Abstract
The unconventional digital petroleum ecosystems are associated with fractured reservoirs that are usually unpredictable, but can produce for longer periods depending on size of petroleum systems and basins. Currently, conventional reservoirs do produce oil & gas even without integrated workflows and solutions. The heterogeneity and multidimensionality of data sources at times can make the data documentation and integration complicated affecting the exploration and field development. We examine the conventional database technologies and their failures in organizing the data of unconventional digital ecosystems. Big Data driven intelligent information system solutions are needed for addressing the issues of complex data systems of unconventional digital ecosystems. Geographically distributed petroleum systems and their associated reservoirs too demand such integrated and innovative digital ecosystem solutions. We propose an innovative design science information system (DSIS), an integrated digital framework solution to explorers, dealing with unconventional fractured reservoirs. The integrated Big Data analytics solutions are effective in interpreting unconventional digital petroleum ecosystems that are impacted by shale prospect businesses worldwide.
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References
Beaumont, E.A., Foster, N.H.: Exploring for Oil & Gas Traps. In: AAPG Treatise of Petroleum Geology, 2nd edn. Publications of Millennium Edition, Memoir 78, UK (1999)
Brown, D.: Looking Deeper into Fracture Impacts, AAPG Explorer, March Archive, USA (2013)
Carvajal, G., Maucec, M., Cullick, S.: Intelligent Digital Oil and Gas Fields, 1st edn. Gulf Professional Publishing, Elsevier, 374 p. (2017)
Cleary, L., Freed, B., Elke, P.: Big Data Analytics Guide. SAP, CA 94607, USA (2012)
Li, G.: World Atlas of Oil and Gas Basins. Wiley, New York, 496 p. (2011)
Castaneda, G.O.J., Nimmagadda, S.L., Cardona, M., Lobo, A., Darke, K.: On integrated quantitative interpretative workflows for interpreting structural and combinational traps for risk minimizing the exploratory and field development. In: Bolivarian Geophysical Symposium Proceedings, held in Cartagena, Colombia (2012)
Coronel, C., Morris, S.: Database Systems: Design, Implementation, & Management. Cengage Learning US, Edition 12, 784 p. (2016)
Durham, S.L.: An Unconventional Idea, Open to Interpretation. AAPG Explorer, March Series, USA (2013)
Indulska, M., Recker, J.C.: Design SCIENCE in IS research: a literature analysis. In: Gregor, S., Ho, S. (eds.) Proceedings 4th Biennial ANU Workshop on Information Systems Foundations, Canberra, Australia (2008)
Khatri, V., Ram, S.: Augmenting a conceptual model with geo-spatiotemporal annotations. IEEE Trans. Knowl. Data Eng. 16(11), 1324–1338 (2004)
Magoom, L.B., Dow, W.G.: The Petroleum System from Source to Trap, AAPG/Datapages, Digital Reprint of AAPG Memoir 60 (2009)
Nimmagadda, S.L., Rudra, A.: Big data information systems for managing embedded digital ecosystems (EDE), a book chapter in a book entitled. In: Big Data and Learning Analytics in Higher Education: Current Theory and Practice. Springer, The Netherlands (2016). https://doi.org/10.1007/978-3-319-06520-5, ISBN 978-3-319-06519-9
Nimmagadda, S.L., Dreher, H.V.: On new emerging concepts of Petroleum Digital Ecosystem (PDE). J. WIREs Data Mining Knowl. Dis. 2, 457–475 (2012). https://doi.org/10.1002/widm.1070
Nimmagadda, S.L.: Data Warehousing for Mining of Heterogeneous and Multidimensional Data Sources, Verlag Publisher, Scholar Press, OmniScriptum GMBH & CO. KG, Germany, pp. 1–657 (2015)
Parasnis, D.S.: Principles of Applied Geophysics. Chapman & Hall, USA (1997)
Vaishnavi, V., Kuechler, Jr., W.: Design Science Research Methods and Patterns: Innovating Information and Communication Technology, Auerbach Publications, NY, Taylor & Francis Group, Boca Raton, FL (2007)
Wight, A.W.R., Hare, L.H., Reynolds, J.R.: A Sedimentary Basin, NE Kalimantan, Indonesia: a century of exploration and future potential, Geological Society of Malaysia, Circum – Pacific Council for Energy and Mineral Resources (1992)
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Nimmagadda, S.L., Mani, N., Reiners, T. (2019). On Knowledge-Based Design Science Information System (DSIS) for Managing the Unconventional Digital Petroleum Ecosystems. In: Czarnowski, I., Howlett, R., Jain, L., Vlacic, L. (eds) Intelligent Decision Technologies 2018. KES-IDT 2018 2018. Smart Innovation, Systems and Technologies, vol 97. Springer, Cham. https://doi.org/10.1007/978-3-319-92028-3_13
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DOI: https://doi.org/10.1007/978-3-319-92028-3_13
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