Blog
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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July 22, 2018 by

Data before delivery: putting the cart before the horse?

I have now heard dozens of stories from friends and colleagues about failed BI and analytics initiatives. They range in costs from hundreds of thousands to tens of millions of dollars. It’s a problem that I see several companies at risk of repeating…and the motivation for today’s blog. A common thread to most of these stories is trying to “fix up our data before we select or implement an analytics tool”. How can anyone possibly understand the data needs, the use cases, and the possible data issues without providing a means to use the data, view the data and identify issues? It’s like trying to anticipate what part of a car a mechanic should fix without test driving it first. Consider starting with the data you have, take it for a test drive. See how the business wants to use it and evolve your data quality and architectural initiatives incrementally. You’ll realize value on the way and better focus your efforts. Why do they fail? Lack of focus: Hyped up terms like “big data”, “data lakes” and “cloud” distract us from the pragmatic task of delivering information ­­­— getting reliable, current information into the hands of business users in a form...

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Presentations

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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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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Client Stories

Producer uncovers millions in operational improvements while establishing visual analytics culture

One of our favourite things is when our clients are able to get more value out of VERDAZO than they originally expected. We love watching visual analytics cultures take hold, as one project inspires another and users across organizations discover new uses for our product. At one intermediate Canadian producer, a project focused on minimizing downtime yielded a $12 million operational improvement on just a single group of wells. But that was just the start of what they did with VERDAZO. Here’s their story.

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How a producer started its analytics journey

A producer in Calgary used our VERDAZO software as part of an initiative to improve their Well Review process. Their results went beyond their expectations: they were able to free up their engineers from days of manual Excel analysis in advance of a well review, saving time that exceeded $175,000 in annual costs. That initial project also spawned something the producer couldn’t have initially predicted: a commitment to analytics that eventually spread across the organization. New projects were created and an analytical culture took hold as the producer uncovered new efficiencies and value in unexpected places.

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Product Infosheets

Machine Learning

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

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Public Data

Explore public data. Identify business opportunities by discovering insights into companies, plays and completion technologies.

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Financial Data

Analyze your accounting data. Optimize financial performance by identifying operating cost issues and revenue opportunities.

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