CMG Research: Statistical Seismic Imaging
|Faculty Investigators:||Alan Levander
|Post Doctoral Investigator:||Fuchun Gao|
|Former Post Doctoral Investigator:||Christian Poppeliers|
|Graduate Students:||Oksana Korostyshevskaya
|Funding Source:||National Science Foundation|
Using reflected seismic waves to image the Earth is a powerful technique to infer the structure of the Earth's crust. At the largest scale, deep crustal reflection seismology can reveal a great deal structure of the crystalline crust to depths of up to 40 kilometers. Conversely, high-resolution reflection seismology for civil and environmental engineering applications can reveal complexity in the first few meters of the Earth's surface. And argueably the most important consumer of seismic imaging technology is the petroleum industry, which routinely produces spectacular images of the first few kilometers of the Earth's sedimentary crust.
The current reflection seismology techniques rely on the assumed properties of consolidated sediments and seismic waves in them (e.g. the tendency to large scale layering of sedimentary structures and the preponderance of singly scattered energy in the seismic data). These properties favor deterministic imaging of Earth structures: in other words, specific targets can be precisely delineated. However, neither the deep crystalline crust nor the near-Earth surface conforms to the basic assumptions required for deterministic seismic imaging. Furthermore, it is often inappropriate or impractical to interpret a deterministic image of the crystalline crust or near surface. Often the overall statistical character of these regions is a more revealing property.
In this project, we combine expertise from the areas of mathematics, statistics, geophysics, and digital signal processing to contribute to the foundations of a new seismic imaging technique collectively termed statistical seismic imaging. The ultimate goal of this project is to develop techniques to extract statistical properties of the Earth from the reflected wavefield. To this end we (1) make extensive use of numerical simulation of the Earth and seismic waves in it and (2) develop inverse methods used to calculate effective statistical properties in the Earth.