traffic delays, or other timely actions that enable more efficient operations.
As shown in the figure above, it is this final step that captures the greatest value.
There is increasing pressure to pump more oil out of existing wells, cost effectively, using advanced drilling technology. Utilizing IoT and IoT Analytics will enable companies to limit production loss due to equipment downtime, and at the same time, reduce CapEx and Operating costs. It is a far cheaper investment, with higher returns than drilling new wells or deploying new well technologies. IoT Analytics is the key to monitoring the health of the oil field by providing earlier notification and real time data for dispatch, predictive analytics to optimize equipment and logistics processes, and scientific reporting to help create more ways to be more efficient.
While there is a significant “untapped” opportunity, the industry already has the variety, volume, and velocity of IoT data coming in. Next steps are to address the complexity required with a unified analytic software platform designed specifically to handle the vast streams of IoT data. Adding these analytics is a proven systematic approach to derive the most value.
Add Vitria to your next IoT Analytics Project Plan
Vitria’s VIA IoT Analytics Platform is capable of leveraging the IoT data from all your sensors and networks to maximize business value by delivering powerful insights in real-time to help you take timely intelligent actions. A command center full of powerful self-service tools and comprehensive dashboards allow you to review and act on fast analytics in real-time across all types of analytics (i.e. streaming, historical, predictive, and prescriptive).
The platform offers an open and flexible platform that can handle all the stages of evolution for IoT value generation. You can get started and proceed at your own pace, choosing the use cased that make the most sense for your business. And rest assured that your initial choices and experience will all be leveraged and drive value for your company over the long run. Learn more how VIA can help you succeed with IoT Analytics.
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