Seismic Data Conditioning, AVO Modeling and Analysis, and Inversion for Reservoir Characterization

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Learning Objectives

Upon completion of this course, participants will grasp key aspects of the concept, workflow and benefits of predicting fluid and rock properties and estimating uncertainties for a better understanding of the reservoir.

Audience

Anyone interested in understanding the theory, workflow and optimal way to integrate reservoir properties into accurate and predictive models.

Content

Day 1 – Data Conditioning

• Random and coherent noise attenuation
• Residual NMO and gather alignment
• Amplitude correction
• Frequency and bandwidth
• Phase distortion
• Trace organization and conversion
• 4D seismic conditioning
• Common offset/angle Azimuthal Gathers

Day 2 – AVO Modeling and Analysis

• Introduction: Basic seismic wave principles, Poisson's ratio, gas saturation, Biot-Gassmann equations, and lithologic examples
• AVO Theory: Zoeppritz's equations, Aki-Richards and Shuey's approximation, elastic wave modeling, and impact of anistropy
• AVO Analysis: AVO attribute volume generation and considerations, processing concerns, interpretation of AVO measurements, classification of AVO responses, AVO crossplotting and polarization, and examples from published case studies
• Emphasizes practical AVO examples from a number of regions around the world
• Explains both the advantages and potential pitfalls of the AVO method

Day 3 – Deterministic Inversion using Strata

• Introduction: Convolutional models, wavelets, reflectivity and noise
• Theory: Recursive, sparse-spike, model-based and colored inversion. Pre-stack methods of Elastic Impedance and Lambda-Mu-Rho
• Analysis: Seismic and wavelet processing, amplitude recover, noise attenuation and imaging
• Practical: Examples of band-limited, sparse-spike and model-based inversion
• Includes pre-stack Simultaneous Inversion

Day 4 – Geostatistical Inversion using GeoSI

• Introduction to inversion methods – deterministic and stochastic.
• Log correlation and Model Building on both seismic and stratigraphic grids
• Basic stochastic inversion theories: Sequential Gaussian Simulation, Bayesian Stochastic inversion and GeoSI inversion theory
• Correlation and Variogram modelling
• Facies classification theory
• Stochastic lithology prediction
• Stabilizing the results
• 3D visualization

Duration: 3 _1/2 days

Software used: HampsonRussell AVO, Strata, GeoSI

Course Format: Instructor-led, workflow-based, virtual classroom

Instructor(s): Shervin Rasoulzadeh

Prerequisites: None

Number of Participants: 8-10

Price:

US $3,000.00