How Closed-loop Operations Enable Digital Transformation of Oil and Gas Fields
Oil and gas companies have been collecting huge amount of operational data – from exploration to processing, long before the IIoT was coined. However, turning that vast amount of raw data into contextual information around equipment and processes often required massive computing power and storage which were either too costly or non-existence previously. Today, the advancement in technology – cloud platform, analytics and computing power – is revolutionising the way how companies can leverage big data and analytics to compete and operate their oil and gas fields.
Lacking clear perspective on Analytics applications
Although the falling cost of connectivity, data storage and processes have enabled oil and gas producers to gather more data from assets and operations than ever before, most companies are still lacking a clear perspective on extracting values from data given the breadth of advanced analytics applications being developed - from producing wells to processing facilities. Digitisation of business and operational processes, if well executed, will enable producers to gain organisation agility and performance visibility -ability to quickly respond to changes in the internal and external environment, to optimise operations and to improve collaboration based on a single source of truth.
Predictive Analytics Applications from Producing Wells to Processing Facilities
Predictive analytics predict performance behaviours of operating assets and processes. These analytics leverage advanced pattern recognition, statistical models and machine learning technology to model an asset’s operating profile and processes, and predict future performance, recommending appropriate, timely actions to improve production uptime and to optimise operating conditions. Some of the key areas where analytics have been successfully deployed are:
- Production Allocation & Planning: Advanced simulation and analytics tools can be used to model and predict the performance of producing wells, allowing proper production recording and planning and uncovering production potential in existing assets.
- Gas lift Optimisation: Advanced analytics can be used to optimise allocation of injection gas to boost production in oil field.
- Gathering Network: Analytics can be used to model fluid flow behaviours in pipeline- multiphase or single-phase flow - to predict pipeline holdup and potential slugging in the network, optimising the designs to reduce CAPEX, production and transportation costs
- Asset Optimisation: Predictive asset analytics have been gaining grounds in oil and gas operations to help reduce abrupted equipment failure that can cause costly production outages.
- Process Optimisation: Process optimisation analytics reconcile dynamic process data – such as pressure, flow rate, and temperature - in real time and predict the optimum operating model based on thermodynamic laws and its physical properties.
4-Stage Closed-loop Framework to enable Digital Transformation
Digital transformation is not only about technology. It requires a holistic approach to transform operations – such as changes to existing workflow, operations and business models. The principle of a 4-stage closed-loop framework – connect, collect, analyse and act - is key enabler to digital transformation. Improving a process requires monitoring of key performance indicators (KPIs) and detecting of any deviation from the targets. This requires understanding the process context to assess various options; making a decision on the most appropriate corrective action); and finally ensuring that the decision. An effective closed-loop performance management platform, combined with analytics, can help companies unlock additional millions of dollars in value.
Are you ready to enable Digital Transformation in your enterprise today?
Download the whitepaper to learn how you can transform your operations management strategies from Reactive to Predictive, reducing breakeven oil and gas prices. This white paper discusses the 4 stages of closed-loop operations framework to unlock business values from big data and analytics – from producing wells to surface facilities, effectively optimising process conditions and reducing unplanned downtime.
Eddy currently manages Industry Solutions marketing at AVEVA, driving awareness of new solutions that enable enterprises to stay ahead of the curve. Over the past 15 years, he has been involved with product management, marketing and sales management in the Industrial Automation space. He is a strong advocate for leveraging technology to improve operational processes to enable a profitable and sustainable future for every stakeholder, Eddy holds a MBA from National University of Singapore and a Bachelor in Engineering from Nanyang Technological University.