“Our energy asset management offerings solve problems across the full spectrum of the sector–from oil and gas to renewable resources,” says Philippe Herve, Senior Vice President, Energy and Sustainability.
To cope with the challenges of the 21st century, such as aging assets, climate change, and net zero initiatives, SparkCognition’s Oil and Gas Maintenance Advisor (OGMA) provides sophisticated solutions to oil and gas operators and helps them predict equipment failures in advance. OGMA combines predictive maintenance, prescriptive maintenance, and production optimization into one solution. Powered by machine learning, predictive maintenance derives sensor data from a facility’s operations and builds a model that imitates a profile of normal operations. The model then analyzes sensor data in real-time to detect any abnormalities or deviations in the system and provides insights about how and when a failure could occur. This gives leeway to the operator to plan timely maintenance and avoid unnecessary downtime and catastrophic failures.
Using SparkCognition’s ML Studio, an automated model building product, OGMA enables data scientists and non-technical users to build highly accurate predictive models based on production data in a matter of hours, assuring speed and scalability. Additionally, OGMA’s prescriptive maintenance uses a natural language processing (NLP) product, SparkCognition Deep NLP, to assess fault codes, deliver the most relevant documentation, streamline the repair process, and capture user input to improve results.
With the acquisition of a renewable energy technology company in 2021, SparkCognition further expanded its reach in the renewables sector and solved problems within it. One of the biggest challenges in renewable energy transition lies in scaling production to maintain its presence in the global energy mix. Given the uncertainty associated with renewable energy production and storage, it is also essential to strike a balance between the supply and demand of renewable energy. SparkCognition empowers its clients to identify underperforming assets and helps them increase production with constructive planning. With the help of machine learning and clean energy, SparkCognition Renewable Suite delivers complete asset management and predictive analytics to users. Renewable Suite combines data analytics with physics-based digital twin technology, resulting in comprehensive models with high accuracy and extended prediction horizons. Within the solution, operators can view asset health and impending maintenance needs, site environmental conditions, energy production, and more, from a fleet-level view down to individual devices. This delivers bottom-line benefits like increased revenue, fewer failures, and optimized processes and planning.
Another growing concern for all major industries is the increasing incidents of cyber-attacks in the energy sector. To safeguard the industry from such threats, SparkCognition has built an AI-powered cybersecurity solution, SparkCognition Endpoint Protection (EPP), which protects IT and Operational Technology (OT) infrastructure from zero-day attacks. With the advancement of Industrial IoT tech and the sensorization of legacy OT assets, protecting them has emerged as a priority.
Our energy asset management offerings solve these problems across the full spectrum of the sector–from oil and gas to renewables
With a sparkling track record of successful, large-scale solution deployments in various sectors, SparkCognition is motivated to build all solutions to be AI-first. To scale up projects, the company has developed an extensive intellectual property portfolio with over 150 granted and pending patents in the field of AI. It continues to invest in AI research and development to fuel its innovations.