Abstract
Abstract Lithologic identification is critical for studying fine - grained sediments, which further elucidates sedimentary environment, and formation. The oil - bearing Chang 7 Section of the Yanchang Formation in Ordos Basin contains thick dark mudstone with a wide distribution, interbedded by siltstone and fine sandstone. The lacustrine fine - grained sedimentary rocks constitute the chief source rock of the Yanchang Formation. On the grounds of fine core description, thin rock slice identification and X - ray diffraction analysis, we proposed a new method based on conventional logging data. This method is using density (DEN) and natural gamma (GR) logging curve intersection and multivariate linear regression analysis of logging curve value and measured mineral content value which is carried out by SPSS software to identify the lithology and the vertical distribution characteristics of fine - grained sedimentary rock of Chang 7 formation in the study area. This method is mainly suitable for lithologic identification of fine - grained sedimentary rocks in lake basin. It not only quantitatively analyses the contents of main minerals and organic matter in fine - grained sedimentary rocks, but also greatly improved the accuracy and universality of using conventional logging data to identify the lithology of fine - grained sedimentary rocks, which provides a reference for the exploration of tight oil.
Highlights
Lithologic identification is critical for studying fine - grained sediments, which further elucidates sedimentary environment, and formation
The term fine - grained sedimentary rock refers to the content of grain whose diameter less than 0.0625 mm is more than 50%, and is mainly composed of clay, siltstone, and small amounts of endogenic carbonates, biological silica minerals, phosphates [39, 40]
The SPSS software can be used to fit the main mineral content and the organic carbon prediction formula method to identify the lithologies of fine - grained sedimentary rocks and further explore the distribution characteristics of fine - grained sedimentary rocks
Summary
Abstract: Lithologic identification is critical for studying fine - grained sediments, which further elucidates sedimentary environment, and formation. On the grounds of fine core description, thin rock slice identification and X ray diffraction analysis, we proposed a new method based on conventional logging data This method is using density (DEN) and natural gamma (GR) logging curve intersection and multivariate linear regression analysis of logging curve value and measured mineral content value which is carried out by SPSS software to identify the lithology and the vertical distribution characteristics of fine - grained sedimentary rock of Chang 7 formation in the study area. This method is mainly suitable for lithologic identification of fine - grained sedimentary rocks in lake basin. It quantitatively analyses the contents of main minerals and organic matter in fine - grained sedimentary rocks, and greatly improved the accuracy and universality of using conventional logging data to identify the lithology of fine grained sedimentary rocks, which provides a reference for the exploration of tight oil
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