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A knowledge-based approach of 3D seismic interpretation : a first step to shared earth modeling by
means of cognitive vision.
P. Verney (IFP/ENSMP, France), M. Thonnat (Pulsar INRIA Sophia Antipolis, France), J.F. Rainaud (Institut
Français du Pétrole, France)
This work deals with the semantic interpretation of a 3D seismic image in order to build a shared earth
model. For achieving this goal, we propose a method which enables to build in a largely automated way,
starting from a 3D seismic image (SEGY), a basic earth model composed of horizons and faults, whose
various mutual relationships are fully defined and geologically consistent.
At present, seismic interpretation is generally based on image processing and seismic attributes. Results are
interpreted by experts, who establish a correspondence between the image provided by the interpretation
platform and a set of geological objects.
In contrast to current seismic interpretation methods, we propose a new interpretation approach, which is not
based on mere image processing but on considering the geological knowledge that can be associated to
seismic images.
We choose to manage this knowledge by means of an ontology which enables formalizing, using and sharing
all useful concepts, relations, attributes and instances.
Our approach is based on the cognitive vision method, which is operated in various domains by the PULSAR
team at INRIA Sophia Antipolis. In accordance with the Marr paradigm, we thus define a seismic
interpretation system by means of 3 abstraction levels of object visual representation :
 The lowest level of abstraction is related to data management, i.e. to extracting from the seismic
image some candidates that potentially correspond or are potentially part of some geological object.

The median level aims at defining criteria for characterizing these candidates by means of relations
and attributes representing their visual properties.

The highest level enables to decide whether a defined candidate can be associated to some geological
object. This interpretation makes use of associations previously established between sets of visual
attributes and relations and actual geological objects.
The most important geological surfaces, which enter into earth models, are horizons and faults. Their mutual
arrangement within a structural model allows to represent the vertical sequence of sedimentary layers present
within the considered prospect and their disconnections through faults. For this reason, we decided to
concentrate on that one issue, considering that other important elements such as diapirs, channels or
chimneys will eventually be objects of future work.
The above described methodology was applied to various seismic blocks. We will consider here the results
that were obtained by processing the Alwyn seismic block, which corresponds to data provided by Total UK
related to a field located in the North Sea. In order to verify our interpretations, we took advantage of results
obtained on the Alwyn block by students of the IFP School, who provided us a set of hand-picked horizons
and faults. These surfaces were identified during a 3 week training session of the IFP School by using the
Petrel software, which is one the most used all over the world for seismic interpretation. The results obtained
by the IFP students were further validated by their supervisors, who have an extensive knowledge of the
Alwyn data.
References:
Verney, P., Interprétation géologique de données sismiques par une méthode supervisée basée sur la vision cognitive,
Ecole Nationale Supérieure des Mines de Paris, 2009, Phdthesis
Verney, P., Perrin, M., Thonnat, M. & Rainaud, J.-F., An Approach of Seismic Interpretation Based on Cognitive Vision,
70th EAGE Conference and Exhibition, 2008(B024), Proceedings
Verney, P., Rainaud, J.-F., Perrin, M. & Thonnat, M., Méthode pour construire un modèle géologique par interprétation
sismique au moyen de techniques de vision cognitive, 2008(5794/00/BA), Patent
Verney, P., Rainaud, J.-F., Perrin, M. & Thonnat, M., A knowledge-based approach of seismic interpretation : horizon
and dip-fault detection by means of cognitive vision, SEG Las Vegas 2008 Annual Meeting, 2008, pp. 874-878,
Proceedings