Interrogating Subsurface Structures using Probabilistic Tomography: an
example assessing the volume of Irish Sea basins
Abstract
The ultimate goal of a scientific investigation is usually to find
answers to specific, often low-dimensional questions: what is the size
of a subsurface body? Does a hypothesised subsurface feature exist?
Existing information is reviewed, an experiment is designed and
performed to acquire new data, and the most likely answer is estimated.
Typically the answer is interpreted from geological and geophysical data
or models, but is biased because only one particular forward function is
considered, one inversion method is applied, and because human
interpretation is a biased process. Interrogation theory provides a
systematic way to answer specific questions by combining forward,
design, inverse and decision theories. The optimal answer is made more
robust since it balances multiple possible forward models, inverse
algorithms and model parametrizations, probabilistically. In a synthetic
test, we evaluate the area of a low-velocity anomaly by interrogating
Bayesian tomographic results. By combining the effect of four inversion
algorithms, the optimal answer is very close to the true answer, even on
a coarsely gridded parametrisation. In a field data test, we evaluate
the volume of the East Irish Sea basins using 3D shear wave speed depth
inversion results. This example shows that interrogation theory provides
a useful way to answer realistic questions about the Earth. A key
revelation is that while the majority of computation may be spent
solving inverse problem, much of the skill and effort involved in
answering questions may be spent defining and calculating those target
function values in a clear and unbiased manner.