As I’m writing this, it’s Earth Day! Oil and gas often get a bad rap when it comes to being stewards of our planet, and it’s not entirely unearned; but I think we can all agree that clean air and clean water are essentials.

Speaking of clean water, this week’s edition continues my series on NAWI’s funding, and I focus on the problems associated with cleaning up water for industry use. I also proudly let my Excel nerd flag fly, sharing some of my favorite tips and tricks. Hopefully, there’s a few takeaways you can pull from this edition, and it isn’t too watered down… see what I did there? 💦

Sarah Compton

Editor, Enspired

Water Innovation Series, Pt 2

Catch up fast: Last week, I introduced the water innovation series I’ll be running the next couple of weeks. Here’s how it will be structured:

1. This weeks’ contribution is going to frame the problem—a bit doom and gloom guys, I’m sorry!

2. Next week, will bring a discussion on NAWI goals.

3. Finally, we’ll get to what we geoscientists like: solutions!

Let’s jump into some of the challenges across the many dimensions of water use and reuse in E&P.

Problem 1: Extractive industries use a ton of water. We can’t operate without it.

• Volume: The NAWI report gives a super unhelpful reference that O&G operations account for 1 percent of total U.S. water withdrawals. For scale, that’s about 8,367 Olympic sized swimming pools’ worth of water … per day!

• Hydraulic fracturing: Begins with “hydraulic” for a reason. Fracturing a well requires anywhere from half a million to 11 million gallons of water per well.

Problem 2: We need to clean up the water we pull out.

Extractive industries also produce water, but that water is not the kind you’d want to take a sip of or swim in.

• Where does it come from? Some of the produced water comes from the ground, and some is water that’s been used in operations.

• Where does it go? A little over 90 percent of this produced water from oil and gas operations is reinjected, either for EOR or into SWD wells.

• Where does it come from, Cotton-Eye Joe? Just kidding 😉🎵

Problem 3: Recycled water is only useful in specific instances.

• By the time a well can produce enough water to be re-used in hydraulic fracturing operations, the hydraulic fracturing has already happened. That’s why it’s producing! There needs to be a big enough base of producing wells in proximity to old wells to effectively re-use produced water.

• Oil and gas have adjusted the chemical makeup of our fracturing water and improved our methods of cleaning it, but more work is needed.

Problem 4: Meeting demand gets tricky from a technical sense.

• Chemical detection: We need to know what’s in the water we’re using and that we’re producing—and we often need to know quickly. Regular measurement intervals might be preferable to one-time measurements.

• Is it working? We need to know how the chemical composition of the water is responding during treatment, and what the end result is.

• Location, location, location: Remote locations have different technical needs from those near municipalities. This means distribution, collection, measurements, and treatment systems for oil and gas might need to be mobile, flexible, and scalable.

The bottom line: We need water for everything, but not all water is created equal, and that creates so many problems.

What’s next: Next week, we’ll go over some goals NAWI has established to help tackle those problems, and we’ll follow-up with the paths forward to achieve those goals the following week.

Go deeper: Go here to see the NAWI road map I’m summarizing.

Tips to Excel in Your Data Analytics

Marenzo/Shutterstock.com

Recently, I needed to pull some production data to update a study that I’m giving a talk on in May, and I got to revisit my old frenemy—Excel.

History lesson: Laziness can spur great (and terrible! ←said in Olivander’s voice from Harry Potter⚡) things. Spreadsheet software started in the late-1970s because a business student didn’t want to do his calcs by hand.

Tools of the trade: Excel is the default tool for a reason.

• Formulas: Formulas aren’t just for mathemagics. By entering a little equal sign in your cell, you open a portal to powerful data analytics and transformations.

• For example, formulas can combine data based on similar traits. Want to combine production data from one spreadsheet with completion data from another? Explore the LOOKUP family of formulas. I’ve found the latest iteration to be very intuitive!

• Pivot charts: These aren’t just for finance folks! This tool is your gateway drug to other BI tools like Spotfire, Tableau, or PowerBI.

Secret weapon: Excel’s hidden gem is VBA and macros. You can use VBA to build macros that do nearly anything. VBA is not nearly as intuitive as Python, but Excel can write your macro for you.

Here’s how:

• Open Excel options: File —> More…—> Options.

• Customize your Ribbon by adding the Developer tab (check the box).

• On the Developer tab in the upper left is “Record Macro.” Click that button, and Excel writes the macro.

Shortcomings: Despite all that it brings to the table, Excel is still a spreadsheet program.

• It’s. Not. A. Database. You can’t really make a data model nor do many useful database actions with Excel. Use Access, or another database program, instead.

• Visualizations: Excel is made to run calculations. For graphics and storytelling with calculations, use BI tools.

• No big data: I have found the end of Excel, and it’s exactly 1,048,576 rows. If you’re working with even more data, you’ve got to put on your big girl pants and get into Python, R, or similar. Fortunately, a lot of that stuff is free! You just need to sacrifice a little time and sanity to learn.

The bottom line: Love it or hate it, I suspect many of you could save yourself a lot of time if you took a deeper look at the capabilities Excel presents. Dive in and free yourself from some of your mundane work!

Train yourself: Some training from Microsoft for Excel can be found here. The helpfiles in the program are also chock full of great information!

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