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<p>The Cretaceous-Paleogene (K-Pg) boundary is one of the most dramatic climate changes on Earth, but its impact on the development of hydrocarbon source rocks is not adequately known on a global scale in the sedimentary basins of the world. The paper provides a multi-proxy analysis of the source rocks of five sedimentary basins in Nigeria, which incorporates an organic and inorganic geochemistry, quantitative palynology, sequence stratigraphy, and machine learning methods to determine the paleo-environment and hydrocarbon generation potential. The study employs a dataset of 247 samples, based on systematic variations in organic matter preservation and thermal maturity that directly correlate with global climate fluctuations during the Late Cretaceous through Paleocene interval. The biomarker distributions indicate enhanced preservation of Type II organic matter during cooler climatic intervals. Statistical clustering of geochemical parameters defines 4 different hydrocarbon system archetypes, which are associated with certain paleoclimatic conditions. Basin modeling reveals that optimal source rock development occurred during transitional climate phases, with total organic carbon values greater than 3.5wt% and hydrogen indices averaging 420&#xa0;mg HC/g TOC. Machine learning algorithms successfully predict source rock quality with 87% accuracy using integrated paleoenvironmental proxies. The framework provides quantitative methods to predicts the distribution of the source rocks in the underexplored basins across the globe using paleoclimatic and geochemical proxies, advancing the petroleum exploration strategies and interactions between the Earth system during the significant climate shifts.</p>

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Machine learning applications in hydrocarbon system evolution: predictive basin modeling of cretaceous-paleogene source rocks in Nigerian sedimentary basins using integrated multi-proxy analysis

  • 期刊论文

  • 发表日期：

    2026年4月21日

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  • G. O. Aigbadon,
  • A. Ogbamikhumi,
  • D. J. Koffa,
  • N. S. Igbinigie,
  • A. Ocheli,
  • O. C. Akakuru,
  • B. Overare,
  • A. I. Obasi,
  • E. O. Akudo,
  • S. O. Onyekuru,
  • J. B. Ahmed II,
  • A. O. Usman,
  • E. O. Avwenagha,
  • D. O. Igwe

摘要

The Cretaceous-Paleogene (K-Pg) boundary is one of the most dramatic climate changes on Earth, but its impact on the development of hydrocarbon source rocks is not adequately known on a global scale in the sedimentary basins of the world. The paper provides a multi-proxy analysis of the source rocks of five sedimentary basins in Nigeria, which incorporates an organic and inorganic geochemistry, quantitative palynology, sequence stratigraphy, and machine learning methods to determine the paleo-environment and hydrocarbon generation potential. The study employs a dataset of 247 samples, based on systematic variations in organic matter preservation and thermal maturity that directly correlate with global climate fluctuations during the Late Cretaceous through Paleocene interval. The biomarker distributions indicate enhanced preservation of Type II organic matter during cooler climatic intervals. Statistical clustering of geochemical parameters defines 4 different hydrocarbon system archetypes, which are associated with certain paleoclimatic conditions. Basin modeling reveals that optimal source rock development occurred during transitional climate phases, with total organic carbon values greater than 3.5wt% and hydrogen indices averaging 420 mg HC/g TOC. Machine learning algorithms successfully predict source rock quality with 87% accuracy using integrated paleoenvironmental proxies. The framework provides quantitative methods to predicts the distribution of the source rocks in the underexplored basins across the globe using paleoclimatic and geochemical proxies, advancing the petroleum exploration strategies and interactions between the Earth system during the significant climate shifts.