For Jef Caers, mother knows best
Mom’s understated observation that her sports-minded teen was “very curious and not bad at math” led to a career in engineering. One of the pioneers of multi-point geostatistics, Caers recently scored three big wins in 2014, including promotion to full pr
When Jef Caers was 18 years old, he told his mother he wanted to pursue a career in physical education because he loved being outdoors and active. The lanky Belgium teenager was passionate about basketball, cycling and running, and saw sports as his future.
His mother's response surprised him. ”No, that’s not what you’re going to do,” she said. “You're going to do engineering, because you're very curious and you're not bad at math.’”
The young Caers knew nothing about engineering. "I had to look it up," he recalled.
Looking back, it’s pretty obvious that his mother knew best. Today Caers is a recognized expert in the relatively new branch of mathematics called geostatistics, which is particularly useful for characterizing the flow of subsurface oil, gas, and water. "When you’re a teenager, I think your parents know you much better than you know yourself," he said. Following his mother's advice, Caers majored in engineering at Katholieke Universiteit Leuven in Belgium and immersed himself in computer science, mathematics, physics and chemistry. In graduate school, Caers chose to specialize in mining engineering. "I wasn't particularly interested in mining," he said, "but it involved geology, which I thought was interesting."
For his PhD thesis project, Caers calculated the value of diamond deposits in Africa, using a rare trove of data provided by a colleague about the worth of different gem sizes gathered from various drill sites. “Very few people had access to this data because it was very closely held by one company," Caers said.
To calculate the value of diamond deposits based on a few drill samples, Caers had to develop a new kind of statistics. "The techniques that were out there just didn't work," he said. "Most traditional techniques are based on the central limit theorem, which states that if you have a lot of data, things will cluster around the average. But that's only true under certain circumstances. In these very organized systems that we study in the subsurface, or things like diamonds which have very long-tailed distributions, the average often doesn't exist or has little meaning."
Caers' novel statistical technique caught the attention of geostatistican Andre Journel, who invited him to continue his research at Stanford University. Journel, now the Donald and Donald M. Steel Professor of Earth Sciences Emeritus, was professor of Petroleum Engineering and Geological & Environmental Sciences at the time. Caers had only been to the United States once before, and wasn't even sure where Stanford was. "I had to look it up on a map,” he said. “Then I thought 'Oh California, that I've heard of.’" It didn’t seem like a bad place for an active sportsman to settle.
Caers arrived at Stanford in 1997 as a postdoctoral researcher and has never left. The next year, at the age of 28, he was hired as an assistant professor of Petroleum Engineering in the School of Earth Sciences and then promoted to associate professor of Energy Resources Engineering (ERE) in 2006. Caers was made a full professor in ERE earlier this year. He was also named the 2014 Krumbein Medalist of the International Association for Mathematical Geosciences. Caers is especially proud of the medal, which is typically awarded to senior scientists for career achievement.
The Krumbein Medal is an example of one of Caers’ favorite aspects about the United States. “In the United States, you’re valued based on your merit. If you do good work, and you want to take a leadership and responsibility role, you can,” he said. This was made especially clear to him in 1998, while he was considering the job offer at Stanford to become an assistant professor. “I went back home to Belgium, and I told a university there about the opportunity at Stanford. I said I wasn’t sure,” Caers recalled. “I asked the other university if they would consider giving me a job. They said they would hire me–but in nine years. “ That left Caers with an easy decision.
At Stanford, Caers continued to refine the mathematical tool that he first developed nearly 20 years ago to evaluate diamond deposits in Africa, called multi-point geostatistics. Caers is the author of three books, his latest published with Wiley-Blackwell in 2014 and titled Multiple-point Geostatistics: stochastic modeling with training images.
At its core, multi-point geostatistics involves calculating spatial uncertainty based on limited data. "A lot of people like to 'chase' the true answer,” Caers said. “But what we should actually be more interested in is uncertainty, because uncertainty will tell us about risk. For example, we don't know for certain what the climate is going to be like in 50 years. It's the same with the subsurface. If I drill here, what is the oil recovery factor going to be? It's not certain. My research focuses on assessing and managing that uncertainty."
Rather than generating one likely answer, multi-point geostatistics generates alternatives that could represent the truth. "If a company is investing tens of millions or even a billion dollars to drill a new well, I can evaluate the probability of getting a return,” Caers said.
Caers also co-directs the Stanford Center for Reservoir Forecasting (SCRF) with ERE and Geophysics professor Tapan Mukerji and along with Alexandre Boucher, currently a consulting professor in ERE, has developed an open-source, industrial-grade software package, called SGEMS, that Caers hopes will encourage scientists and engineers to apply multi-point geostatistical methods to their particular subjects. So far, it seems to be working. Caers has seen a spike in recent years in the application of his technique for addressing problems in various fields, ranging from petroleum, natural gas and mineral recovery to groundwater and soil modeling, carbon sequestration and even finance.
Caers says that his own life is a good example of what can come from embracing uncertainty. "If I think back to when I was 18 and I look at where I am at now," he said, "I would never have guessed the path that my life has taken."
Ker Than is the associate director of communications for the School of Earth Sciences.