Visual analytics software for your entire company

We know Oil & Gas companies are dealing with fewer resources and greater financial pressures. VERDAZO was purpose-built to deal with these conditions. Watch our video to learn why it’s the best visual analytics software for Oil & Gas.

Enterprise-class software for Oil & Gas

Major value for your frontline users, your IT department and senior management.

Delivers bottom line value

By now, the stories are almost endless. Our clients have used VERDAZO to attract initial investors, to grow revenue without adding staff and to free up over 25% of their engineers’ time. They’ve found hundreds of thousands of dollars in unpaid revenue and made hundreds of millions in improvements in optimized completion designs. Learn more.

Maximize the value of your resources

VERDAZO creates alignment around people and processes, enhances communication across functional groups and improves your overall analysis capabilities. Ultimately, it ensures your people and your assets always deliver the maximum possible value.

Impact today, evolution tomorrow

Your organization will see immediate impact with VERDAZO – unlike with Tableau or Spotfire which require additional investments of time and money just to get started. Plus, our ongoing commitment to crowdsourced innovation means we’ll keep evolving to meet your future needs.

Industry-leading time to value

Users can do immediate analysis with VERDAZO by leveraging its targeted Oil & Gas analytics capabilities, crowdsourced workflows and pre-built templates. It’s so easy to use that they’ll often see value in the very first hour. No other data visualization software can make that claim.

Build a culture of analytics

To thrive in the future, an Oil & Gas company must make smarter, faster, and better decisions – with fewer people. That requires building a culture of analytics, where all users can access the consistent reliable information they need to innovate. Our software delivers all that.

Capabilities at a glance

Engineers & Operations

  • No more time-consuming or broken spreadsheets
  • Save the time, effort and cost of building your own tool
  • Incorporate all your Oil & Gas data sources
  • Do effective analysis from day one
  • Speed up your analysis with vast pre-built capabilities
  • Includes our Discovery Analytics methodology & workflows
  • Purpose-built for Oil & Gas
  • Embedded with industry experience, expertise & best practices

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IT Managers

  • Delivers consistent, reliable information
  • Centralized business logic
  • Provides enterprise-level scalability
  • Offers an open, configurable environment
  • Rapid implementation saves time and money
  • Flexible licensing structure
  • Not a build-it-yourself toolkit
  • Purpose-built for Oil & Gas

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Maximize your investment in analytics

Tap into our Oil & Gas expertise with custom training and consulting services.

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Our best content on Oil & Gas analytics

Machine Learning: Practical Use in Upstream Oil & Gas

There’s an enormous amount of discussion about the possibilities of Machine Learning but far less practical information about the impacts it can have on Oil & Gas today. In this presentation, we articulate some of most valuable prizes Machine Learning offers for upstream Oil & Gas, including feature importance and sensitivity analysis, and the power of predictive Machine Learning models. The presentation outlines two recent case studies – one focused on reservoir properties and the other focused on drilling and completion optimization – that bring the material to life. This presentation was originally delivered May 31, 2018 as part of the SPE Oil & Gas Breakfast Series in Calgary.

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Machine Learning

Predict production performance, reservoir properties and optimize well location & completion design.

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May 7, 2018 by

Machine Learning: Is it really a Black Box?

Machine Learning isn’t the “black box” that many perceive it to be. On complex data sets, the use of Machine Learning with a rigorous process and supporting visualizations can yield far more transparency than other methods. What is a “Black Box”? Machine learning models are sometimes characterized as being Black Boxes due to their powerful ability to model complex relationships between inputs and outputs without being accompanied by a tidy, intuitive description of how exactly they do this. A “Black Box” is “a device, system or object which can be viewed in terms of inputs and outputs without any knowledge of its internal workings” (Source: Wikipedia). Black Boxes (and Machine Learning models) exist everywhere We tend to label things as “Black Boxes” when we don’t trust them more than when we don’t understand them. Machine Learning models aren’t unique in having an element of “mystery” in how they work – there are all sorts of things we trust all around us for which we don’t fully understand the inner workings. GPS, search engines, car engines, step counters, even the curve fitting algorithms in Excel are examples where we trust what’s happening inside because we’re able to see and, with experience,...

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