Blog
March 2, 2020 by

The White Elephant in The Room

The title of this blog combines two concepts. A white elephant is a possession whose cost to dispose of, is out of proportion to its usefulness. The elephant in the room is a metaphorical idiom for an important topic, problem, or risk that that everyone knows about but no one wants to discuss because it makes at least some of them uncomfortable. With this explanation in place let’s ask a question. Question: “What produces 1.1 trillion litres of water per year in order to extract a marketable commodity?” Hint: 5.4 barrels of water are produced for every $50 worth of this marketable commodity. Answer: Canada’s Petroleum Industry. Some might say this is a water industry with a petroleum by-product. For over 20 years in this industry I have been aware of water produced in conjunction with oil & gas, of increases in water cut as wells mature, and the significant percentage of operating costs that trucking and disposal represents. However, I didn’t appreciate the magnitude of produced water that the industry contends with… until now. Produced water is water that is co-produced with petroleum products from a reservoir at significant depth. Produced water is non-potable water, saline, and often contains undesirable...

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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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Presentations

Machine Learning: Usability, Stability & Interpretability

Machine learning in the Oil & Gas industry has met with varied success and no shortage of hype.  Barriers to success in the industry include data challenges, inflated expectations, and a lack of trust from those who stand to benefit from its results.  In this presentation, we will be showing the bulk of our Spirit River Study from the SPE Subsurface Workshop, plus a whole lot more.  We will explore trust-building approaches that include feature selection, interpretive visualizations, stability considerations, “What’s a good R2?”, and a Man vs Machine simulation.  In the simulation, we compare traditional type-curve generation approaches with those based on machine learning models, using data from the Marcellus.

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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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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

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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Production Data

Analyze your production data. Optimize production performance, minimize downtime and improve your ability to hit production targets.

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