VISAGE Diagnostic Workflows: Optimizing Financial Performance
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.
This is the 2nd blog in a series about VISAGE Diagnostic Workflows
Let’s face it, oil and gas producers are in the business of making money, not making oil and gas. The current market has made this a poignant reminder to the industry. That’s why we’re doing this blog series on “diagnostic workflows”, an analytic approach that helps you focus your efforts where they count the most. This week’s blog is all about Financial Performance: optimizing netback and minimizing operating expenses.
Check out last week’s blog on Optimizing Production Performance for the details about the three steps that make up a typical diagnostic workflow:
1) Identify & Prioritize
2) Inform & Assess
Analyzing Financial Data in a Rapidly Changing Market
The biggest challenge to analyzing Financial data in a rapidly changing market is “data latency”. It can take months for costs and revenues to get booked to wells … and some of those costs are annual costs.
While VISAGE has developed some advanced techniques to address these issues, I’ll focus on the diagnostic tools that leverage the data that is available … and save a more advanced discussion for a future blog.
Here are three steps that pertain to a Financial Performance Diagnostic Workflow.
1) Identify and Prioritize
The chart below shows:
- the Diagnostic Measure (on the y-axis) Netback Efficiency ($/BOE). This tells us how large our margins are per BOE produced for each well. A negative Netback/BOE represents a well that is losing money.
- the Contextual Measure is Netback Contribution ($). This tells us how important each well is in terms of its overall financial contribution to the company. The bigger the contribution, the more attention it deserves … and the greater impact an efficiency improvement will have.
- the wells (each well is a point) have been Categorized by Area, so we can gauge how each Area collectively contributes to the company and how each well (within an Area) compares to its peers.
I have identified four candidates for investigation: a high contributor, an outlier, an unlikely Netback/BOE and a large negative Netback.
2) Inform and Assess
The chart below shows that detailed Opex breakdown for the outlier. We can quickly see that following a well servicing event (red bars) the gas processing fees (green bars) have increased substantially even though Total Sales (BOE) are less than they were previous to the well servicing.
The report below provides a lower level of detail, all the way down to the minor account level. This report supports further drilldown that may ultimately result in the engagement of the accounting department to assist in investigating the increase in gas processing fees.
That concludes this week’s blog. The next blog will focus on a Variance from Production Forecast Diagnostic Workflow.
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Thanks for reading. I welcome your questions and suggestions for future blogs.
Some other blogs you may find of interest:
About VISAGE – visual analytics for the petroleum industry
VISAGE analytics software equips operators and analysts in the petroleum industry to make the most valuable and timely decisions possible. VISAGE brings together public and proprietary oil and gas data from multiple sources for easy to use interactive analysis.