The world’s energy industry is now challenged with a burgeoning demand in emerging economies, competition for leasing rights and financial capital, and increasing public scrutiny and regulatory demands for transparency – all while trying to ensure delivery of product with aging assets and the threat of a retiring work force. In this environment, oil, gas and utilities companies are seeking opportunities to improve processes and technologies to remain competitive. Qualex can provide everything needed – including predictive maintenance, forecasting and analysis, and energy trading and risk management systems – for oil, gas and utilities companies to create intelligence from new and existing data sources and deliver information for effective decision making across the enterprise.[read more=”Read More” less=”Read Less”]
Why you need Qualex
Qualex’s Oil, Gas and Utilities practice can help in the following areas:
• Upstream: Drilling performance analytics, Planning and forecasting production; Controlling costs through predictive maintenance and asset optimization; Reducing risk by identifying and mitigating exposure; and Increasing overall business performance.
• Midstream: Transport and storage optimization, Reserves and distribution dashboards and Flow and leak detection.
• Downstream: Forecasting demand of products and services; Minimizing risks of financial transactions; Extracting valuable insights from a company’s in-house data.”
• Reporting and optimizing regulatory compliances.
Let us show you how a modest investment in technology can substantially increase your ROI. Let us help you manage your business better through your data. And help you minimize costs and drive profit straight to your bottom line.
Predictive Asset Maintenance, as an example
SAS Predictive Asset Maintenance helps organizations to accurately predict events that could cause outages and to run their assets at peak performance. The solution uses data integration, automation, analysis and predictive analytics to boost uptime, performance and productivity while lowering maintenance costs and the risk of revenue loss.
• Reduce downtime
• Optimize maintenance cycles
• Reduce unscheduled maintenance
• Improve root cause analysis
• Enhance data visibility[/read]