How Advanced Analytics in Oil & Gas Are Opening Up a World of Possibilities


Posted on: September 2, 2016 by Dr. Erwin Dijkstra

The oil and gas environment has become increasingly challenging, since oil and gas is more and more difficult to find, extract and produce. Extraction now has to deal with deep water, deep and tight reservoirs; wells of 5 km long, temperatures in excess of  130 degree Celsius, high pressures and high levels of shock and vibrations. In these conditions steering the well must be done with high precision, often aiming for a pay-zone that is mere meters in diameter.

Understandably, to successfully navigate the drilling requires a high-level of downhole technology, with steering and logging reliant on numerous advances in both software and hardware. Resilience is critical: failure of just one of these devices can lead to several days of downtime at high cost and risk of deteriorating quality of the well bore.

Here are some of most important advancements in technology for the industry:

Diagnostic & prescriptive analysis of large set of runs

Logging and steering tools have multiple sensors and collect high resolution data of downhole operational and environmental conditions. Big Data analytical platforms provide the opportunity to analyse this diagnostic information for large sets of runs (hundreds - few thousand) with millions of measured of hundreds of observables, creating a representative view on the chances of success or failure during any given operation.

This big data approach to investigate so many runs in one study is completely new. The diagnostic analysis studies the operational conditions that increase risk of failure. The diagnostic analysis is input to enable predictive models to be built which can be used in several ways:

  • Operational Guidance: Downhole tools store the data in memory. Small datasets can then be sent back to the surface by low frequency pressure pulses through the drilling fluid. The new models can offer a more accurate, real-time update on the operational conditions in the well and sent indication to surface to the driller to update him on the potential risks, therefore reducing the chance of downhole failure and ultimately limiting non-productive time.
  • Preventive maintenance: The models also help predict when specific parts are likely to fail and should be replaced. By evaluating the downhole-data after each job, and keeping track of such cumulative exposure, we can update and fix any at risk parts before they break.

The richness of the available downhole data allows for other types of analysis. Here we are not considering the formation data, but simply the data on tool conditions and status, environmental and operational conditions and parameters. This data is collected by the service company to improve its tools and job execution; it is not common to share this with the operator. However, with the deep insights that the new evaluation capabilities offer, it becomes useful to share some specific information with field owner, operator and other service companies.

Big Data Lake

Well construction is part of a larger business value chain: Atos Ascent industrial data platform

  • For the asset owner and operator: from field development planning to oil & gas sales
  • For the service company: from order to cash

Big Data platform is required for the analysis as described here, but also for and in the other business functions. And there is great benefit for corporate optimization in combining the performance indicators and drivers of all of these functions. As you can see in the below diagram, this enables organizations to become data driven, where people in different business functions have access to information over the entire business value chain and can take much better decisions:

Creating  an Industrial Data Platform

Atos Ascent data and analysis market placeThe value of data becomes a key differentiator. Business ecosystems of partners working together want to share their data and insights in a safe and secure manner, with properly controlled permission for specific purposes. This is already happening in the B2C market with connected consumers and the potential benefits for a B2B partner ecosystem are very significant. In the oil and gas industry we can expect the emergence of Industrial Data Platform, i.e. Data & Analysis Market Place for suppliers, partners and clients, in the next few years.

In my next blog, I’ll discuss how new advanced analytics will revolutionise the oil and gas industry.

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About Dr. Erwin Dijkstra

Head of Atos Codex Offers for IoT, analytics and AI, Distinguished Expert and member of the Scientific Community
Erwin Dijkstra is responsible for Atos Codex Offers in IoT, analytics and Artificial Intelligence. Erwin has a PhD in Solid State Physics, has worked almost a decade for a leading Oil company in drilling, petroleum engineering and field development planning. Erwin is a member of the Atos Scientific Community that is the best 135 scientific people from within the group who are “creators of change”, making sure that whenever our clients choose Atos they always get the best solutions available in their journey to digital transformation. In Erwin’s view, as a business expert, he has a duty to keep learning with its customers, to keep actively engaging with disruptive innovative ideas, to have regular exchange with his peers and expert communities, and to be open to investigating new developments. He is fully committed to help Atos and Atos’ clients anticipate and craft their vision regarding upcoming technology disruptions and the new challenges facing our industry.

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