Bertrand, Author at VERDAZO

September 21, 2016 by Bertrand

Verdazo’s contribution to the Alberta Modernized Royalty Framework

October marks the early opt-in period for companies to benefit from the Alberta Modernized Royalty Framework (MRF). We thought this would be a suitable time to share some of the details about Verdazo Analytics’ contributions to the process that shaped the MRF. In early 2016 we were pleased to be asked by CAPP (Canadian Association of Petroleum Producers), and several of our clients, to contribute to the recent Alberta Oil & Gas royalty review mandated by the NDP government after its election in 2015. Our invitation to participate was based on the recognition that a critical way to ensure productive dialogue between stakeholders, particularly those with different needs and perspectives, is to start from an accurate, transparent, data-driven analysis framework. As part of our contribution to the review, we used our VERDAZO software to provide rapid analysis on a variety of potential C* scenarios and the impacts they would have on the industry and its stakeholders. It was particularly satisfying to be able to present our analyses to the panel stakeholders in an easily digestible visual form with our software. In our work with clients across the industry over the last decade, we’ve learned that being able to deliver sophisticated information visually is an...

May 18, 2016 by Bertrand

2016 Drilling Forecast & Production Impacts of Reduced Drilling

What kind of production impacts might we expect in Western Canada in 2016? To gauge this we need to forecast 2016 drilling activity, compare that to 2015 drilling activity and measure the impacts that 2015 reduced drilling had on production. My drilling activity forecast for 2016 is 3909 wells. That would be a 41% reduction from 2015 drilling activity and a 73% reduction since 2014. (Note: the 2016 forecast used the same method as my 2015 drilling forecast, which was within 4% of actual drilling results). Production Impacts of Reduced Drilling The reduction in drilling in 2015 yielded a surprising twist… the Spirit River formation added more new gas production than the Montney. The Spirit River formation accounted for 39% of new gas production in 2015 (with 246 wells coming on with gas production) ahead of the Montney which accounted for 33% of new gas production (with 304 wells coming on with gas production). The results are based on “Projected Formation” with the following formations grouped together as Spirit River: Notikewin, Falher, Wilrich and Spirit River. See www.formationfinder.com/ab/ . Gas production in WCSB exited 2015 at 18.75 bcf/day, a drop of only 2%. The 2015 production additions almost offset the 23.8% decline of pre-2015 gas production. New oil production from...

April 25, 2016 by Bertrand

Forward Curves Are a Poor Predictor of Future Spot Prices

In building a price forecast, any single indicator, including forward curves, is usually a poor predictor of future spot prices. It is important to consider a wide variety of information when building a spot price forecast. In general, all price forecasts are wrong – the goal is to be less wrong more often and have a body of supporting information to justify each forecast. In the oil and gas industry, one of the primary uses of price forecasts is to provide a reasonable basis for the valuation of oil and gas assets. These were insights I gleaned from a conversation with Tyler Schlosser, Director of Commodities Research, GLJ Petroleum Consultants. I asked Tyler about the cautions and considerations he takes when looking at Forward Curves in the process of building the GLJ price forecast. Here is what Tyler had to say: “Oil and gas futures, or forward curves, are not true spot price forecasts. In addition to market expectations of future spot prices, other factors influence futures prices. Some of these factors are: interest rates inflation expectations storage costs and availability insurance hedging effects liquidity – can the contracts be easily bought and sold at sufficient volumes? rapid speculative position accumulation...

April 7, 2016 by Bertrand

Visage Information Solutions rebrands to Verdazo Analytics

Visual data analytics pioneer in Oil & Gas plans expansion into U.S. market, other verticals under new name Calgary, Alberta — Bertrand Groulx, Co-Founder and President, today announced the rebrand of Visage Information Solutions to Verdazo Analytics. The company’s flagship product, formerly known as VISAGE, has been rebranded as VERDAZO. Verdazo Analytics provides visual data analytics software to enterprises looking to make smarter, faster decisions by revealing the hidden insights in data. The company’s new website can be found at www.verdazo.com. Visage Information Solutions was founded in Calgary in 2006 and over a decade built a client base that accounts for over half of Canada’s Oil & Gas production. The company defined the discovery analytics space for the Canadian energy industry and was recognized for its achievements with a 2011 Technology Stars award for Best Exploration Technology. The company has been widely recognized as an industry steward, pioneering the tools and techniques used for operational analyses. In 2015 nearly a quarter of a million charts and reports were run on the company’s software. “I’m especially proud of the fact that we did it all without a dedicated sales force,” said Groulx. “Our success has always been built on getting our...

April 6, 2016 by Bertrand

A decade of innovation: from VISAGE to VERDAZO

VISAGE has rebranded to VERDAZO. See the press release. How We Got Started Some technologies are designed to disrupt. Ours was designed to do the opposite. When we founded Visage Information Solutions as a two-person shop in 2006, it wasn’t because of a desire to render another technology obsolete or upend established systems in the Oil & Gas industry. It was to create visual data analytics software that could help everyone make smarter, faster decisions with the datasets they were already using. We knew there were frustrations for many business users who often spent hours a day just gathering data (before they could even start to analyze it). There was a clear unmet need. Still, we were pleasantly surprised how quickly VISAGE struck a chord with our users. When they saw the analytic capabilities it contained, and how quickly it could make a difference in their day-to-day work, they jumped onboard. The Growth Years With each passing year as our business grew, we focused on enhancing our product so every new release of VISAGE offered more specific and more relevant value. We charged everyone on our team with understanding our clients’ data analysis challenges and ensuring VISAGE addressed them. And...

March 21, 2016 by Bertrand

Type Curves Part 8: EUR, Value, Uncertainty & Auto-forecasts

Editor’s Note: While VISAGE rebranded to VERDAZO in April 2016, we haven’t changed the VISAGE name in our previous blog posts. We’re proud of our decade of work as VISAGE and that lives on within these blogs. Enjoy. The steep decline rates of multi-stage horizontal wells result in production being more heavily weighted towards the early life of the well. The point at which 50% of the well’s EUR is produced (i.e. the “Half-life” of the well) occurs at approximately 20% of the well’s life (in this Montney example). The Half-life of a well is an important measure in that it correlates strongly with the point where 80% of a well’s value has been achieved (see example chart below courtesy of Rose & Associates). That is, roughly 80% of a the well’s value will occur in the first 20% of its life. While this will vary from play to play and with well design, it does make a salient point… the bulk of the value is achieved quite quickly.This has a variety of implications. If roughly 80% of the value occurs in the first 20% of the life of a well, then value will inherently be a bigger driver for investment decisions. It...

February 15, 2016 by Bertrand

Alberta Modernized Royalty Framework: C* Winners and Losers

Editor’s Note: While VISAGE rebranded to VERDAZO in April 2016, we haven’t changed the VISAGE name in our previous blog posts. We’re proud of our decade of work as VISAGE and that lives on within these blogs. Enjoy. With recent information released about the Revenue Minus Cost (RMC) approach of the Alberta Modernized Royalty Framework (MRF), there has been much discussion within the industry about the C* capital cost calculation. At VISAGE we have been donating our time and resources to industry associations to provide analytic insights into the C* calculation. Today I will share with you my own analysis and shed some light on the plays that are likely to be winners or losers of the C* calculation. My motive is to offer statistical insight, fuel discussion and explore opportunities that may minimize unfair advantages, or disadvantages, to any particular plays, and operators. C* = a1 × (TVD) + a2 × (TVD – Vdeep) + a3 × (TVD × TLL) The C* formula calculates the Drilling and Completion Capital Cost Allowance that can be recovered during the pre-payout 5% royalty period. A nice summary can be found in the GLJ blog The Modified Royalty Framework: What We Know and Don’t Know. It...

February 8, 2016 by Bertrand

Type Curves Part 7: Survivor Bias

Editor’s Note: While VISAGE rebranded to VERDAZO in April 2016, we haven’t changed the VISAGE name in our previous blog posts. We’re proud of our decade of work as VISAGE and that lives on within these blogs. Enjoy. A common issue with Type Curves is that they are “Survivor Biased”, and can provide an unrealistic (optimistic) production outlook. Survivor Bias Definition: as depleted wells are excluded from the monthly average-production-per-well calculation, the Type Curve values are biased by the surviving wells (i.e. wells that are still producing). As such the Type Curve does not reflect the actual average production one might expect taking into account wells that are depleted (or shut-in permanently). This chart illustrates how Survivor Bias can cause latter-life production increases in a Type Curve. Few software products provide Survivor-Bias Controls that allow you to include zeros in the production average after wells are identifiably depleted. The challenge when dealing with public production data is how to identify that a well is depleted. At VISAGE we chose to use a “period of non-production” as the mechanism to identify a depleted well. The user can define the length of this period (e.g. if a well has not produced in...

February 1, 2016 by Bertrand

Type Curves Part 6: Operational/Downtime Factors on Idealized Curves

Editor’s Note: While VISAGE rebranded to VERDAZO in April 2016, we haven’t changed the VISAGE name in our previous blog posts. We’re proud of our decade of work as VISAGE and that lives on within these blogs. Enjoy. Type Curves have many complexities and can be developed to serve a variety of purposes. As such any decision maker who is using Type Curves (especially Idealized Type-well Curves) as part of any decision making process should be asking: How was this type curve developed? What does it represent? Is it being used to inform economic decisions or development plans? Yes… then has it been scaled to accurately reflect operational realities? (i.e. scaled with an Operational/Downtime Factor) There are several approaches to calculating an Operational/Downtime Factor for your Idealized Type Curve. Three example approaches include: 1) Downtime Approach This is = (Hours Producing / Hours Available). While this is an easy calculation to perform can be the least reliable. The main weaknesses are: This is not a “production-weighted” factor (e.g. if more downtime happens in the small producers, then you could be applying too large a factor to your large producers … and vice versa) The downtime percentage can vary year over year … should you apply different...

January 18, 2016 by Bertrand

Type Curves Part 5: Condensing Time (Idealized Type Curves)

Editor’s Note: While VISAGE rebranded to VERDAZO in April 2016, we haven’t changed the VISAGE name in our previous blog posts. We’re proud of our decade of work as VISAGE and that lives on within these blogs. Enjoy. A technique that is often used to compare wells or to augment the production decline profile of a well is “condensing time”. While this technique has its merits, it should be used with caution… it results in an “Idealized Type Curve” that may significantly over-represent the production (and value) you can expect from a well. You run the risk of falling short of your production targets if you don’t take into account realistic downtime expectations (I will discuss this in detail next week). This should give an even greater impetus for decision makers to ask, “How did you develop your type curve?”. The two most common techniques used to condense time include: 1) Removing Time Periods with no (or low) production; and 2) measuring production in the context of “Cumulative Producing Time”. Removing Time Periods By removing time periods with no production you are aligning producing months across the data set. While this is a good practice on Rate vs Cumulative Production charts (which do not effectively...

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