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<p>This study presents a systematic review of cognitive computing applications in reservoir characterization and exploration optimization. Using a PRISMA-guided literature review of more than 180 peer-reviewed studies published between 1980 and 2025, we evaluate how cognitive systems integrate machine learning, natural language processing, and reasoning frameworks to support subsurface decision-making. The review synthesizes applications including seismic facies classification, intelligent well-log correlation, petrophysical property prediction, and integrated geological modeling. Beyond summarizing existing work, the study proposes a conceptual cognitive workflow for petroleum data integration and highlights emerging research directions, including explainable AI, hybrid human-AI decision systems, and digital twin integration.</p>

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A systematic review of cognitive computing for reservoir characterisation and exploration optimisation

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月16日

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  • Fossong Guilianno,
  • Kingsley Onyekwere Okengwu,
  • Ugochi Adaku Okengwu

摘要

This study presents a systematic review of cognitive computing applications in reservoir characterization and exploration optimization. Using a PRISMA-guided literature review of more than 180 peer-reviewed studies published between 1980 and 2025, we evaluate how cognitive systems integrate machine learning, natural language processing, and reasoning frameworks to support subsurface decision-making. The review synthesizes applications including seismic facies classification, intelligent well-log correlation, petrophysical property prediction, and integrated geological modeling. Beyond summarizing existing work, the study proposes a conceptual cognitive workflow for petroleum data integration and highlights emerging research directions, including explainable AI, hybrid human-AI decision systems, and digital twin integration.