Automatic seismic pattern recognition method

G - Physics – 01 – V

Patent

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G01V 1/28 (2006.01) G01V 1/30 (2006.01)

Patent

CA 2205457

An automatic seismic pattern recognition method is characterised in that it includes determining a given number of seismic patterns to be recognised; providing a set of seismic trace portions for said region; defining a pattern recognition parameter common to all the trace portions, and determining the value of said parameter for each of the trace portions of the set; selecting trace portions among said set; selecting a one-dimensional neural network containing as many cells as there are patterns to be recognised, each cell being assigned a value of the recognition parameter; submitting the neural network to a learning process with the selected trace portions, so that at the end of said process, each cell matches a pattern to be recognised, and that said patterns are progressively ordered; presenting each trace portion of said set to be processed to the classified and ordered neural network; and attributing to each trace portion presented to the network the number of the cell closest to it. The invention is particularly useful for recognising seismic patterns between two horizons defined by plotting a seismic section.

Elle est caractérisée en ce qu'elle consiste à: déterminer un nombre donné de faciès sismiques à reconnaître; prendre un ensemble de portions de trace sismique concernant ladite zone; définir un paramètre de reconnaissance de faciès commun à toutes les portions de trace et déterminer la valeur dudit paramètre pour chacune des portions de trace de l'ensemble; sélectionner des portions de trace parmi ledit ensemble; choisir un réseau neuronal unidimensionnel renfermant autant de cellules que de faciès à reconnaître, chaque cellule étant affectée d'une valeur du paramètre de reconnaissance; effectuer l'apprentissage du réseau neuronal à l'aide des portions de trace sélectionnées, de sorte qu'en fin d'apprentissage chaque cellule corresponde à un faciès à reconnaître, et que lesdits faciès soient ordonnés graduellement; présenter chaque portion de trace dudit ensemble à traiter au réseau neuronal classé et ordonnancé; et affecter à chacune des portions de trace présentée au réseau le numéro de la cellule la plus proche. Application notamment à la reconnaissance de faciès sismiques entre deux horizons pointés sur une section sismique.

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