Do your fastest, most effective analyses ever

We know you’re trying to make the best, most profitable decisions, which are hidden in masses of data. Watch our video and learn why Verdazo BI is the best software for Oil & Gas.

This is the data visualization software you’ve been looking for

If you’re doing Oil & Gas analysis without Verdazo BI, you’re already behind.

Purpose-built for Oil & Gas

Other data analytics software tries to work for everyone under the sun. Verdazo BI is built just for you. We’ve worked with hundreds of Oil & Gas industry experts and thousands of users to tailor its capabilities to your analytics challenges. You’ll experience its power from the first day you use it.

Unique Discovery Analytics

Discovery Analytics is our unique visual analysis methodology. Other tools let you explore data but only within the bounds of how they were built and limited by the technical and domain expertise of their creators. Verdazo BI enables you to cut a path through the data and steer your evolving analysis in whatever direction your insights take you.

Broad pre-built capabilities

You don’t have to build anything with Verdazo BI. We’ve done it for you. Verdazo BI comes with our pre-built Analytics Accelerators: chart templates, workflows and custom reports, plus you can build your own analyses. Our Analytics Accelerators are embedded with Oil & Gas best practices and customizable to meet your specific business needs.

Value from day one

Some data analytics software requires you to devote extra time and energy before you can do any effective analysis, but Verdazo BI is no build-it-yourself toolkit like Spotfire or Tableau. It’s a fully built software application and is ready to use from day one. In fact, many users are doing effective analysis within minutes of being set up.

Machine Learning

Artificial intelligence offers you the ability to leverage the integrated datasets used across all asset life-stages. You can identify and quantify which inputs matter most for specific outcomes, determine dependencies between model inputs and develop predictive models – and that’s just the start. Machine Learning will help you take your analysis to the next level. Learn more

Capabilities at a glance

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

Explore our industry-leading analytics content

May 13, 2019 by

Verdazo Analytics at geoconvention 2019, Calgary

There are three ways to see Verdazo’s team in action at geoconvention 2019 in Calgary. Marcelo Guarido will be presenting Machine Learning Strategies to Perform Facies Classification Tuesday May 14th at 9:00 am in the Glenn Room 206. Verdazo Analytics’ Director of Data Science Brian Emmerson will co-present The Importance of Geoscience in using Machine Learning to Predict and Optimize Well Performance – Case Study from the Spirit River Formation Wednesday May 15th at 10:35 in the Telus Room 104-105. You can also catch members of the Verdazo team at Booth 503 to learn more about our visual analytics and machine learning capabilities.

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May 12, 2019 by

Augmenting Well Production Analysis with Subsurface Data

The Montney Formation, located in the Western Canadian Sedimentary Basin, is developed in a multi-zone stack throughout the fairway.  Unfortunately, these refined target zones are not captured in public data.  For analysis, it is important to differentiate Montney Wells into multiple target zones because they vary significantly in reservoir properties both vertically and laterally. Identifying the target zone based on sequence stratigraphy is a valuable process but can be time-consuming. In this blog we show a quick method to differentiate target zones using a depth-based approach that is helpful when you have limited time and resources.  This workflow can be applied to any map-based data to derive a data set suitable for well production analysis. For contour-based geologic data to be useful for well production analysis, we need a map-derived value for each individual well.  To accomplish this, we started with a publicly available Geologic map of the Montney Top in Meters Subsea (BC OGC, 2012). Figure 1: Digitized and interpolated Montney Top Subsea TVD (True Vertical Depth) Structure Map, (OGC, 2012). The Montney Top Structure map contours were digitized (Figure 1), so that interpolated well-values could be derived.  Using point-sampling, the Montney Top Depth was extracted at the intersection...

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April 14, 2019 by

Anton Biryukov of Verdazo Analytics places third in global machine learning competition

Verdazo Analytics Data Scientist Anton Biryukov took home third prize in a machine learning competition in March of this year. “Turn up the Zinc” was a crowdsourcing challenge to augment Glencore‘s efforts to predict zinc recovery at their McArthur River mine in Australia. The participants used the Unearthed platform and consisted of 229 global innovators from 17 countries forming 61 teams and submitting 1286 model variations over one month. “The Unearthed platform provides a great opportunity to polish my data science skills, while solving applied problems in the oil and gas and mining industries,” said Anton, who worked on the problem during his spare time. While most contest submissions were team collaborations, Anton chose to tackle the problem with the help of just one junior data resource. “For my team, third prize in this competition means motivation to try harder in the next challenge, plus new doggy treats for Junior Data Analyst Lumi.” Lumi and Anton discuss strategy For more information on “Turn up the Zinc,” click here.

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