A comprehensive porosity prediction model for the Upper Paleozoic tight sandstone reservoir in the Daniudi gas field, Ordos Basin

• Published in: Journal of earth science (Wuhan, China) Vol. 28; no. 6; pp. 1086 - 1096
• Main Authors: Qiu, Longwei, Yang, Shengchao, Qu, Changsheng, Xu, Ningning, Gao, Qingsong, Zhang, Xiangjin, Liu, Xugang, Wang, Donghui
• Format: Journal Article
• Language: English
• Published: Wuhan China University of Geosciences 01.12.2017; Springer Nature B.V; School of Geosciences, China University of Petroleum, Qingdao266580, China%School of Geosciences, China University of Petroleum, Qingdao266580, China; State Key Laboratory for Mineral Deposits Research, School of Earth Sciences and Engineering, Nanjing University, Nanjing210046, China%Exploration and Development Institute, North-China Branch Company, SINOPEC, Zhengzhou450006, China%Tianjin Fanglian Technology Development Co. Ltd., Tianjin300280,China
• Subjects: Biogeosciences; Compaction; Concrete; Densification; Diagenesis; Earth and Environmental Science; Earth Sciences; Geochemistry; Geology; Geostatistics; Geotechnical Engineering & Applied Earth Sciences; Grain; Mathematical models; Oil and gas fields; Porosity; Qualitative analysis; Sandstone; Sedimentary rocks; Ordos Basin; Daniudi gas field; tight sandstone reservoir; porosity; controlling factors
• ISSN: 1674-487X; 1867-111X
• DOI: 10.1007/s12583-016-0935-2

This paper investigated the porosity controlling factors for tight sandstone reservoir in the Daniudi gas field, Ordos Basin based on an integrated petrographic, petrophysical and geostatistical analyses, and proposed a comprehensive prediction model for reservoir porosity. Compaction was found to be a key factor for causing reservoir densification. The degree of sandstone compaction appears to be affected by grain sizes and sorting. Under normal compaction conditions (e.g., cement content less than 6%, and with no dissolution), the variation in reservoir porosity with burial depth can be well correlated with grain compositions, grain sizes, and sorting. Based on qualitative examination of the controlling factors for reservoir porosities, geostatistics were used to quantify the effects of various geological parameters on reservoir porosities. A statistical model for comprehensive prediction of porosity was then established, on the assumption that the present reservoir porosity directly relates to both normal compaction and diagenesis. This model is easy to use, and has been validated with measured porosity data. The porosity controlling factors and the comprehensive porosity prediction can be used to quantify effects of the main controlling factors and their interaction on reservoir property evolution, and may provide a reference model for log interpretation.