Episode 307: How QI Connects Science and Business Impact
“Machine learning over the last few years has become revolutionary. But we still need, and maybe even more so, the constraint and knowledge of rock physics and QI as an integral part of those workflows.”
Stephan Gelinsky describes quantitative interpretation as the place “where science meets business impact.” That idea anchors this conversation with Stephan and Per Avseth, built around the May quantitative interpretation special section of The Leading Edge.
Elastic FWI and machine learning are moving quickly into QI, but both guests argue that better algorithms make rock physics, geology, and judgment more important, not less.
Per also points to a broader challenge. Some students are turning away from reservoir geophysics because they associate it with petroleum, even though the same science is needed for CCS, geothermal, critical minerals, natural hydrogen, and other subsurface problems tied to the energy transition.
The question is not whether QI still matters. It is how the field keeps its physics, communicates uncertainty, and shows the next generation where that science can take them.