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2010•Marine Geology LettersRequires access

APPLICATION OF NEURAL NETWORK TECHNOLOGY OPTIMIZED BY MULTIPLE SEISMIC ATTRIBUTES TO PREDICT HIGH-IMPEDANCE SANDSTONE RESERVOIRS IN ORDOS BASIN

Zhiqiang Wu

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Abstract

The seismic attribute extracted from seismic data may be related to some geologic parameters.However,a single attribute parameter usually has multiplicity.In this paper,The high-impedance sandstone reservoir is predicted with neural network technology optimized by multiple seismic attributes.Calculation results show that this technology is effective to avoid the multiplicity of a single seismic attribute and the difficulty in recognition of integrated multiple seismic attributes.With this approach,we can improve the prediction precision for a high-impedance sandstone reservoir.

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What this paper is about

The seismic attribute extracted from seismic data may be related to some geologic parameters.However,a single attribute parameter usually has multiplicity.In this paper,The high-impedance sandstone reservoir is predicted with neural network technology optimized by multiple seismic attributes.Calculation results show that this technology is effective to avoid the multiplicity of a single seismic attribute and the difficulty in recognition of integrated multiple seismic attributes.With this approach,we can improve the prediction precision for a high-impedance sandstone reservoir.

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Available abstract

The seismic attribute extracted from seismic data may be related to some geologic parameters.However,a single attribute parameter usually has multiplicity.In this paper,The high-impedance sandstone reservoir is predicted with neural network technology optimized by multiple seismic attributes.Calculation results show that this technology is effective to avoid the multiplicity of a single seismic attribute and the difficulty in recognition of integrated multiple seismic attributes.With this approach,we can improve the prediction precision for a high-impedance sandstone reservoir.

Key concepts: Geology, Seismic attribute, Seismic to simulation, Artificial neural network, Electrical impedance, Multiplicity (mathematics), Seismology, Seismic inversion

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APPLICATION OF NEURAL NETWORK TECHNOLOGY OPTIMIZED BY MULTIPLE SEISMIC ATTRIBUTES TO PREDICT HIGH-IMPEDANCE SANDSTONE RESERVOIRS IN ORDOS BASIN — Research Paper | ScholarLens