The Inverse Modeling and Geostatistics Project
Research People Papers Software Teaching

Risk Assessment and Multiple Scenario Generation from Seismic and Geological Data

This project is funded from 21. August 2009 by DONG Energy & Production (DKK 3.5 mill. or $690.000).

Summary
Risk assessment in hydrocarbon exploration and production requires a careful, integrated data analysis where uncertainties are correctly balanced. Current methods can do this, but they ignore that data has multiple interpretations, and this adds the further, major risk that economically interesting interpretations are overlooked. This project combines the most recent advances in geophysical and geostatistical theory to develop methods and software for simultaneous analysis of uncertainty and non-uniqueness of geophysical and geological data.

The aim of this project is to develop methods, algorithms and software for integrated uncertainty assessment and generation of multiple geological scenarios from seismic data and statistical geological information. An important principle behind the method will be to generate models that fit seismic data within uncertainties, and simultaneously obey geostatistical constraints (including well information). Since efficient algorithms with this goal cannot easily be developed using traditional Monte Carlo methods, our aim is to investigate more systematic, iterative methods.

(Collaborators: Chief geophysicist Niels Ter-Borch, DONG Energy and Production, Denmark; R & D Manager, Ph.D. Morten G. Stage, DONG Energy and Production, Denmark; Prof. dr. Albert Tarantola, IPGP, University of Paris, France; Prof. dr. Jef Caers, Energy Resources Engineering Department, Stanford University, USA.)