Petrophysical inversion based on f-s-r amplitude-variation-with-offset linearization and canonical correlation analysis

Author:

Grana Dario1ORCID,Russell Brian2ORCID,Mukerji Tapan3ORCID

Affiliation:

1. University of Wyoming, Department of Geology and Geophysics, Laramie, Wyoming, USA. (corresponding author)

2. GeoSoftware, Calgary, Alberta, Canada.

3. Stanford University, Department of Energy Resources Engineering, Stanford, California, USA.

Abstract

The prediction of petrophysical properties, such as porosity and rock-fluid volumes, from partially stacked seismic data typically requires a rock-physics model that often is lithology dependent and difficult to calibrate. We adopt canonical correlation analysis (CCA) to infer the underlying relation between petrophysical properties and elastic attributes estimated from seismic data. We develop a two-step inversion approach: first, we predict elastic properties from partially stacked seismic data using a Bayesian linear inverse method based on an amplitude-variation-with-offset (AVO) linearization in terms of fluid, rigidity, and density factors, and then we predict petrophysical properties from the estimated AVO attributes using CCA. The novelty of our approach is the application of CCA to the fluid and rigidity factors, which avoids the calibration of an explicit rock-physics model by automatically deriving a linear relation in the lower dimensional space of the canonical variables. The parameterization of the linearization in terms of fluid, rigidity, and density factors maximizes the correlation with respect to the petrophysical properties of interest. Furthermore, the probabilistic approach is extended to the petrophysical inversion using Bayesian linear theory and the posterior distribution of petrophysical properties conditioned by seismic data is computed by combining the probability distributions obtained from seismic and petrophysical inversion to propagate the uncertainty from the seismic to the petrophysical domain. The inversion is validated on a synthetic case that finds high accuracy of our formulation. A case study with synthetic and real partially stacked seismic data also is presented and compared to a traditional inversion with an explicit rock-physics model.

Publisher

Society of Exploration Geophysicists

Subject

Geochemistry and Petrology,Geophysics

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