Multi-Objective Petrophysical Seismic Inversion Based on the Double-Porosity Biot–Rayleigh Model

Guo, Qiang; Ba, Jing; Carcione, José M.

doi:10.1007/s10712-022-09692-6

Cited by 12 publications

(2 citation statements)

References 60 publications

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“…[1][2][3][4][5][6][7][8] or petrophysical parameters (e.g., porosity, fluid saturation, mineral content, etc.) [9][10][11][12][13] and then provides a database for geofluid identification, lithology classification, and reservoir prediction [14]. By using the processed seismic gathers as input data and geological or logging data as prior constraints, it is one of the most effective techniques in seismic exploration of the oil/gas industries.…”

Section: Introductionmentioning

confidence: 99%

Sequential Seismic Anisotropic Inversion for VTI Media with Simulated Annealing Algorithm Aided by Adaptive Setting of Optimization Parameters

Luo

Guo

2023

Remote Sensing

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As an important geophysical data processing technique, seismic inversion estimates subsurface rock properties with seismic observations. However, anisotropic inversion, intended for a vertical transverse isotropy (VTI) media that primarily describes shale gas/oil resources, suffers from high nonlinearity. Simulated annealing is a widely used global optimization algorithm for solving nonlinear seismic inverse problems, but it involves multiple optimization parameters (e.g., initial temperature, search limit, and perturbation range). The importance of such parameters has been proven whilst the relevant analysis is limited in seismic inversion studies. This work hereby proposes a sequential anisotropic inversion method for VTI media, wherein we combine Bayesian linear and simulated annealing nonlinear inversion schemes. The simulated annealing is featured by adaptive optimization parameters aided by the linear result. Rather than the conventional method, the adaptive setting can be implemented trace by trace for complex reservoirs, which endows the method with enhanced stability and extended applicability. Synthetic tests and practical application demonstrate the validity of the method, wherein the obtained stiffness parameters facilitate the characterization of potential shale reservoirs with an improved accuracy.

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Section: Introductionmentioning

confidence: 99%

Sequential Seismic Anisotropic Inversion for VTI Media with Simulated Annealing Algorithm Aided by Adaptive Setting of Optimization Parameters

Luo

Guo

2023

Remote Sensing

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“…To overcome the limitations of a single approach, many studies tend to combine statistical and rock physics approaches flexibly and appropriately. For example, with the rock physics approach, statistical models can add the constraints of well log data (Guo et al., 2022; Pang et al., 2021); with the statistical approach, rock physics models can generate data to supplement sparse training samples (Y. Wang et al., 2021). Therefore, we combine the two approaches to establish a multiobjective inversion problem in this paper.…”

Section: Introductionmentioning

confidence: 99%

Joint inversion for facies and petrophysical properties based on a bi‐level optimization model

Wen,

Yang,

Cheng

et al. 2023

Geophysical Prospecting

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In many subsurface studies, facies and petrophysical properties are two important reservoir parameters that are closely correlated. They are routinely used in well interpretation, hydrocarbon reserve calculation and production profile prediction. These two parameters have commonly been determined in two separate tasks because of their mathematical differences (facies are discrete and petrophysical properties are continuous). However, it is incorrect because facies and petrophysical properties are often strongly correlated. Therefore, we propose a new joint inversion method of facies and petrophysical properties based on a bilevel optimization model. In the bilevel optimization model, the upper‐level problem is the petrophysical property inversion while the lower‐level problem can identify the facies and add a facies‐related constraint for the upper‐level optimization. We also develop a new genetic algorithm for the discrete‐continuous inversion problem based on the bilevel optimization model because the inversion problem usually has multiple local solutions. In addition, rock physics and statistics are combined in the inversion process. A rock physics model is used to establish the basic relationships between the petrophysical and elastic parameters, and the statistical approach is used to describe the intrinsic connection among the multiple reservoir parameters based on well log data. The numerical experiments indicate that the traditional separate prediction method and the new joint inversion method can quickly obtain more accurate results. In the application examples of real data, the inversion results can be matched to the well log data within the limits of the input data resolution, which further verifies the reliability and application potential of this new method.This article is protected by copyright. All rights reserved

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Process parameter optimization of WC/Inconel 625 metal matrix composites laser cladding based on the Taguchi approach and NSGA-II algorithm

Rafiei,

Soheil Shamaee,

Ghasemi

2024

Soft Comput

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Multi-Objective Petrophysical Seismic Inversion Based on the Double-Porosity Biot–Rayleigh Model

Cited by 12 publications

References 60 publications

Sequential Seismic Anisotropic Inversion for VTI Media with Simulated Annealing Algorithm Aided by Adaptive Setting of Optimization Parameters

Sequential Seismic Anisotropic Inversion for VTI Media with Simulated Annealing Algorithm Aided by Adaptive Setting of Optimization Parameters

Joint inversion for facies and petrophysical properties based on a bi‐level optimization model

Process parameter optimization of WC/Inconel 625 metal matrix composites laser cladding based on the Taguchi approach and NSGA-II algorithm

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