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Probabilistic inversion of seismic data for reservoir petrophysical characterization; review and examples

Dario Grana, Leonardo Azevedo, Leandro de Figueiredo, Patrick Connolly and Tapan Mukerji
Probabilistic inversion of seismic data for reservoir petrophysical characterization; review and examples
Geophysics (October 2022) 87 (5): M199-M216

Abstract

The physics that describes the seismic response of an interval of saturated porous rocks with known petrophysical properties is relatively well understood and includes rock physics, petrophysics, and wave propagation models. The main goal of seismic reservoir characterization is to predict the rock and fluid properties given a set of seismic measurements by combining geophysical models and mathematical methods. This modeling challenge is generally formulated as an inverse problem. The most common geophysical inverse problem is the seismic (or elastic) inversion, i.e., the estimation of elastic properties, such as seismic velocities or impedances, from seismic amplitudes and traveltimes. The estimation of petrophysical properties, such as porosity, lithology, and fluid saturations, also can be formulated as an inverse problem and is generally referred to as rock-physics (or petrophysical) inversion. Several deterministic and probabilistic methods can be applied to solve seismic inversion problems. Deterministic algorithms predict a single solution, which is a "best" estimate or the most likely value of the model variables of interest. In probabilistic algorithms, on the other hand, the solution is the probability distribution of the model variables of interest, which can be expressed as a conditional probability density function or a set of model realizations conditioned on the data. The probabilistic approach provides a quantification of the uncertainty of the solution in addition to the most likely model. Our goal is to define the terminology, present an overview of probabilistic seismic and rock-physics inversion methods for the estimation of petrophysical properties, demonstrate the fundamental concepts with illustrative examples, and discuss the recent research developments.


ISSN: 0016-8033
EISSN: 1942-2156
Coden: GPYSA7
Serial Title: Geophysics
Serial Volume: 87
Serial Issue: 5
Title: Probabilistic inversion of seismic data for reservoir petrophysical characterization; review and examples
Affiliation: University of Wyoming, Department of Geology and Geophysics, Laramie, WY, United States
Pages: M199-M216
Published: 202210
Text Language: English
Publisher: Society of Exploration Geophysicists, Tulsa, OK, United States
References: 196
Accession Number: 2023-001384
Categories: Applied geophysicsEconomic geology, geology of energy sources
Document Type: Serial
Bibliographic Level: Analytic
Illustration Description: illus.
Secondary Affiliation: University of Lisbon, PRT, PortugalLTrace, BRA, BrazilPCA, GBR, United KingdomStanford University, USA, United States
Country of Publication: United States
Secondary Affiliation: GeoRef, Copyright 2023, American Geosciences Institute. Reference includes data from GeoScienceWorld, Alexandria, VA, United States. Reference includes data supplied by Society of Exploration Geophysicists, Tulsa, OK, United States
Update Code: 2023
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