Digital transformation journey in upstream oil and gas, gas processing

IIoT, Digital Oilfield 4.0 and Industry 4.0 are some of the really big terms describing digital transformation in the oil and gas industry today. It came as no surprise when a recent survey pointed that while most executives agreed digital transformation would be an important source of growth for them over the next several years, they are still lacking a clear perspective on where and how they can embark on the “right” digital journey to maximize production potential of their assets--especially given the breadth of complex applications from wells to processing facilities, and from designs to operations in both asset and operations lifecycles.

Digital transformation of business and operational processes, if well executed, will enable producers to gain organization 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. It can be a game changer for most oil and gas operators, giving them a distinct competitive advantage in term of reduced OPEX and improved throughput.

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 Optimization: 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 behaviors in pipeline- multi-phase or single-phase flow - to predict pipeline holdup and potential slugging in the network, optimizing the designs to reduce CAPEX, production and transportation costs
• Asset Optimization: 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 Optimization: Process optimization 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

Holistic approach to Digital Transformation is Key

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. For instance, improving a process requires monitoring of key performance indicators (KPIs) and alerting the stakeholders of any meaningful 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.

Last mile of Digital Transformation

Insight alone does not create value. Action is needed to close the loop but all too often, value is lost as a result of failing to act timely on the information to close the loop. Automated Workflow is a critical component of an effective IIoT architecture, equipping employees with decision tools and setting clear responsibility and accountability to close the performance loop which is the last mile of a digital transformation.

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