Unparalleled capabilities that enhance data governance

VERDAZO is software that can scale with your organization’s growth and offer consistent reliable information delivery. Watch our video to learn why it’s the best visual analytics software for Oil & Gas.

Enterprise-scale capabilities and sustainability

VERDAZO has more power and flexibility than any other Oil & Gas analytics software.

Consistent reliable data delivery

Stop relying on spreadsheets that break and burn up your users’ time. Create a single source of data truth across the organization that enables better communication and alignment, and reduces data maintenance costs.

Pre-built capabilities in a configurable environment

On top of a library of pre-built Analytics Accelerators, workflows and data visualization templates, VERDAZO offers an open, configurable development environment.  You can either scale it yourself or leverage our team’s skills and experience.

Cost-effective scaling for organizations of all sizes

Our software scales effectively and efficiently whether your organization has 10 people or 10,000. We also offer data integration services and a flexible licensing structure that lends itself to your evolving business needs over time.

Rapid implementation saves time and money

Our team will get yours up and running fast. We accelerate implementation by using our library of Analytics Accelerators, which are pre-built configurations for dozens of core Oil & Gas systems and workflows — all in an open, configurable, administrative environment. Over the years we’ve performed hundreds of implementations with thousands of users. We do it better than anyone else.

The enterprise-class analytics engine

VERDAZO delivers critical value all across an organization, catalyzing innovation while enabling scalability, repeatability, security and centralized, consistent business logic.

Capabilities at a glance

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

Learn how VERDAZO works for your IT Department

Whether it’s data integration and configuration, or broader Oil & Gas consulting, we’re the best in the business.

Let’s talk

Industry-leading Oil & Gas analytics content

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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