Incorporating Seismic Data into 3-D Reservoir Characterization

@inproceedings{PairazianRM1997a,
 abstract = { Two different approaches are proposed in this paper for integrating seismic data in 3D reservoir models. First method is a non supervised and based on seismic cluster analysis. The geological interpretation of the obtained clusters is done afterwards by calibrating the clusters with the reservoir characteristics at the weil locations. The supervised method can also be carried out for estimating the probable distribution of geological properties in reservoir volume. This method consists of using a neural network as a non-linear prediction tool where the training data is composed by the traces of different seismic attributes in the vicinity of the wells. The combination of this two approaches can be very efficient in reducing the uncertainties and improving the image quality. },
 author = { PAIRAZIAN, Karen },
 booktitle = { 15th gOcad Meeting },
 month = { "june" },
 publisher = { ASGA },
 title = { Incorporating Seismic Data into 3-D Reservoir Characterization },
 year = { 1997 }
}