Identifier
etd-11122008-144747
Degree
Doctor of Philosophy (PhD)
Department
Petroleum Engineering
Document Type
Dissertation
Abstract
Reservoir architecture may be inferred from analogs and geologic concepts, seismic surveys, and well data. Stochastically inverted seismic data are uninformative about meter-scale features, but aid downscaling by constraining coarse-scale interval properties such as total thickness and average porosity. Well data reveal detailed facies and vertical trends (and may indicate lateral trends), but cannot specify intrawell stratal geometry. Consistent geomodels can be generated for flow simulation by systematically considering the precision and density of different data. Because seismic inversion, conceptual stacking, and lateral variability of the facies are uncertain, stochastic ensembles of geomodels are needed to capture variability.
In this research, geomodels integrate stochastic seismic inversions. At each trace, constraints represent means and variances for the inexact constraint algorithms, or can be posed as exact constraints. These models also include stratigraphy (a stacking framework from prior geomodels), well data (core and wireline logs to constrain meter-scale structure at the wells), and geostatistics (for correlated variability). These elements are combined in a Bayesian framework.
This geomodeling process creates prior models with plausible bedding geometries and facies successions. These prior models of stacking are updated, using well and seismic data to generate the posterior model. Markov Chain Monte Carlo methods sample the posteriors. Plausible subseismic features are introduced into flow models, whilst avoiding overtuning to seismic data or conceptual geologic models. Fully integrated cornerpoint flow models are created, and methods for screening and simulation studies are discussed. The updating constraints on total thickness and average porosity need not be from a seismic survey: any spatially dense estimates of these properties may be used.
Date
2008
Document Availability at the Time of Submission
Release the entire work immediately for access worldwide.
Recommended Citation
Kalla, Subhash, "Reservoir characterization using seismic inversion data" (2008). LSU Doctoral Dissertations. 1310.
https://repository.lsu.edu/gradschool_dissertations/1310
Committee Chair
White, Christopher D
DOI
10.31390/gradschool_dissertations.1310