Digital Energy Journal- A ‘third platform’ approach to analytics

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A ‘third platform’ approach to analytics

Thursday, January 22, 2015

For oil and gas companies looking to improve their efficiencies, the EMC technology and model for moving to a 'Third Platform' data driven approach will improve data capture, utilization and bottom-line results, said EMC's Chris Lenzsch

For oil companies investing in new unconventional fields or revitalizing mature fields, modest improvements in efficiency can have staggering impact on both the top line revenue and overall cost structures.

Looking at an anecdotal example based on past experiences and digital oilfield use cases, the net impact of moving to a 'data driven approach' for a typical small to medium unconventional field can be expected to reach a 4% increase in oil production and 5% decrease in overall capex and opex spend, said Chris Lenzsch, Solutions Manager, upstream analytics with EMC. He was speaking at the Digital Energy Journal September 23rd Aberdeen conference, 'using analytic to improve production.'

For an example $2bn capital/operating budget and corresponding 100M boepd production forecast company, this means a $140MM revenue increase and $75MM cost reduction per year.

One of the potentially biggest areas to use analytics to improve both operations activities and production impact is artificial lift optimization, he said.

Ensuring your pump is continuously operating at optimal conditions for production through put and life of device, working out what intervention led to the biggest change in production, understanding common failure models predictively, and even acting on the 'front-end' of the well life-cycle making sure you get the artificial lift supply chain and logistics in place at the right time of the wells decline forecast model will reap big rewards.

'All these things can be driven through proper data capture and analytical models coupled with relevant time workflows,' he said.

For example, to optimize your completion models around 'best bang for the buck' to create maximum production, you can have a multi-variable, correlation model of frac actuals and production responses which you update after every frac, and a model of how the wells corresponding production is working in context of the correlation model which you continually update and continuously improve.

'You've got to understand and try to optimize across the whole lifecycle. Without the continuous loop process, it doesn't work nearly as well, wasting great potential. All this data is out here and it's always trying to learn, we need to make it happen.'

EMC is helping oil companies and partners with delivering technology and planning strategies for implementing effective big data and analytics on the third platform, looking at improving drilling and completions, production operations and optimization, reservoir exploitation, supply chain and logistics, performance based monitoring, and predictive machine learning models.

EMC has set up a research and development centre in Brazil focused on oil and gas big data and analytics, he said.

To get maximum benefit from you system, you must capture, store and be able to utilize data in the context of role centric activities and workflows, he said.

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