Over the last decade, the collective impact of changes in production technologies, the shift in commodity prices and a reduced workforce is defining a ‘new normal’ in oil & gas. This presentation provides a visual overview of evolving production and market trends and explores the role data and technology will play as the industry adapts to its changed landscape. “Visual Analytics in the New Normal: Past, Present & Future” was originally presented as part of the geoLOGIC Adapting to the New Normal technical showcase on Nov. 16th, 2017.
Production forecasts derived from Type-well Curves are typically based on limited data. Our desire to predict the production performance of recent wells with limited data introduces uncertainty that is difficult to quantify. There is also an industry tendency to rely on early predictors like IP90 as a comparative measure of well performance. This study includes a look-back involving more than 87,000 forecasts (Montney and Viking wells) to see how much data you need for an 80% confidence interval. It also compares how much data you need from both a Volumes(Reserves) and Value perspective.
The use of Type-well Curves for Development Planning has many uncertainties. Not adequately taking these uncertainties into account can result in statistically unachievable expectations. Failure to meet production expectations can have drastic stock market consequences on share value. This presentation provides guidance about the uncertainties that need to be considered and how Aggregation Curve approaches can help you better plan for statistically achievable results.
In the Kakwa area of the Montney there has been a recent trend away from the use of nitrogen as an energizer in the completion of horizontal multi-stage fractures. This presentation explores the effectiveness of this trend, specifically examining the production performance, cost implications and economics of the use of nitrogen in the area, and considers the uncertainty associated with drawing early conclusions.
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.
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.
Our Oil & Gas clients continue to emphasize an increasingly acute need to do things smarter, simpler and more cost-effectively across their organizations. That’s one of the reasons why VERDAZO has been effective for them: it enhances their analytical capability and capacity no matter their economic constraints. This is important for any producer where the order of financial magnitude of a decision can be in the multi-millions of dollars. However, it may be even more critical for junior companies who often walk a thin financial line on the way to full capitalization and initial production. When Calgary-based Burgess Creek Exploration was founded in 2015, VERDAZO was its very first purchase.
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 effective way to build a data-driven consensus on the best course of action. Here at Verdazo Analytics, we’re very proud of the final outputs of the royalty review and thank CAPP (Canadian Association of Petroleum Producers) for including us in the process.
The start of a new year is often accompanied by commitments for change and improvement, both business and personal. We’re all striving to innovate, “to introduce something new; make changes in anything established”. In business, this often involves technology. How you approach the introduction of technology could be the difference between realizing true innovation or ending up with a “Dishwashing Robot”.
A friend introduced me to the expression “Dishwashing Robot” as a way of describing what happens when you apply new technology to an old way of doing things. It seems innovative on the surface, but it doesn’t bring true, impactful change to an organization. “Innovation” (e.g. a dishwasher) occurs when you leverage the full potential of new technology to change a process and realize optimal benefits. So my challenge to you, and myself, is to consider how we can change processes in our organizations to maximize the benefits of any new technologies we introduce.
I have to admit right from the start: I am not what anyone would call a neutral observer on this topic. After all, I run a company that builds and sells visual analytics software. I’ve done so for over a decade. It’s in my interest that someone – you, perhaps – be interested in buying that software. I come to these biases honestly and I state them upfront.
Like many senior leaders and executives out there, I’m also trying to do more with less. I want to achieve my business goals with only the most calculated investments. I’m trying to deliver value as quickly as possible and make sustainable choices that will serve my company, and my clients, well over the years to come.
The last week of September had me doing three industry presentations that all shared a common theme, “uncertainty”. Today’s blog will focus on the presentation Uncertainty Considerations for Development Planning Type Curves.
Uncertainty extends through the reservoir, drilling, completions & operations and is compounded by commodity prices. What is certain is that shareholders have little tolerance for production shortfalls. The following image show the reduction in stock price of 8 companies in 2017 that occurred following the announcement of production shortfalls.
Figure 1: Stock price reactions to production shortfalls
I could have easily showed you several companies who hit their production targets and maintained or increased their stock price. While it’s not important to know who these companies are, it is important to know that there are best practices that can help protect you from targeting statistically unachievable results and falling short of your production promises.
I recently read the article Same Stats, Different Graphs which spoke about Anscome’s Quartet, four highly varied datasets that are identical when examined using summary statistics, then took it to the next level with the Datasaurus Dozen by demonstrating how highly varied datasets could produce the same summary statistics.
Datasaurus Datasource: Alberta Cairo
Explore public data. Identify business opportunities by discovering insights into companies, plays and completion technologies.
Analyze your accounting data. Optimize financial performance by identifying operating cost issues and revenue opportunities.