Geostatistic Recognition of Genetically Distinct Lacustrine Shale Facies Based on Big Data Technology

With the breakthrough and progress of shale oil and gas exploration, the strong heterogeneity of shale has been highly paid attention. Relying on the traditional geological methods, the classification of shale is difficult to meet the current needs of exploration and development. It is a very important problem that how to complete the genetic classification of shale based on the comprehensive consideration of many parameters including genesis and characteristics. This paper demonstrates that the geostatistic recognition based on big data technology analysis can processing numerous data and identifies genetically distinct shale facies, which improve understanding of changes in a single shale formation. It has functions (1) of assigning genetic affinities and (2) of making it available that a confidence level in the classification for any additional shale samples.