In this publication, Philippe Doyen reviews some of the most widely used workflows for constraining 3-D earth models with seismic data. They typically involve a sequential process where seismic data are first inverted to elastic properties. Inverted data are then depth-converted and transferred into the earth model framework, where the seismic attributes are used to guide the interpolation of reservoir properties between the wells.
Geostatistics provides a number of tools for this purpose, including generalized regression techniques such as cokriging and kriging with external drift, stochastic simulation with seismic constraints and geostatistical inversion. These techniques are reasonably well-established and their application can lead to significantly better constrained earth models. So what are the remaining challenges for seismic data integration in earth models? In particular, what are the main limitations or bottlenecks with current approaches that need to be addressed in order to make this integration more widely applicable? In the last few paragraphs, Philippe Doyen lists some of the future challenges and new directions in seismic earth modelling.
Table of Contents
Chapter 1: Introduction to Geostatistics and Earth Modelling from Seismic Data
Course Overview
Earth Modelling Workflow with Seismic Data
Introduction to Geostatistics
Chapter 2: 3-D Geostatistical Interpolation & Filtering
Overview
Simple Kriging
Ordinary Kriging
Kriging with Locally Variable Mean
External Drift Kriging
Cokriging
Factorial Kriging
Factorial Cokriging
Chapter 3: Stochastic Simulation with Seismic Constraints
Overview
Sequential Gaussian Simulation
Sequential Simulation with LVM or Collocated Cokriging
SGS with Non-linear Relationships
Simulation with Downscaling
FFT-Moving Average Simulation
Gradual Deformation
Chapter 4: Facies Modelling from Seismic Data
Overview
Bayesian Classification
Sequential Indicator Simulation with Seismic Constraints
Truncated Gaussian Simulation
Boolean Simulation Methods
Multi-Point Statistics Simulation
Chapter 5: Stochastic Inversion
Overview
Geostatistical Inversion using SGS
Bayesian Stochastic Inversion
Exploiting Geostatistical Inversion Results
Joint Stochastic Inversion of Elastic and Petrophysical Properties
Chapter 6: Statistical Rock Physics
Introduction
Monte Carlo Simulation of Rock Physics Templates
Combining Rock Physics and Spatial Uncertainty
Uncertainty Propagation using Linearized Analysis
Rock Physics Inversion using MCS and Bayesian Methods
Pseudo-Well Generation
Direct Petrophysical Inversion
Chapter 7: 4-D Earth Modelling
Overview
Initial Geomodel C Construction
Downscaling of Dynamic Properties
PEM-Based Calculation of Elastic Properties
Computation of 4-D Synthetics
4-D Interpretation
4-D Seismic History Matching
Future Directions
References
Acknowlegements
List of Main Mathematical Symbols
List of Main Abbreviations
Index
For more information about the EAGE Education Tour II, please check the EAGE Education website.
