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Geological Characterization of the 3D Seismic Record within the Gas Bearing Upper Miocene Sediments in the Northern Part of the Bjelovar Subdepression—Application of Amplitude Versus Offset Analysis and Artificial Neural Network

Author

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  • Tihana Ružić

    (INA-Industry of Oil Plc., Avenija Većeslava Holjevca 10, 10000 Zagreb, Croatia)

  • Marko Cvetković

    (Faculty of Mining, Geology and Petroleum Engineering, University of Zagreb, Pierottijave 6, 10000 Zagreb, Croatia)

Abstract

As natural gas reserves are generally decreasing there is a need to successfully characterize potential research objects using geophysical data. Presented is a study of amplitude vs. offset, attribute and artificial neural network analysis on a research area of a small gas field with one well with commercial accumulations and two wells with only gas shows. The purpose of the research is to aid in future well planning and to distinguish the geophysical data in dry well areas with those from an economically viable well. The amplitude vs. offset analysis shows the lack of anomaly in the wells with only gas shows while the anomaly is present in the economically viable well. The artificial neural network analysis did not aid in the process of distinguishing the possible gas accumulation but it can point out the sedimentological and structural elements within the seismic volume.

Suggested Citation

  • Tihana Ružić & Marko Cvetković, 2021. "Geological Characterization of the 3D Seismic Record within the Gas Bearing Upper Miocene Sediments in the Northern Part of the Bjelovar Subdepression—Application of Amplitude Versus Offset Analysis a," Energies, MDPI, vol. 14(14), pages 1-16, July.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:14:p:4161-:d:591734
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    References listed on IDEAS

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    1. Marko Cvetković & Bojan Matoš & David Rukavina & Iva Kolenković Močilac & Bruno Saftić & Tomislav Baketarić & Marija Baketarić & Ivor Vuić & Andrej Stopar & Anja Jarić & Tomislav Paškov, 2019. "Geoenergy potential of the Croatian part of Pannonian Basin: insights from the reconstruction of the pre-Neogene basement unconformity," Journal of Maps, Taylor & Francis Journals, vol. 15(2), pages 651-661, July.
    2. Nilesh Dixit & Paul McColgan & Kimberly Kusler, 2020. "Machine Learning-Based Probabilistic Lithofacies Prediction from Conventional Well Logs: A Case from the Umiat Oil Field of Alaska," Energies, MDPI, vol. 13(18), pages 1-15, September.
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