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Develop measurable skills and capabilities
This class provides a hands-on, workflow-based course on data-driven surface multiple prediction.
At the end of this class, students will have the skills to perform surface multiple prediction using the General Surface Multiple Prediction (GSMP) seismic function module (SFM). These skills include effective testing, quality control and optimum parameterization
Understanding the Input Data Prerequisites and Designing a Testing Plan
At the end of the day the student will be able to explain the input data requirements for GSMP and its basic theoretical background, which involves but is not limited to the earth’s convolutional model, multiples’ convolutional model and 3D marine acquisition limitations.Day 2
GSMP Optimum Parameterization, Testing and Quality Assessment
At the end of the day the student will be able to parameterize GSMP and describe the strategies behind the optimization of various parameters by using QC tools such as SeisView/MAD/Petrel etc.Day 3
Analysis of Results and Introduction to Adaptive Subtraction
At the end of the day the student will be able to describe the various approaches available for adaptive subtraction. There will also be an enhanced session for various uses of GSMP modelling in different geological settings.
Experienced geophysicists who wish to gain a more in-depth understanding of the GSMP technique
An understanding the theory of data-driven Surface Related Multiple Elimination (SRME) and familiarity with WesternGeco’s scheme of General Surface Multiple Prediction (GSMP), including “on-the-fly interpolation”.
Basic Omega and Petrel skills.
Customize your own learning journey and track your progress when you start using a defined learning path.