Nov-2024

Digital strategies for refinery operators

Large-scale digitalisation of the downstream sector will only be possible if companies make all the data they collect available in a way that’s intuitive to human users and machines.

Cognite

Article Summary

However, for many downstream operators, data is trapped in complex, siloed systems. This makes it more complicated for workers to use the data in their day-to-day activities; data scientists must build point-to-point integrations every time they want to develop a new application, and maintenance workers have to access multiple systems to find the information they need.

Digital transformation presents a game-changing opportunity to improve yield, productivity, asset reliability, and workforce effectiveness. Refiners need to sharpen their digital capabilities in three critical areas: analytics in production, field force effectiveness, and asset management.

Unexpected refining outages have soared in recent years, surpassing 2,000 incidents in 2019, quadruple 2015 levels, according to Industrial Info Resources, a provider of industrial process and energy market intelligence. Cognite’s solutions can help operators monitor asset integrity, anticipate unexpected shutdown, and boost plant uptime with a state-of-art root-cause analysis system powered by physics-guided machine learning.

Strategic investments in digital tools and systems support cost reductions and production optimisation, which can help refineries become more adaptable, responsive, and competitive in a shifting landscape. To stay competitive, companies need to embed digital capabilities in all aspects of their operations in order to improve efficiency, reduce costs, and protect revenues and margins.

Cognite helps liberate the data from siloed systems, such as historians, control systems, and various ERP systems and contextualise it for easier creation and deployment of analytics models and business applications powered by artificial intelligence and machine learning. Cognite creates a digital representation of a company’s operations by connecting all of the IT and OT data together. With contextualised data as a service, downstream operators no longer need to collect, clean, and contextualise data for every new data science project. This enables companies to scale beyond pilot projects and create solutions that generate real value, from more robust and reliable machine learning applications for optimisation and automatisation to human-facing applications such as advanced visualisations.

Liberating and contextualising data expands the applications of advanced analytics, which can significantly improve our understanding of how plants work by revealing hidden bottlenecks and solving complex problems. Cognite’s interdisciplinary team, which includes people with more than a decade of experience from operating refineries, as well as experts in process engineering, instrumentation, automation, and optimisation, is perfectly positioned to help downstream operators identify and unlock unrealised value. This paper explains how Cognite’s products can help operators and plant owners accelerate field force effectiveness, optimise plant production efficiency to reduce the cost of operations while increasing refinery throughput, and plan and carry out effective maintenance and inspection activities while gaining much deeper insight into asset integrity.

Investments in data operations (DataOps) platforms and digital tools can support cost reductions and production optimisation, which can help refineries become more adaptable, responsive, and competitive in a shifting industrial landscape. To stay competitive, companies need to embrace digital capabilities in all aspects of their operations in order to reduce costs, improve efficiency, and bolster revenues and margins.

Current processes make assets run inefficiently, consuming significant resources
Digitalisation requires universal access to understandable data, data that has not just been collected across siloed source systems, but connected for contextual significance, discovery, and meaning. It requires a central DataOps platform that allows subject-matter experts to unleash their creativity, resulting in operationalised digital use case execution for better decision-making and streamlined processes.

Cognite Data Fusion® gives operators that foundational layer, providing a holistic data model that represents the physical assets and serving as a robust structure to digital twin applications.

Common processes in refineries like crude oil allocation and scheduling require data from many different systems, such as historians, ERPs, laboratory data, specification sheets, and more. The process of feeding the data into software or a proprietary algorithm requires a lot of manual work by a skilled worker. Since the process isn’t automated, it consumes significant resources and carries the risk of manual errors.

Further, downstream operators have highly coupled processes that require predictive control. Realtime optimisation presents an opportunity to run plants optimally, stabilise plant processes, and help make them more agile.

Running a downstream asset continuously at maximum efficiency and effectiveness isn’t an easy task. Operators have to apply their subject-matter expertise to manually ingest data, run experiments by tweaking variables and seeing the impact on asset performance, and make decisions based on the results. This is time-consuming work, and there is no guarantee that the asset will be operating at its maximum efficiency.

Optimise production processes to maximise plant yield
Reduce time to value. Cognite’s products drastically reduce the time skilled workers need to access data from multiple data sources, making the data available via a unified API, feature-rich SDKs, various connectors, and through dedicated applications. This helps free up time, which experts can then reinvest in activities that generate value. Automating data collection and cleaning also eliminates the risk of manual errors, increasing data quality.

Cognite Data Fusion® was built to tackle data quality monitoring challenges and make data readily available for computation. Liberating and contextualising the data from different sources makes it easy to perform real-time optimisation. Cognite’s digital twin technology can be leveraged to combine the liberated, contextualised data residing in Cognite Data Fusion® with visualisations, simulators, and optimisers to guide a suboptimally running plant toward the optimal operating point.

Cognite provides an open, unified asset model supported by a holistic DataOps framework. With the help of Cognite Data Fusion® and advanced analytics it facilitates, assets can consistently operate at maximum effectiveness and efficiency. All the data from different systems is easily accessible, making it easy to perform production programming.

Data in Cognite Data Fusion® can power machine learning models that can predict yield, energy consumption, and product specifications within the error ranges defined by experts. These machine learning models can then be incorporated into dashboards to ensure assets continuously work at maximum efficiency, maximising yield while reducing energy use and waste, and keeping assets within their specification limits. Even small improvements in asset performance can translate into significant revenue gains.

Together with some of the largest players in oil and gas, Cognite has developed best-in-class intraday performance logic to reach the full value potential of production optimisation by adopting a continuous, data-driven approach to production performance management. Using insights from historical and real-time production performance tracking to provide guided recommendation and access to performance enhancing advisors, refineries can detect, assess, and act on opportunities for reaching and expanding maximum throughput.