Wave-equation based AVO Inversion for High Resolution Reservoir Characterisation

 Date  14 November 2017
 Instructor  Prof Dr Dries Gisolf, Delft Inversion  
 Level  Advanced
 Duration  1 day

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Course Description

The purpose of this course is to teach participants the fundamentals of extracting quantitative property information from seismic data. In the end this leads to an inversion process that is linear if the data is supposed to consist of primary reflections only.  If, on the other hand, the data model is based on the full elastic wave-equation, all multiple scattering and multiple mode conversion over a target interval (typically 500 m around the reservoir) are taken into account and the inversion becomes non-linear. Wave-equation based, non-linear inversion leads to a higher resolution than obtained from conventional linear inversion techniques.

In order to understand the difference between the linearised data model and the full non-linear data model it is important to have a good understanding of the acoustic and elastic wave equations. In wave-equation based inversion the properties are directly derived from the data. In the elastic case these properties are the bulk-modulus, the shear modulus and the density.  The non-linear inversion presented in this course is an iterative process of which the first iteration (the Born approximation) represents the linear inversion result. In the higher iterations progressively higher orders of scattering are matched in the data.  The method is based on an integral representation of the wave equation. In conventional AVO inversion the data is linearised in the reflection coefficients.  This linearisation leads to different properties to be inverted for: the acoustic and elastic impedances.

An important aspect of reservoir oriented full wave form inversion (FWI-res) is that the surface recorded data are localised (focused) to the target area. This can be achieved by redatuming, or by local demigration of migrated data.

Finally, wave-equation based inversions at the reservoir scale is demonstrated by realistic synthetic reservoir models and real data case studies. The real data case studies include the extraction of angle dependent wavelets from the seismic-to-well match and the inversion of 3D data volumes for two different properties.

Course Objectives

Upon completion of the course, participants will be able to:

  • Understand what quantitative property information is contained in seismic data and how to extract it.
  • Make better judgements as to what inversion method to apply to what problem.
  • Have a better understanding of the relationship between the temporal bandwidth of the data and the spatial bandwidth of the inversion result and the role of the background models.

Further the role of reservoir geophysics in multidisciplinary projects.

Participants' Profile

This course is designed for geophysicists active in reservoir studies and/or quantitative interpretation. Also processing geophysicists who would like to become involved in quantitative interpretation should attend this course.

 

Pre-requisites

  • Basic training in geophysics
  • Some knowledge of differential equations and integrals

About the Instructor

Dries GisolfProf Dr Dries Gisolf graduated from the Delft University of Technology in 1971 and obtained his PhD at the University of Utrecht in 1975. In 1976 he joined Shell International Research in Rijswijk, The Netherlands, as a seismic data processing geophysicist. Between 1980-2000 he held various positions for Shell in Oman, The Netherlands, Australia, Malaysia and Nigeria. Throughout his career with Shell he was involved in acquisition, processing and interpretation of seismic data, with an emphasis on quantitative prediction of reservoir properties. In September 2000 he was appointed Professor of Acoustics at the Faculty of Applied Sciences at Delft University of Technology. After retiring from TU Delft in 2010, he co-founded Delft Inversion in 2012, a service company providing high-resolution reservoir-oriented inversion services to the oil and gas industry.