4.7 Article

Estimating thermal maturity of organic-rich shale from well logs: Case studies of two shale plays

Journal

FUEL
Volume 235, Issue -, Pages 1195-1206

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.fuel.2018.08.037

Keywords

Organic-rich shale; Maturity indicator; Vitrinite reflectance; Compensated neutron log; Yanchang Formation; Bakken Shale

Funding

  1. National Natural Science Foundation of China [41722403, 41574121]
  2. Fundamental Research Funds for the Central Universities (China University of Geosciences, Wuhan) [CUG170619]

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Thermal maturity is an important geochemical parameter for the study of source rocks in unconventional shale plays. Using well logs to estimate thermal maturity would overcome the discontinuity of core sample analysis and can provide continuous profiles. However, estimating thermal maturity from well logs, unlike total organic carbon (TOC) content has received less attention. In this paper, we used vitrinite reflectance (R-o) to characterize thermal maturity and proposed a practical method to produce a continuous profile of thermal maturity from well logs. For this purpose, a maturity indicator (I-m) regarding with kerogen element compositions and types was defined. I-m was calculated for different kerogen types based on their H/C versus O/C atomic ratios. It was found that R-o decreases with the I-m of all three types of kerogen monotonically, which was used as a foundation for thermal maturity predictions. Then, the I-m was related to the compensated neutron log (CNL) responses of kerogen by considering the variations in elemental compositions of organic matter with maturity. Based on known CNL response of major sedimentary minerals and pore fluids, a petrophysical equation was established to obtain I-m from well logs. Finally, the proposed method was applied to Chang 7 Shale of Triassic Yanchang Formation of the Ordos Basin, China and the Bakken Shale of Williston Basin, North Dakota, USA, two major source rocks with different kerogen types and maturities. The results showed an acceptable agreement between lab measurements and predictions of R-o with a good correlation coefficient, verifying the new method is effective and reliable.

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