The New Oil | SLB

The New Oil

Published: 11/01/2018

Jennifer Presley, Executive Editor, E&P, speaks with oil & gas industry leaders, including Gavin Rennick, president of Software Integrated Solutions, Schlumberger, about big data.

Technology has long been a key driver in the success of the oil and gas industry. Digitalization—the use of digital technologies to change a business model and provide new revenue and value-producing opportunities—is driving the industry to a whole new level. In these post-downturn times, everybody is keeping a close eye on the bottom line and adopting solutions that help keep costs low without compromising workplace safety. The promise that data analytics, machine learning, artificial intelligence (AI) and more can provide these sought-after solutions is growing.

However, as is the case with most raw materials, value often increases with improvement. Raw data, like crude oil, also must be refined for its real value to shine brightly.

This data refinement process is one that the oil and gas industry has come to embrace in recent years. Aided by advances in high-performance computing, networking, storage, machine learning and more, operators and service companies alike are installing the infrastructure and writing the algorithms necessary to mine and refine the data into actionable steps.

Big Data is beginning to deliver big results, but is it doing so fast enough?

Partnering for success

Schlumberger, like other industry leaders, has adopted the spirit of creating and enabling a culture of continuous improvement through the use of digital technologies.

“Embracing new technologies generates a lot of excitement within Schlumberger. We have a natural bent in that direction, an almost genetic bias toward wanting to discover the next new technology,” said Gavin Rennick, president of Software Integrated Solutions for Schlumberger.

“From a leadership standpoint, it is critical to see that this is supported from the top and enabled from the bottom. For us, the most personal way of doing that is through training our employees, giving every employee access to the tools and capabilities to create or participate in working groups.”

For an industry built on data, sorting out good quality data from low-quality data has long been a difficult and time-consuming challenge, but Rennick believes the company has found a way to make that process far more efficient.

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DELFI enables users to take advantage of E&P domain science and knowledge using the latest digital technologies to unlock the value of data.

“It is important to understand that all data can be valuable and, when utilized, patterns within the data that do not seem intuitive can be realized,” he said. “Having an ecosystem that supports all of the tools to handle the volume of data also is essential. Working with Google enables us to do both. Their technology stack is built to handle Big Data.”

That partnership with Google Cloud was formally announced in 2017 with the release of Schlumberger’s DELFI cognitive E&P environment.

“The amazing thing about the DELFI environment is that it allows our customers to combine their data and petrotechnical expertise with new digital technologies such as AI and analytics tools, and is customized to E&P based on our knowledge of the domain science,” he said. “Our customers can automate and orchestrate processes in a customized and intelligent way, from a sophisticated interpretation of a piece of data down to the basics of evaluating its quality,” he said. “Many of those elements are key services and technologies built into the data ecosystem that is provided within the DELFI environment, and as the environment is open, they are also able to create their own.”

In the quest for lower cost and maximized efficiencies, operators are moving away from silos toward a systemwide approach to development. The digital transformation is facilitating this move, making innovation and technology development more of a collaboration rather than a solitary pursuit.

According to the company, the DELFI cognitive E&P environment enables a new way of working for asset teams by providing technology for seamless integration between geophysics, geology, reservoir engineering, drilling and production domains. The environment leverages data analytics, machine learning, high-performance computing and enables collaboration across E&P teams.

“We made the connection with Google early on, so we could work together to solve specific challenges the industry was facing,” Rennick said.

The companies first partnered on overcoming specific challenges around seismic, and from there it “blossomed into a much broader business relationship where we are now bringing products to market together. That is possible when you have a level of technical respect and a tremendous level of trust with the company with whom you’ve partnered. Those sorts of relationships are what you need in order to be successful in the world at large and certainly in this industry going forward,” he said.

The launch of the DELFI environment saw the deployment of an E&P data lake on the Google Cloud Platform that comprises more than 1,000 3-D seismic surveys, 5 million wells, 1 million well logs and 400 million production records from around the world, according to a Schlumberger press release.

“Our partnership with Schlumberger is a multiyear collaboration with several areas of focus. One is a focus on Big Data and the E&P data lake,” Google Cloud’s Darryl Willis said. “Another huge component is the focus on high-performance computing and also on artificial intelligence, particularly on accelerating seismic interpretation and in 3-D modeling.”

The E&P data lake is based on Google’s BigQuery, Cloud Spanner and Cloud Datastore platforms with more than 100 million data items comprising more than 30 terabytes of data. The Schlumberger Petrel E&P software platform and INTERSECT high-resolution reservoir simulator is running on a Google Cloud Platform integrated into the DELFI environment.

Gavin Rennick
Gavin Rennick, President of Software Integrated Solutions, Schlumberger
Jennifer Presley, Executive Editor, E&P
Article Topics
AI & Machine Learning Automation Data & Information Management
Products Used