AUTHOR=Su Zhaodong , Cao Junxing , Xiang Tao , Fu Jingcheng , Shi Shaochen TITLE=Seismic prediction of porosity in tight reservoirs based on transformer JOURNAL=Frontiers in Earth Science VOLUME=11 YEAR=2023 URL=https://www.frontiersin.org/journals/earth-science/articles/10.3389/feart.2023.1137645 DOI=10.3389/feart.2023.1137645 ISSN=2296-6463 ABSTRACT=

Porosity is a crucial index in reservoir evaluation. In tight reservoirs, the porosity is low, resulting in weak seismic responses to changes in porosity. Moreover, the relationship between porosity and seismic response is complex, making accurate porosity inversion prediction challenging. This paper proposes a Transformer-based seismic multi-attribute inversion prediction method for tight reservoir porosity to address this issue. The proposed method takes multiple seismic attributes as input data and porosity as output data. The Transformer mapping transformation network consists of an encoder, a multi-head attention layer, and a decoder and is optimized for training with a gating mechanism and a variable selection module. Applying this method to actual data from a tight sandstone gas exploration area in the Sichuan Basin yielded a porosity prediction coincidence rate of 95% with the well data.