Petrophysics for Seismic Interpretation Course
Duration: 5 Days / 20 Hours
ــــــــــــ 20/04/2025
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Seismic Petrophysics is the careful and purposeful use of rock physics data and theory with well-log data in the interpretation of seismic observations. The course begins with simple commonly used models and continually expands on them to include increasingly complicated and realistic interpretations. At each step, the relationships between laboratory, theory, well-logs, and seismic data are investigated. A set of spreadsheets that incorporate many of the models, predicting fluid properties, rock properties, and seismic response.
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Part 1: Fundamentals
· Porosity and velocity
· Effect of clays on velocities
· Invasion, fluids
· Simple mixing laws (Voigt, Reuss, etc)
· Critical Porosity
· Hashin-Shtrikman bounds
· Fluid substitution ; Gassmann equation
· Fluid mixing; patchy saturation
Part 2: Log Data; Post-stack Attributes
· Vp and Vs; Poisson’s ratio
· Using M instead of K if no Vs
· Sonic and Dipole logging
· Seismic processing
· Post-stack attributes
· Interval attributes
· Unique attributes
Part 3: Seismic Data and Pre-stack Attributes
· Pre-stack seismic processing
· Model scenario of production
· Pressure-dependence of properties
· Angle-dependent rock physics
· Pre-stack attributes
· 3-term and 2-term approximations
· Lamda-rho etc
Part 4: Fluids and Inversion
· Fluid properties
· Spreadsheet solutions
· Rocks and fluids
· Empirical relationships
· Acoustic inversion
· Case study of time-lapse monitoring
· Elastic inversion
· Stochastic approaches
· Rock physics templates
Part 5: Complicated Rocks and Advanced Topics
· Kuster-Toksoz “crack” model
· Coal as a special example
· Xu and White model for shaly rocks
· Other models for shaly rocks
· Petrophysical Inversion
· Importance of scale
· Phantom horizons
· Carbonate rocks
· Heavy Oil
· Spectral content
· Thin-bed problems
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Petrophysicsits, geophysicists, geologists, technical support personnel, seismic processors, exploration and data processing managers and data acquisition managers.