Abstract:
Reservoir thickness is an important parameter in the description and simulation of reservoir. The principle and method of the Support Vector Machines are introduced in th...Show MoreMetadata
Abstract:
Reservoir thickness is an important parameter in the description and simulation of reservoir. The principle and method of the Support Vector Machines are introduced in this paper. Based on the previous study of seismic interpretation, 100 sets of data of the five seismic attributes and the reservoir thickness in a work area are used as the example for predicting the reservoir thickness. The results prove that this method may throw important light on the predicting and computing the reservoir thickness.
Published in: 2012 8th International Conference on Natural Computation
Date of Conference: 29-31 May 2012
Date Added to IEEE Xplore: 09 July 2012
ISBN Information: