There’s 3 big questions every oil company of every size should be able to answer:
“How much oil/income did I make?” “Which wells are making money?” and “What am I spending my money on?”. To answer each those questions I’ve spent countless hours logging into separate systems, exporting bits of data, combining all that data into a spreadsheet, and QC’ing that data before I could even begin to answer just one of those questions. Better tools like the ones we’ve built at the links above make it possible to spend more time finding answers and less time wrestling with data.
Many a morning, in my Sisyphean days optimizing waterfloods I’d pull yesterday’s production for the hundreds of wells I was responsible for, then pull that same production a week before yesterday, match them up, subtract one from the other, sort by the difference, and then start going through the biggest changes to try and explain ‘why?’. Well X dropped sharply Tuesday – “OK, why is that?”. Was there a well test? Did one of the other wells in that tank battery get a well test? Shoot, which wells are in that tank battery, let me go look up which 16 producers flow into it. I don’t see downtime for this well, maybe some of the other wells went down or kicked back on and the allocation engine misattributed the change to this producer. If none of those things, then what I’m seeing is real, and only now can I start diagnosing the issue. Time to go look at WellView and see if the lease operator entered a note…
I still have nightmares about that waterflood.
At the time, the best tool available to me was Landmark’s DSS 5000 (shudder…). I probably spent 80% of any given day trying to convince myself that what I was seeing was the result of the reservoir, completion, or wellbore and not a ghost in the data. The tools available back then were not what they are today, and I have the thinning hair to prove it!
For repeated workflows like route reviews and asset surveillance, Business Intelligence tools mean answering a question once effectively answers that same question almost instantly in the future. Spotfire and Power BI users know that spending a little more time up front building connections to each of the systems makes it possible to build reports that remain evergreen and are easy to share. Your production system probably already a table with historical well tests, lease operator comments, and downtime history. By writing a formula to calculate week over week production changes and using filters to flip from route to route the exercise above could take an hour instead of a morning. Because the tools are cloud based, data is easy to share across departments. Data refresh happens while you sleep, and with the reserves data in the data warehouse you can compare production actuals vs forecast too. If you can connect to accounting data you could calculate whether a well is even economic to spend time on in the first place!
It’s taken a while to publish one of the many Production reports that we’ve built, but we wanted to be able to show off one that leverages all the things we’ve learned in the last two years working in data management and analytics. I love talking about this stuff, so drop me a line if you want to chat about your own report, ask about how to stand up a data warehouse, or best practices on setting up your data model. If you want to play with an interactive version of our production report, you can do so on our website right now!