Oz Yilmaz is a world-renowned figure in geoscience research, with 48 years in the oil and gas business, currently chief technology officer of Houston-based GeoTomo. Best known for his definitive two-volume Seismic Data Analysis (2001) and a more recent textbook on Engineering Seismology (2015), his forthcoming book is entitled Land Seismic Case Studies. His career and writing belies a remarkable journey beginning in a small village in Turkey, son of an elementary school teacher.
Starting in Turkey, there must be a story behind your university education in the United States?
In high school, I had a geology teacher who inspired me to be curious about nature and physical geology. In the summer of 1966, after I graduated from high school, I took the government scholarship exams to study abroad. I began my undergraduate studies in geology at the University of Missouri-Rolla, but soon realized that I had to satisfy my thirst for math and physics. Thus, I had a Bachelor’s degree in geology with geophysics option. I then went to Stanford and did rock physics and earthquake seismology for my Master’s degree, and exploration seismology for my Doctoral degree.
How do you go about the process of writing a book?
First step is to draft an outline with chapter titles and section titles for each chapter. Second, for each section, I construct the individual (a), (b), (c) … elements of each figure, and compose the figures accordingly. This step does not have to be in order. Depending on the raw material at hand, I may first construct the figures for a section that is in a later chapter. Next, I write the figure captions, but rather comprehensively, incorporating as much detail as necessary. I then draft the main text for the section under consideration based on the details of the figure captions, from which details are subsequently removed. Once I finish a chapter, I write the introduction section for it. And once I finish all the chapters, I write the introduction chapter for the book.
Your book on engineering seismology has moved away from mainstream oil and gas research. Is there a reason for this?
In 2000, I decided to focus on land seismic exploration. I designed and developed a workflow-based land seismic data analysis software package for near-surface modelling and subsurface imaging. In land seismic, an important problem is to estimate an accurate velocity-depth model for the near surface for statics corrections. I therefore decided to investigate the near surface wave phenomenon in great detail. That led me to conduct numerous projects in engineering seismology for which the subject matter is the near surface. Engineering Seismology published in 2015 was the result of compiling all the research work and engineering projects I have conducted. Naturally, the next stage in my writing was to compile all the workflow-based near-surface modelling and subsurface imaging projects. This new volume Land Seismic Case Studies due out this month is for the practising geophysicists in oil and gas exploration.
For years your mantra was seismic analysis in the depth domain. Has that changed?
After years of exhausting effort, I have reached a conclusion which I express by a verse that is the preamble of the introduction chapter of the new book. My message is that the idealism of the young age has surrendered to the realism of the old age.
In an already long career, what are you most proud of so far?
I am proud of the many colleagues with whom I jointly worked on many research topics and who have inspired me and fueled my enthusiasm for earthquake seismology, engineering seismology, and exploration seismology.
Is the future healthy for students of geoscience and engineering?
While we are in the irreversible decline phase of the oil and gas exploration, there is a wide world of earthquake seismology and engineering seismology in particular, and engineering geophysics in general that includes applications of non-seismic methods. Therefore, there is much joy in pursuing a career in geophysics in the future. In this regard, it is indeed a very wise step that EAGE has taken to widen the world of geophysics by extending the society’s attention to engineering geophysics.
How convinced are you of the benefits of ‘digitalization’ in geoscientific work?
There has been a strong push to apply AI with its variants — machine learning, deep learning, convolutional neural network — to solve difficult problems in exploration seismology, thanks to the highly influential propaganda by the high-tech companies of the Silicon Valley. With regards to AI’s applicability to problems in seismic data processing, inversion, interpretation, and integration of diverse geoscience data, it is in the latter case, and to some extent in seismic interpretation that AI methods have been rather successful. Whereas, problems in processing and inversion really require natural not artificial intelligence. I base this on my experience in testing the AI algorithms for these two categories.
