Joseph Stefani
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| Latest company | Chevron Energy Technology |
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Joe Stefani received degrees in Engineering and Geophysics from the University of California and Stanford. He has worked for Chevron Energy Technology Company since 1984 and has been involved in a range of geophysical R&D: high-fidelity Earth and seismic modeling, acquisition, anisotropy, inversion, and general Aki and Richards stuff. Most recently he has helped build the SEG SEAM Phase 1 and Phase 2 Earth models. Joe served as the SEG/AAPG Distinguished Lecturer in 2013.
Fall 2013 AAPG/SEG Distinguished Lecturer
The Earth is cleverer than you are — Learnings in earth and seismic modeling, and applications of FD modeling to rock physics and geomechanics
Earth modeling, from the construction of subsurface structure and stratigraphy, to the accurate understanding of rock physics, through the simulation of seismic and nonseismic responses, is an enabling technology to guide decisions in acquisition, processing, imaging, inversion and reservoir property inference, for both static and time-lapse understanding. So it is crucial to capture those Earth elements that most influence the geophysical phenomena we seek to study. This is notoriously difficult, probably because we regularly underestimate how clever the Earth can be in producing various geophysical phenomena.
The main part of the talk focuses on methods we have used in building complex Earth models (both overburden and reservoirs) and their seismic simulations, emphasizing the challenge to reproduce the appropriate features observed in real data. Questions to consider are the quality of the seismic data that will act as a guide in the model building, and that of the well logs used to quantify the rock physics. Another consideration is the amount of physics to include in the geophysical response simulation, which is a tradeoff between computational load and acceptable characterization of the data features.
Finally, the industry workhorse for seismic modeling continues to be the time-domain finite-difference (FD) algorithm, mainly because of its balance between accuracy and efficiency, simple concept and gridding, and ease of programming on various hardware platforms. Because of this simplicity, and the growing interest in time-lapse and geomechanical problems, a short treatment is included of how FD modeling can be adapted to problems in rock physics and geomechanics from core to basin scales.
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