Kevin Ward, Petrosys Europe
In the oil and gas industry, I see a lot of subsurface technical maps of varying degrees of quality. The quality of these maps can differ greatly not just from company to company but often between departments. What is obvious, however, is that the great maps tend to have a top down push within the team for consistency between software applications and mapping standards.
It is a sad reality in all too many instances nevertheless that there are technical teams/individuals who are not encouraged to think about the quality of the maps they present, and which ultimately can cost the company time/effort and money!
With that in mind here are my top 5 reasons why poor maps are costing you money.
1. Aesthetic quality – making a poor first impression
Sometimes looks do matter. I saw a really poor map published in a journal a few years back. The article was actually very interesting and technically valuable to others working in this area, but I very nearly skimmed past it because the map was just a quick screenshot of a working visual display.
The map was of poor quality so my initial impression was that the entire article would be too. In the space of a few seconds the author had lost any real credibility with me.
It’s a bit like how you present yourself at a meeting. Let’s say this geoscientist had been standing up to present this article at an Oil and Gas conference or to a potential partner looking to farm into their license. Would he have presented in flowery shorts and his favourite Batman t-shirt? I’m guessing…probably not. But why not? He would still have said the same things and still have been just as capable a geoscientist.
The reason is that appearance is important for gaining credibility. People will judge you on it – even if that’s not fair!
The same data presented in a high-quality map, all labeled correctly, puts people at ease. They sit back and think “this person knows what they’re talking about and they care about their work – I can trust them”. This will help (although not guarantee 😊) you win more license applications and attract more investment into your current licenses
2. Technical accuracy – lack of knowledge and understanding
Your map should be more than just good looks- the final geological structure is important too. Probably the best (or worst!) example I can use to illustrate this was a velocity map created from about 10 wells. This map had huge bullseyes centered around each well point because the user had pressed the ‘grid’ button without knowing or caring what the algorithms were doing.
The resultant depth map, therefore, had some nice-looking prospects but they were fake and just gridding anomalies. Luckily, in this case, the anomalies were so obvious that money wasn’t wasted exploring any of these ‘highs’.
How many times however have you seen prospects, which look great, but are created or exaggerated because someone doesn’t fully understand good mapping practices?
This is also very true in faulted horizons where many users simply overlay fault polygons on an unfaulted surface but don’t consider what this structure should look like if it were to be mapped properly.
Take time to think about what your map is showing, and you’ll be respected for it when your maps are reviewed.
3. Time to create and update – rushing it all at the end
Fudge things at the end and you’ll regret it when you need to make changes. How many times have you been so pushed for a deadline/presentation that you’ve finished your map in PowerPoint or some other drawing package?
It happens regularly and I suppose if you’re pushed for a deadline you must do something, but I would urge those people to take a step back during a quieter period and consider the cost implications of doing this.
You’ve interpreted the data, you’ve displayed it on some sort of 2D visualisation canvas but before you can present you spend a reasonable amount of time (and therefore cost) in a non-technical application putting on labels to explain the data and hide/mask problems you don’t want anyone to see – in other words, you fudge it.
Now consider after the meeting someone asks for the same ‘map’ but with something changed or with some newly acquired data included etc. You’ve got to do the whole process again and any ‘time saved’ by using a non-technical application has been a false economy.
Why not, after you’ve interpreted the data, display the data live onto a high-quality map canvas? Now when you need to present you spend minimal time tweaking labels and if you ever need to refresh with new data, you push the ‘refresh’ button. Much more cost-effective.
4. Lack of clarity – leaving others to make ‘assumptions’ about your work
A good map should be a standalone representation of your knowledge of a surface or area. Poor maps don’t do this and you either have to spend time (and again cost) explaining what you meant in detail or, in your absence, your colleagues need to discuss what they think is going on, adding unnecessary risk to decisions and let’s face it, not winning you any friends.
An easy example of this is something as simple as not having labels – if no legend is provided assumptions must be made about symbols on the map. Or, a more technical example such as no raw data displayed means assumptions are made about where the technically validated areas of good control are, versus your ‘best estimates’ as to the likely structure in areas of poor data control.
And we all know what happens when people ‘assume’…
5. Lack of consistency – everyone is doing their own thing
One software package and mapping standard can and should fit all. It is very common in teams where no direction from higher up is given as to best mapping practices for different mapping packages and techniques to be used, resulting in maps generated to varying degrees of quality with different standards.
There’s no correct standard for mapping but guidelines around which software to use and the standard layout of a map should be given.
Take the initiative, bring it up at a meeting and become the ‘mapping standards’ champion. You’ll be respected for improving efficiency and quality.
With standard layouts created, each member of the team can then display their data onto a template canvas which not only makes the cost of producing each map cheaper, but it also saves time deciphering over what colour is high/low, what the contour increment is, which way is north, etc.
Major time saver. Major cost saver.
What do you think? Are there other reasons why mapping quality improves the finances of an oil and gas company? Or do you disagree? Perhaps you feel it’s not worth the extra effort?