Multi-wave seismic oil and gas reservoir prediction method based on deep neural network

Abstract

The invention discloses a multi-wave seismic oil and gas reservoir prediction method based on a deep neural network. The method comprises the steps of firstly, carrying out optimization on seismic attributes through employing a particle swarm optimization clustering analysis method and a kernel principal component analysis method for original data obtained from a longitudinal and transverse wave seismic attribute set, removing redundant information, and highlighting characteristics of the multi-wave seismic oil and gas reservoir to obtain better deep neural network sample data; then, learningthe obtained sample data through a deep neural network model, and carrying out simulation prediction to obtain an oil and gas reservoir evaluation map; and finally, performing image enhancement processing on the oil and gas reservoir evaluation image so as to improve the detail information and the edge identification degree of the image and improve the definition of the image. In oil and gas reservoir prediction, the method provided by the invention can improve the depicting precision of the seismic oil and gas reservoir, and provides a new way for identification and prediction of the oil andgas reservoir.

Description

technical field [0001] The invention belongs to the technical field of oil and gas reservoir prediction, in particular to a multi-wave seismic oil and gas reservoir prediction method based on a deep neural network. Background technique [0002] Seismic oil and gas reservoir prediction has always been a hot and difficult point in the exploration and development of oil and gas fields. Seismic data contain rich information on geological structures, physical properties of oil and gas, and underground strata. Therefore, using seismic data to obtain information on lithology and physical properties related to oil and gas is an effective prediction method. At present, the commonly used seismic oil and gas reservoir prediction technologies mainly include seismic attribute analysis technology, AVO technology, seismic fracture prediction technology, petrophysical analysis technology, forward modeling and multi-wave seismic oil and gas detection, etc. Seismic attribute analysis technol...

AI Technical Summary

Problems solved by technology

However, with the development of mathematics and computer technology, hundreds of seismic attributes can be obtained, but too much seismic attribute extraction will have a large amount of redundant data, and there will be problems such as unclear correspondence between the extracted attributes and geological significance. Therefore, how to optimize various attributes to improve production efficiency and reduce exploration costs is an urgent problem at this stage

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