One of the emerging technologies in geophysics is the stochastic inversion of geophysical data for the prediction of rock and fluid properties. The probability distribution of the geophysical properties of interest can be computed using a probabilistic inverse method. The integration of stochastic inverse methods and geophysical modeling allows generating multiple reservoir models of rock and fluid properties that honor the geophysical measurements. Stochastic approaches allow sampling multiple solutions from the posterior distribution of the model parameters and quantifying the uncertainty in the model parameter predictions. Stochastic inversion algorithms can be applied to seismic inversion problems as well as petrophysical inversion problems. In this work, we discuss analytical and numerical approaches, as well as their advantages and disadvantages.
Presentation Date: Monday, September 25, 2017
Start Time: 1:50 PM
Location: 381A
Presentation Type: ORAL
