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dc.contributor.authorNimmagadda, Shastri
dc.contributor.authorAseev, A.
dc.identifier.citationNimmagadda, S.L. and Aseev, A. 2017. Big data role in the upstream business research. In: Third EAGE Workshop on High Performance Computing for Upstream, 1-4 Oct 2017, Athens, Greece.

An offshore petroleum is the main focus of the current research with Big Data and high performance computing motivations in the study area. We undertake a joint exploration study focusing on Romanian offshore Black Sea (Western) basin, using volumes and varieties of datasets in a Big Data scale. The exploration datasets include more than 175 2D seismic lines, 30 km2 of 3D seismic data, information on more than 8 exploratory drilled wells including check-shot and VSP data including existing petrophysical and production data. Big Data opportunities are explored in the current upstream business research by proposing data modelling, visualization and data interpretation schemes. In spite of the data quality issues in the study area, several isochrones, isochores and other geological information are integrated and made based on which depositional models are drawn for risk minimizing the exploration and field development plans. The conclusions are based on structural, strati-structural interpretation, organic geochemistry and identification of new opportunity areas. Several data models, visualization and interpretation artefacts can handle the volumes and varieties in Big Data scale minimizing the risk involved in the upstream business in the investigating area. Several new opportunities are identified in the shelf, slope and deep marine areas.

dc.titleBig data role in the upstream business research
dc.typeConference Paper
dcterms.source.title3rd EAGE Workshop on High Performance Computing for Upstream 2017
dcterms.source.conferenceThird EAGE Workshop on High Performance Computing for Upstream
dcterms.source.conference-start-date1 Oct 2017
dcterms.source.conferencelocationAthens, Greece
curtin.departmentSchool of Management
curtin.accessStatusFulltext not available
curtin.facultyFaculty of Business and Law
curtin.contributor.orcidNimmagadda, Shastri [0000-0002-0841-6727]
dcterms.source.conference-end-date4 Oct 2017
curtin.contributor.scopusauthoridNimmagadda, Shastri [23490052500]

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