Google Maps has revolutionized navigation. Most of us now have turn by turn directions right in the palm of our hands. But have you ever decided you’d rather zig instead of zag because you just preferred a different route? Or accidentally selected the wrong address and ended up in the wrong place? With any powerful software, there’s still a human element. The software is only a tool, and it’s up to the user to use that tool appropriately for their needs, to ensure that they achieve their desired end result, and arrive at the desired destination.

Starting a new project for a client is always exciting, but it’s important to slow down and consider the questions that must be asked. To ensure the project goes as planned, you should know what the desired deliverables will be and know they can be produced given the input data that is available. Asking the right questions before you start can prevent undesirable outcomes like loss of time and money due to hourly overruns required to correct errors.   

So what questions should you be asking? 

Here are the four most important questions to ask when starting a project:

  1. What is the end goal? What are the deliverables that you’re required to produce? 
  2. What data have you been given in order to produce those deliverables?
  3. What is the quality of the data you’ve been given?
  4. What are the steps that I’m going to have to take to produce the required deliverables?

By answering these questions, you’ll be clear on how you’re going to load your data, exactly what will be required, and you’ll be certain that the desired deliverables can, indeed, be produced with the input data that you’ve been given. It’s important to consider how you’re going to use the data so you know how to proceed through the project. 

Read this Case Study on successful project results from
Seven D Oil & Gas

Here are some additional things to consider when starting a project:


This includes everything that’s related to where your data is positioned on the Earth. Geospatial questions to ask include:

  1. Are my datum and my maps compatible? 
  2. Do my shapefiles match my well spots?
  3. Are my well spots correct? (Hint: We have a tool that shows you all of your bad well spots)
  4. If my data is geographical, what datum and projection is it in? (Hint: Your data must be loaded with datum and projection information)
  5. Does the data contain deviation information?

Data Source

This includes anything to do with where the data came from. 

Data Source questions to ask include:

  1. Where is my data coming from? What vendor? A colleague? Digital download? The State?
  2. What kind of geospatial information am I getting? (Shapefiles, layer files? Or Petra files, map files?)

Data Type and Quality

What types of data are included? The quality of data is often directly related to the type.

How well kept or accurate that data is will determine how much work is required and the number of hours spent. The less accurate the data is, the longer it will take to build out the project. 

Data Type and Quality questions to ask include:

  1. Have you gone through and cleaned the data? 
  2. Has the data been cleaned by someone else?

Software Proficiency 

This includes considerations about your proficiency level in the software and checking that you have the settings correct before proceeding if there are any areas where you are less confident. 

Software Proficiency questions to ask include:

  1. Do I have my scales set correctly?
  2. Have I selected the right parameters to view my data?
  3. How big are my files for import? Are the files too large?
  4. Are the file types that I’m trying to import supported?

At Neuralog, we know that Geoscience is a highly technical profession that requires careful due diligence. That’s why we’ve designed our software with a variety of built-in tools to make it easier to identify errors in bad datasets. Our file importers are simplified for ease of use to ensure that your data is imported correctly. And we don’t require vendor formats, so you can have your own ‘secret’ way of doing things and still import your data correctly.

Our goal at Neuralog is to make your experience working with our software as frictionless as possible. If you still have questions about how to ensure a successful project, contact us for more information

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