Computer Vision Retrieval for Similar Petrographic Thin Sections
The harmonized Digital Core Concept(DCC)is flawed without descriptive characteristics of porosity and permeability based on images of the Thin Sections.The texture”s properties of the Thin Section have profound influence on reservoir properties.Grain size has impact on porosity,permeability and sorting.Finding similar textures may be connected to the reservoir comparisons.What you need is a simple and effective way of image retrieval.The authors of this research designed and implemented Computer Vision approaches for such a problem and found them fast and accurate.
CV Computer Vision ML machine learning Legacy archives
Belozerov B.V A.V.Butorin F.V.Krasnov
LLC Gazpromneft Science & Technology Centre,Saint-Petersburg,Russia
国内会议
2017年第五届数字油田国际学术会议(DOFIAC2017)
青岛
英文
373-375
2017-10-15（万方平台首次上网日期，不代表论文的发表时间）