Energy. Who has it? Who needs it? Where does it come from? And how do we get more? It’s a problem for the ages. Literally.
No matter how you look at it — and everyone from engineers to entrepreneurs to environmentalists have spent countless hours examining the problem — global demand for energy continues to rise. In fact, some estimates indicate energy use will increase almost 50 percent by 2050.* Developed countries will require as much energy as ever and developing countries will need even more as they try to improve their economies and standard of living.
*“EIA projects nearly 50% increase in world energy use by 2050, led by growth in renewables,” U.S. Energy Information Administration, Oct. 7, 2021.
For petroleum and geosystems engineers who tackle this problem head on every day, the ultimate goal is this: power tomorrow by providing energy that’s affordable, sustainable and clean.
Here’s how UT PGE alumni and students are making it happen.
Doug McMaster
Of the 117 recipes Doug McMaster (BSPE 2013) made while homebound during the COVID-19 pandemic, biang biang noodles is his favorite. Named for the sound the noodles make when they’re stretched and bounced on a counter, “this dish is fun to make, pure joy to say and packed with flavor,” he says.
McMaster got interested in cooking when Professor Maša Prodanović introduced him to Modern Cuisine: The Art and Science of Cooking during his senior year. After he graduated, he took a job as a reservoir engineer with Pioneer and enrolled in culinary school, going to cooking class from 6 to 9 a.m. before heading into the office. Just as he experimented in the kitchen, McMaster worked in various parts of Pioneer’s oil and gas business — production, completions, asset development, budget and planning — before discovering a passion for data analytics.
“In oil and gas, you have to make good economic decisions, whether you have a dollar or a billion dollars. Data analysis helps you decide where to spend your money next,” he says. “Where should you locate new wells, how do you optimize existing ones, and what’s the best way to reach your decarbonization goals?”
McMaster spent two years writing software to answer those questions at Pioneer before becoming vice president of product at ComboCurve, which offers energy companies cloud-based software tools that can consider thousands of variables in a matter of minutes. His team of 75 data scientists, software developers and petroleum engineers are responsible for designing and refining ComboCurve’s data models.
It’s like a Lamborghini, he says. “Everyone wants to drive the sexy machine learning model, but nobody in the industry has the time or resources to build and improve it. That’s what we do. It’s critical to clean, organize, measure and maintain the model to keep it running at maximum efficiency.”
Maximum efficiency means maximum results — for the industry and the world. “Oil and gas has always relied heavily on data, but managing high data volumes and maintaining veracity has become increasingly difficult,” says John Eric McCarthy (BSPE 2022), who joined McMaster’s team at ComboCurve last summer. “While data analytics and AI aren’t a panacea, they’re the key to innovative software solutions that are crucial to a sustainable future.”
McCarthy and McMaster first met when ComboCurve hosted an on-campus coding workshop and sponsored UT PGE’s annual Energy AI Hackathon. Besides McCarthy, the company has hired Hyeok Kong (BSPE 2022), Travis Salomaki (BSPE 2022), and Ben Sullivan (BSPE 2020, MSBA 2022), as well as several student interns.
Exceptional petroleum engineers with solid data chops are rare, but McMaster knows the country’s No. 1 petroleum engineering program is the place to find — and mentor — them. “I always advise the PGE students I meet to be relentless about learning new things,” he says. “You’ll hit a critical mass where you can be successful and really set yourself apart” — whether it’s making scrumptious biang biang noodles or helping meet the ever-growing demand for efficient, affordable energy.
Yuanrui Zhu
When Yuanrui Zhu was accepted to the PGE PhD program in 2021, she wasn’t sure what her dissertation would be about or which professors would be a good match for her research interests. But she knew she was coming to the No. 1 petroleum engineering program in the U.S. and something good was bound to happen. Rather than wait for it, though, she turned to a hashtag. #EnergyTwitter to be exact.
Yuanrui Zhu
Through the popular hashtag, which is how top energy scientists, engineers, policy analysts, journalists and other experts communicate on social media, Zhu connected with Research Associate Professor Arvind Ravikumar before either one of them actually arrived on the Forty Acres. Zhu was in Beijing, having just completed her master’s degree in petroleum engineering from China University of Petroleum, and Ravikumar was wrapping up as an assistant professor at Harrisburg University of Science and Technology.
Fast-forward a year and a half, and Zhu is now one of six PhD students conducting research in Ravikumar’s Sustainable Energy Transitions Lab. She’s completing a first-of-its-kind geospatial life cycle analysis of the U.S. liquefied natural gas (LNG) supply chain and incorporating methane emissions measurements into the life-cycle assessment framework. When she can’t find site data, she’s traveled to the source to conduct measurements using state-of-the-art aerial systems so she can better model realistic emissions scenarios.
What she’s found so far is that methane emissions intensity varies significantly across LNG supply chains — where gas is sourced affects the carbon intensity of U.S. LNG exports. Why? Because other recent measurements across upstream production and processing stages have shown large variation: One recent study found methane leakage in the Permian Basin to be significantly higher than in the Marcellus Shale play. Ultimately, Zhu hopes to use all the data she has amassed to create a cloud-based model to track methane emissions in real time across all facilities in the U.S. LNG supply chain. Along the way, she’ll be able to compare the effectiveness of various emissions monitoring technologies like satellites, aircraft and drones.
“I’ve spent hours preparing, collecting and dealing with emissions data to be able to incorporate into our model,” says Zhu, who was selected to present her work at the American Geophysical Union fall meeting in December. “With that information combined with the emissions data from these new technologies, we can help operators find out which facilities are the biggest emitters — and how they can take action to reduce emissions and make a cleaner product.”
Sounds like Zhu is ready for an #EnergyTwitter thread of her own.
Carlos Figueroa-Díaz
Carlos Figueroa-Diaz (BSPE 2024) dims the lights in his apartment and starts his favorite Spotify playlist, heavy on the Tame Impala. He grabs a bag of trail mix and settles into a puffy gray office chair. But it’s not time to game on his PC — it’s time to work.
Figueroa-Diaz is one of seven undergraduates who participated in last summer’s SURI, UT PGE’s 10-week paid Summer Undergraduate Research Internship program that pairs selected students with faculty members conducting cutting-edge energy research. He determined which depleted or semi-depleted hydrocarbon reservoirs in the Gulf of Mexico could potentially be used to store carbon dioxide with Associate Professor Nicolas Espinoza, who collaborates with ExxonMobil, Chevron, UT Austin’s Energy Institute, the U.S. Department of Energy, and Saudi Arabia’s King Abdullah University of Science and Technology on carbon geological storage projects.
“Carbon capture is an emerging technology that is a net positive for the environment. We can take CO2 that would otherwise be going into the atmosphere and store it somewhere instead,” says Figueroa-Diaz. “The question is, where do we keep it and how do we make sure it stays there?”
To answer that question, he first looked at production data from about 30 reservoirs to figure out how much oil and gas had been produced, initially plugging data into a spreadsheet and then using Python to automate the process. Then, he used a tool called Prism to capture location data for the reservoirs. “Think Google Earth but for oil and gas,” he says.
With the production and location data cleaned and captured, Figueroa-Diaz began determining how much CO2 each reservoir could hold. After working the problem manually for a while, he eventually developed a fully automated multiple-regression-based tool that could estimate the CO2 mass density at each reservoir as a function of its pressure and temperature, and figured out how much CO2 could be stored using mass balance.
Figueroa-Diaz, who learned the bulk of his coding skills the summer after he graduated high school through an online Python course offered by MIT, had honed his skills in UT PGE’s two required data analytics courses and a handful of personal projects. “I’d been coding in Python for a good minute, but when Dr. Espinoza essentially said, ‘Turn this into a multivariate calculus project in Python,’ there were times I really didn’t think I could do it,” Diaz says. “But he just knew I could. His confidence helped me push through.”
Now, Figueroa-Diaz’s model is ready for others to build on. Next steps include adapting it to calculate the CO2 storage capacity of hybrid oil/gas reservoirs and figuring out ways to incorporate seismic and reservoir petrophysical data.
“I am a very small part in a giant network trying to turn carbon storage into reality,” Figueroa-Diaz says. “Research like what we’re doing in Dr. Espinoza’s lab is really going to move CCUS in a positive direction.”