Luis Canales

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Luis Canales
Luis L. Canales headshot.png
Latest company Geophysics Department at Stanford University
BSc Civil Engineering
MSc Geophysics
PhD Geophysics
BSc university University of Mexico

Biography Citation for the Reginald Fessenden Medal

Contributed by Oz Yilmaz

Seismic data processing is aimed at increasing vertical and lateral resolution. We apply techniques to enhance reflection energy contained in recorded data by way of estimating and removing source waveform, and by attenuating random noise, coherent linear noise, and multiples. Ultimately we obtain an accurate image of the subsurface.

During the last two decades, significant advances were made in the analysis of reflection seismic data. And they did not come easily. In exploration geophysics, as in many other applied sciences, many ideas are tossed around but only a few find their way into practical use. Luis Canales has played a significant role in transforming theoretical concepts in data analysis into practical schemes which made a difference in the quality of the results we get from processing.

Luis Canales invented in 1984 a technique for attenuation of spatially random noise on seismic data. Since then, it has become an integral part of the seismic data processing sequence. The technique involves designing and applying a complex Wiener prediction filter in the space-frequency domain. It can be applied to common offset, moveout-corrected, common midpoint, or CMP stacked data, as well as 3-D seismic data. Moreover, the foundation theory of linear uncorrelated noise attenuation (LUNA) has inspired several researchers who have extended it to other applications, including multiple attenuation, trace interpolation, and missing data restoration.

Luis had an affinity for mathematics early in his education. Thanks to his father, though, he received a B.S. degree in civil engineering from National University of Mexico in 1970. His master's research was primarily in rock physics and earthquake seismology. Specifically, he studied earthquake mechanisms by way of modeling stress-slip relations for three-dimensional faults. He applied results of his theoretical work to some historical earthquakes from North and South America.

During his work towards his Ph.D., he combined earthquake seismology and rock physics with exploration seismology. Specifically, he became keenly interested in developing numerical solutions to problems in reflection seismology. Among his early works are I.1 norm spectral estimation and wavelet estimation. At the end of his graduate studies at Stanford, he became affiliated with the Stanford Exploration Project and continued making contributions in applying signal processing techniques to reflection seismic data.

Luis returned to Mexico in the fall of 1975 to become associate professor and head of the Computer Center at the Center for Scientific Research and Graduate Studies of Ensenada in Baja, California. During the next five years at the research lab, he maintained his close association with the Stanford Exploration Project.

At the end of the 1970s, Luis decided to pursue his passion for applied mathematics entirely in the expanding field of exploration seismology. It was the age of applying numerically efficient schemes to a wide range of problems in exploration seismology from deconvolution and wavelet estimation to noise and multiple attenuation, velocity analysis, and migration. He began his career in the oil industry with Mobil Research Laboratory in Dallas in 1979 as a research geophysicist working on traveltime and amplitude inversion.

In 1981, he joined Digicon Geophysical in England as a senior research geologist and worked on a wide variety of problems in seismic data processing. A few years later, he became director of a special projects group at Digicon. It was then that he invented LUNA, now recognized by the Society as a significant contribution to the analysis of seismic data. Today, this technique is applied to more than half the recorded data at some stage in processing. He developed a technique for stable estimation of source waveforms based on Burg's algorithm for spectral estimation. This technique proved to be successful for difficult land and transition-zone data. Luis also developed novel stacking techniques applicable to data with low signal-to-noise ratio.

Shortly after returning to the United States, Luis became a research associate in the Geophysics Department at Stanford University in 1990. He was able to conduct research in rock physics, crosshole tomography, as well as analysis of surface seismic data. Finally, he joined Cogniseis Development as vice president for research and development in 1994. He continues to produce efficient and accurate algorithms for processing seismic data specifically for trace interpolation, deconvolution, multiple attenuation, and migration.

People in science and technology have strengths of one type or another. One may have built up an immense theoretical knowledge base in a field of interest, but may often find it difficult to transcribe that knowledge to solve practical problems. Conversely, one may have gut feelings for practical problems, but may often find it difficult to formalize the problem and set it on a sound theoretical foundation. Luis is that rare individual who has the combination of strengths in broad and in-depth theoretical knowledge, and the ability to synthesize a practical solution to a problem. He is not only interested in solving problems in seismic data analysis, but also solving them using efficient algorithms. Luis accomplishes this through his extensive knowledge in computer architectures.

Luis is a distinguished scientist, not just for his strength in theory and his ability to form a practical solution to a problem, but also for his marvelous human character. He is most approachable, modest, and open to discussing a topic. I am most delighted to write this citation on behalf of the Society for a wonderful and dear friend. For all his contributions, most specifically for LUNA, we honor Luis Canales most appropriately with the Reginald Fessenden Award.