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

Senior Management

  • Targets efficiencies
  • Optimizes corporate performance
  • Adds millions to your bottom line
  • Creates alignment between people, processes, and data
  • Delivers value from day one
  • Catalyzes innovation across your organization
  • Purpose-built for Oil & Gas
  • Creates a culture of analytics

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
  • Purpose-built for Oil & Gas
  • Not a build-it-yourself toolkit

Analytics for the entire well lifecycle

Planning

Drilling

Completions

Production & Operations

Planning

Optimize your development strategies and corporate value

  • Use public data to understand evolution of plays and technology.
  • Perform competitor analyses and leverage best practices for type curves, completion design and statistical methods.
  • Scrutinize data quickly, easily and visually.

Drilling

Get an integrated view on how drilling impacts all aspects of a well’s lifecycle

  • Use rig-state KPI’s to compare current and historical drilling activities to identify optimization opportunities.
  • Leverage drilling data to inform completion design.
  • Integrate multiple data sources to get a holistic view of drilling impacts on value.

Completions

Optimize your completion design with multivariate analysis

  • Compare different operators’ completion techniques to refine your approach.
  • Better understand the impacts of technology & design on production.
  • Leverage our Machine Learning expertise to better understand & optimize completion designs.

Production & Operations

Optimize your production and operational performance

  • Minimize your downtime and reduce its impacts.
  • Improve your ability to hit production targets.
  • Perform more effective well reviews with integrated financial performance analysis.
  • Enhance collaboration between the field and head office.

Only VERDAZO offers Discovery Analytics

Our Discovery Analytics methodology is the most powerful approach to Oil & Gas analytics in the industry. Discovery Analytics enables a sequence of explorations, each predicated on the insights of the last. Other tools are limited by the technical and domain expertise of their creators. VERDAZO enables you to steer your analysis in whatever direction your insights take you.

Machine Learning

Advanced analytics solutions for Oil & Gas

What’s your plan to take advantage of artificial intelligence? Don’t have one? That’s a problem. We can help accelerate your use of Machine Learning to leverage the integrated datasets used across all asset life-stages. This is a new frontier in Oil & Gas analytics and we’re here to help you achieve a major competitive advantage.

Key Applications

  • Identify and quantify which inputs matter most for specific outcomes
  • Determine dependencies between model inputs
  • Develop predictive models with complex data
  • Optimize completion designs

Read industry-leading Oil & Gas analytics content

Spirit River Machine Learning Study

This machine learning study incorporates GLJ’s consistent petrophysical evaluation of the entire Spirit River play. Coupled with production and completion information, this geoscience data equips Verdazo’s machine learning team & technology to deliver a predictive model, robust interpretive visualizations, and tools that can help explain, feature by feature, the drivers of production performance for each well. This presentation provides an overview of this study and was presented at the SPE Subsurface Analytics Workshop on February 27th, 2019. If you would like to learn more about purchasing the detailed Spirit River machine learning study and predictive model click here.

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February 20, 2019 by

Brian Emmerson speaking on SPE panel on subsurface analytics

Verdazo Analytics Director of Data Science Brian Emmerson is a featured speaker at a panel on subsurface analytics at the upcoming Society for Petroleum Engineers (SPE) Subsurface Data Analytics workshop on February 27, 2019 at The Bow in Calgary. The panel, titled “An In-Depth Discussion on Subsurface Analytics,” also features Louis Fabbi of Fabi Analytics, David Fulford of Apache Corporation and Christopher Petr of CNOOC International. Verdazo Analytics President Bertrand Groulx will co-moderate the panel. The panel will explore the successes, challenges and opportunities the future of subsurface data analytics holds, including existing datasets that are underutilized in the industry and how to overcome obstacles to leverage them using new and evolving technologies. The panel takes place from 4:00-5:00 p.m. on February 26-27 at The Bow in Calgary. To register for the workshop or for more information, click here.

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February 20, 2019 by

Bertrand Groulx presenting machine learning case study at SPE workshop

Verdazo Analytics President Bertrand Groulx will present a machine learning case study at the Society for Petroleum Engineers (SPE) Subsurface Data Analytics workshop on February 27, 2019 at The Bow in Calgary. The case study utilizes GLJ Petroleum Consultants’ Spirit River regional geologic study and incorporates both geoscience and engineering data to characterize which geological, reservoir and completion data contribute most significantly to well production performance. John Hirschmiller of GLJ will join Groulx for the presentation. As part of the presentation, Groulx will outline how machine learning models provide objective, analytical means to interpret large, complex datasets. The presentation will provide interested parties with practical applications of machine learning, particularly for assessing the commercial viability of resource development, optimizing completion designs and informing reserves evaluations. Groulx’s presentation takes place from 8:00-9:30 a.m on February 27th. The SPE workshop takes place February 26-27 at The Bow in Calgary. To register or for more information, click here.

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