Seismic Data Processing in Oil and Gas Exploration: Methods, Advances, and Innovations for Improving Exploration and Production Efficiencies.

@article{1709676,
      author = {Nyaknno Umoren, Malvern Iheanyichukwu Odum, Iduate Digitemie Jason, Dazok Donald Jambol},
      title = {Seismic Data Processing in Oil and Gas Exploration: Methods, Advances, and Innovations for Improving Exploration and Production Efficiencies.},
      journal = {Iconic Research And Engineering Journals},
      year = {2020},
      volume = {4},
      number = {3},
      pages = {169-179},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1709676.pdf},
      abstract = {Seismic data processing has emerged as a cornerstone of oil and gas exploration, enabling enhanced imaging and interpretation of subsurface geological structures. Recent technological innovations have transformed conventional workflows by integrating artificial intelligence (AI), machine learning, and predictive analytics to optimize seismic signal clarity, reduce noise, and extract critical geological features. In particular, the adoption of real-time geosteering, deep learning models, and IoT-enabled systems has accelerated the detection of hydrocarbon-bearing formations and improved drilling accuracy. This paper reviews contemporary methods and advances in seismic data acquisition, processing, and interpretation, with a focus on the practical application of AI-driven models in exploration campaigns. Drawing from recent frameworks and predictive maintenance strategies, it highlights how data intelligence tools are reshaping seismic workflows for greater efficiency and reduced operational risks. By exploring case studies and conceptual frameworks from Nigeria?s oil and gas industry, the review underscores the pivotal role of innovative data technologies in enhancing exploration success and maximizing production outcomes.},
      keywords = {Seismic Data Processing, Predictive Analytics, Oil and Gas Exploration, Machine Learning, Real-Time Geosteering, Data-Driven Interpretation.},
      month = {September},
  }