Equipment Health & Performance Optimization
Upstream and midstream energy production assets are comprised of millions of pieces of equipment that support the development and production of fuel sources. These assets are critical to energy production, and having them deployed optimally is critical to achieve production targets, decrease costs, and minimize failures or downtime. For O&G operators to achieve their daily production targets, they need equipment to run optimally 24x7. However, operators are faced with equipment that performs sub-optimally and high equipment failure rates, which lead to unplanned downtime. Maintenance teams spend much of their time “firefighting” – reacting to unplanned downtime events. According to the U.S. Department of Energy, predictive maintenance saves 8% to 12% over preventative maintenance costs and upward of 40% over reactive maintenance costs. Specifically, the Equipment Health & Performance Optimization solution delivers the following capabilities for the customer:
- Real-time visibility to and insights on equipment health and performance
- Prediction of equipment failure days or weeks ahead for proactive maintenance
- Optimization of equipment to improve performance
The Equipment Health & Performance Optimization solution unlocks value by enabling organizations to address key challenge areas:
Outcomes operators see
Production Operations
- Missing overall production targets
- Unplanned downtime
- Expensive replacement of assets
Challenges personnel have
Equipment Failure
- Aging assets
- Inefficient servicing and maintenance of assets
Challenges customers experience
Sub-optimal Performance
- With limited visibility into asset performance, customers find it difficult to benchmark performance and prioritize improvements
- Error-prone manual calculations
- Expertise limited to a few SME
Lack of data-driven insights at scale
Inadequate Analytics and Tools
- Inability to leverage centralized data sets to train machine learning (ML) models for similar equipment leads to inaccurate and high false positives
- Inability to have a well- coordinated maintenance plan that takes into account real-time equipment health, and planned maintenance
How to get started
Step 1: Deployment Readiness Assessment (DRA)
Activities
- Business case definition
- Feasibility analysis for analytics/ML
- Data strategy
- Security strategy
Outcomes
- Readiness and maturity assessment
- Infrastructure inputs into planning
- Engagement scope
Step 2: Deployment planning
Activities
- Evaluate analytics/ML strategies
- Data lake environment review
- Enrich data lake with additional sources
- Architecture design
Outcomes
- Reference architecture
- Analytics/ML strategy
- End-to-end engagement plan
Step 3: Deployment execution
Activities
- Security (implement firewalls and data security) implement analytics workflow
- Build data visualization/UI
- End-to-end testing of equipment health workflow
Outcomes
- Implemented analytics/ML workflow
- Implemented data visualizations/UI
- Deployed use cases
Visit the AWS Solutions Library so you can learn how to get started with Equipment Health & Performance Optimization and other solutions for the energy industry.
Deployment partners
Technology partners
Shoreline IoT has simplified asset management with a single vendor, fully automated, end-to-end, AI/ML solution that unlocks access to operational data to extend equipment useful life by decades. Purpose built for non-experts, this plug-n-play solution is low cost, infinitely scalable and easy to install in minutes. Non-experts can effortlessly manage 24/7 remote asset monitoring, predictive maintenance and asset performance optimization at the same cost as manual inspections, making it affordable for all assets, especially unconnected ones.
Press Release: DCP Midstream Collaborates with Shoreline to Accelerate Next Gen AI/ML Asset Performance Management SaaS Solution
“Shoreline’s AI/ML APM solution is built on AWS to rapidly scale its solution and help transform asset intensive industry customers worldwide by enabling plug and play IIoT smart sensors with direct sensor-to-the-cloud connectivity,” said Yasser Alsaied, Vice President, IoT at AWS.
Oil & Gas companies, in all phases of collection, processing, and distribution, affords many opportunities for the investigation of production data to drive improved results in efficiency, safety uptime, and yields. Seeq® enables your operations engineers to quickly investigate and discover insights to improve bottom line results.