Introduction to inversion methods – deterministic and stochastic.Attributes exercises using seismic data and well logs.
Application of attributes to predict missing log data.Application of attributes to convert seismic data volumes into geological or petrophysical volumes.Theory of seismic attributes, linear, non-linear and neural network methodologies for attribute selection, cross-validation and attribute ranking.QCing the results of gather conditioning.Algorithms for gather conditioning: Mute, NMO, Trim Statics, Deconvolution, Filtering, Radon Transforms, Gather Creation (angle, super), and Stacking.Identifying the need for gather conditioning.Introduction to importance and benefit of gather conditioning.Combining LithoSI and RockSI (Note that LithoSI is a seismic petro-facies program which is a companion program to RockSI).Uncertainty analysis using Monte Carlo simulations of PEMs.Facies creation using Petro-Elastic Models (PEMs).Introduction to rock physics and the RockSI software program.AudienceĪnyone interested in understanding the theory, benefits, and workflows for the use of advanced techniques for seismic reservoir characterization Content Students will learn workflows and best practices for incorporating advanced techniques when estimating reservoir properties and analyzing uncertainties of these properties. Upon completion of this course, participants will understand key aspects of advanced topics associated with predicting rock and fluid properties using quantitative seismic reservoir characterization techniques.