Senior Geophysical Consultant
Andrey Bakulin is a Senior Geophysical Consultant at Saudi Aramco's EXPEC Advanced Research Center in Dhahran. He holds a Ph.D. in geophysics from St. Petersburg State University of Russia. Andrey had a brief academic career at St. Petersburg State University and the Colorado School of Mines and contributed to setting foundations for quantitative seismic fracture characterization using seismic anisotropy with the key Geophysics paper “Estimation of fracture parameters from reflection seismic data” cited more than 700 times. Andrey joined the industry in 1999 and worked at Schlumberger Cambridge Research, Shell Bellaire Technology Center, and WesternGeco. He co-developed the Virtual Source Method as the first industrial application of seismic interferometry. He deployed practical methods for estimating anisotropy from seismic and designed rock physics transforms to characterize fractures and 3D stresses from seismic anisotropy. He pioneered localized tomography with borehole data remains the primary method of deriving anisotropic parameters for velocity model building. Since 2010 he has worked at EXPEC ARC of Saudi Aramco. Currently, he leads the focus area for Data Acquisition and Robotization. His most recent achievements include solving near-surface scattering noise challenge, making 3D seismic survey design transparent to interpreters, successful permanent seismic monitoring of land carbonates with buried receivers, and developing seismic and uphole acquisition with Distributed Acoustic Sensing. He served SEG in various roles, including the 2011 Spring Distinguished Lecturer on a Virtual Source. He is frequently recognized as a top presenter at SEG and won two Best Paper at SEG awards. He has numerous professional awards, with the latest including the 2019 Conrad Schlumberger Medal from EAGE for “solving problems that impact data quality and efficiency”.
May 30
Land seismic is inherently more complex than marine, even more so in arid desert environments. Geophysical techniques proven in a desert environment would ace everywhere else. Monitoring in a desert environment is extremely challenging due to shifting sand dunes and seasonal changes. First, I will walk you through actual field feasibility results with various source-receiver configurations. Then, picking the winner of hybrid acquisition with buried receivers and surface source, we dive into a 3D case study of monitoring CO2 injection in a carbonate land reservoir. I show how fantastic marine-like repeatability of 4% NRMS (Normalized Root-Mean Square error) can be achieved in complex desert environments when surveys are done in the same season. Scaling up such monitoring to more extensive areas demands Distributed Acoustic Sensing (DAS) to optimize instrumentation costs. I show a deep seismic imaging field demonstration using shallow DAS vertical arrays and compare it to conventional 2D surface seismic. I conclude by explaining how DAS antennas can decrease the density of the monitoring array, thus providing a robust system for monitoring mass-scale CO2 sequestration.
