Matthew G. Averill

Using expert knowledge in solving the seismic inverse problem

In this talk, we analyze how expert knowledge can be used in solving the seismic inverse problem. To determine the geophysical structure of a region, we measure seismic travel times and reconstruct velocities at different depths from this data. There are several algorithms for solving this inverse problem.

How to reconstruct the original shape of a radar signal

The shape of the radar signal can provide us with the additional information about the reflecting surface. However, to decrease the noise, radars use filtering, and filtering changes the shapes of the radar signal. It is therefore necessary to reconstruct the original shape of the radar signal.

Towards Combining Probabilistic, Interval, Fuzzy Uncertainty, and Constraints: An Example Using the Inverse Problem in Geophysics

In many real-life situations, we have several types of uncertainty: measurement uncertainty can lead to probabilistic and/or interval uncertainty, expert estimates come with interval and/or fuzzy uncertainty, etc. In many situations, in addition to measurement uncertainty, we have prior knowledge coming from prior data processing and/or prior knowledge coming from prior interval constraints. In this paper, on the example of the seismic inverse problem, we show how to combine these different types of uncertainty.