EGU24-3705, updated on 08 Mar 2024
https://doi.org/10.5194/egusphere-egu24-3705
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Detection of orbital signals in the sedimentary record through stochastic statistical modeling

Meng Wang1, Mingsong Li1, Elizabeth A. Hajek2, David B. Kemp3, Yujing Wu1, Hanyu Zhu1, and Zhijun Jin4,5,1
Meng Wang et al.
  • 1School of Earth and Space Sciences, Peking University, Beijing, China (mwang@pku.edu.cn)
  • 2Department of Geosciences, Pennsylvania State University, Pennsylvania, USA
  • 3School of Earth Sciences, China University of Geosciences, Wuhan, China
  • 4Institute of Energy, Peking University, Beijing, China
  • 5State Key Laboratory of Shale Oil and Gas Enrichment Mechanisms and Effective Development, SINOPEC, Beijing , China

The preservation of orbital signals in sedimentary records, a crucial aspect for the reliability of astronomical time scales, has been insufficiently explored, presenting challenges in interpretation. In this study, we focus on the effect of inconsistent sedimentation rates on the preservation of these orbital signals from a modeling perspective. We delve into how inconsistent sedimentation rates influence the retention of these orbital signals. Employing stochastic statistical models, our research simulates diverse sedimentary environments, we show that 405-kyr eccentricity tuning is the most reliable approach for constructing ATS among different tuning strategies, particularly in environments characterized by high energy conditions and unsteady sedimentation such as fluvial or deltaic settings. This discovery holds substantial importance in refining geological time scales. We introduce an innovative approach to evaluate sedimentation rates within these records. Our study demonstrates the robustness of the cyclostratigraphic method and deepens our understanding of the preservation of sedimentary records, thereby enriching our grasp of Earth's intricate geological past.

How to cite: Wang, M., Li, M., Hajek, E. A., Kemp, D. B., Wu, Y., Zhu, H., and Jin, Z.: Detection of orbital signals in the sedimentary record through stochastic statistical modeling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3705, https://doi.org/10.5194/egusphere-egu24-3705, 2024.