Introduction

This course provides a detailed exploration of seismic inversion, a critical tool for reservoir characterization, allowing for the transformation of seismic data into quantitative rock property models. Participants will learn about various seismic inversion methods, data integration, and applications in subsurface analysis.

Objectives

• Understand the fundamentals of seismic inversion and its applications.
• Learn about different inversion methods: acoustic, elastic, and pre-stack.
• Develop skills in interpreting inversion results and integrating well log data.
• Explore the role of inversion in reservoir characterization and modeling.
• Analyze future trends, including AI and machine learning in seismic inversion.

Who Should Attend?

This course is ideal for:

• Geophysicists, seismic interpreters, and reservoir engineers.
• Exploration geologists and petrophysicists involved in subsurface characterization.
• Data scientists interested in geophysical applications of AI and ML.
• Recent graduates in geophysics or geological sciences.

Course Outline

Day 1: Fundamentals of Seismic Inversion

• Introduction to Seismic Inversion
  • Overview of seismic inversion and its importance in reservoir characterization
  • Key concepts: impedance, reflectivity, and wave propagation
• Types of Seismic Inversion
  • Differences between post-stack, pre-stack, acoustic, and elastic inversion
  • Techniques for selecting the appropriate inversion method based on objectives
• Data Requirements and Preprocessing
  • Importance of high-quality seismic data and preprocessing steps
  • Overview of data conditioning, noise reduction, and data quality checks

Day 2: Post-Stack and Pre-Stack Inversion Techniques

• Post-Stack Inversion Techniques
  • Overview of model-based, band-limited, and sparse spike inversion
  • Applications and limitations of post-stack inversion
• Pre-Stack Inversion Techniques
  • Techniques for conducting pre-stack inversion: AVO analysis, elastic inversion
  • Advantages of pre-stack over post-stack in identifying fluid and lithology changes
• Acoustic and Elastic Impedance Inversion
  • Differences between acoustic and elastic inversion and their applications
  • Techniques for obtaining impedance volumes for reservoir characterization

Day 3: Interpreting and Integrating Seismic Inversion Results

• Interpreting Inversion Data for Reservoir Properties
  • Techniques for interpreting impedance data to assess porosity, lithology, and fluid content
  • Role of inversion data in delineating reservoir boundaries and heterogeneities
• Integrating Well Logs with Seismic Inversion Data
  • Techniques for calibrating seismic inversion with well log data
  • Importance of synthetic seismograms and cross-validation for accuracy
• Multi-Attribute Analysis and Rock Physics Modeling
  • Overview of multi-attribute analysis for improving property prediction
  • Role of rock physics in enhancing inversion accuracy and interpretation

Day 4: Advanced Inversion Techniques and Reservoir Modeling

• Simultaneous and Joint Inversion Techniques
  • Overview of simultaneous inversion for combining multiple seismic datasets
  • Joint inversion of seismic and non-seismic data for improved reservoir models
• Machine Learning in Seismic Inversion
  • Applications of machine learning for predicting rock properties from inversion data
  • Overview of neural networks, random forests, and support vector machines in inversion
• Seismic Inversion for Reservoir Modeling
  • Techniques for using inversion data in 3D reservoir modeling
  • Integrating seismic inversion with geological and petrophysical data

Day 5: Case Studies and Future of Seismic Inversion

• Case Studies in Seismic Inversion Applications
  • Analysis of real-world examples where seismic inversion improved exploration outcomes
  • Lessons learned in inversion accuracy, data integration, and interpretation
• Innovations in Seismic Inversion and Future Trends
  • Trends in multi-physics inversion, data fusion, and real-time inversion
  • Role of cloud computing and high-performance computing in seismic inversion
• Final Project: Seismic Inversion Plan for a Hypothetical Reservoir
  • Participants develop an inversion plan, selecting techniques, data sources, and interpretation strategies for a hypothetical reservoir characterization project
• Preparing for Future Advances in Seismic Inversion
  • Techniques for adapting to new technologies and improving interpretive skills
  • Role of continuous learning and software proficiency in advancing geophysical analysis