Coronavirus has a serious impact on global oil demand and prices, with the WTI / Brent crude oil benchmarks plummeting since January 2020. Low prices, coupled with an unprecedented decline in demand, will be difficult for the upstream sector in the near term, particularly for regions with unfavourable economies of production. In the current scenario of a historically low-price environment, the debt-ridden US shale / tight oil industry will see the biggest hit, with drilling capital budgets cut, operations shortened, and production declining.
IIoT (Industrial Internet of
Things), Digital Oilfield 4.0 and Industry 4.0 are some of the truly important
terms describing digital transformation in today's oil and gas industry. It was
no surprise that a recent survey pointed out that while most executives agreed
that digital transformation would be an important source of growth for them
over the next few years, they still lack a clear perspective on where and how
to embark on the "right" digital journey to maximize the production the potential of their assets, particularly given the wide range of complex
applications.
Comprehensive
approach
Digital transformation is not
just about technology. It offers a comprehensive approach to transforming
operations – such as changes to existing workflows, operations and business
models. For example, improving the process requires monitoring of key performance
indicators (KPIs) and alerting stakeholders to any significant deviations from
the targets. This requires an understanding of the process context for
assessing the various options; taking a decision on the most appropriate
corrective action; and finally ensuring that a decision is taken. An effective
closed-loop performance management platform, combined with analytics, can help
companies unlock additional millions of dollars of value.
Production to
Processing - Application
Predictive analytics predicts
the performance behaviour of operating assets and processes. These analyses
leverage advanced pattern recognition, statistical models and machine learning
technology to model the operating profile and processes of the asset and
predict future performance, recommending appropriate, timely action to improve
production uptime and optimize operating conditions. Some of the key areas in
which 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 the allocation of injection gas to boost production in oil field
- Gathering Network: Analytics can be used to model fluid flow behaviours 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
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