DocumentCode :
641255
Title :
Multidimensional data warehousing and mining - An approach for managing multiple reservoir ecosystems
Author :
Nimmagadda, Shastri L. ; Dreher, Heinz V. ; Shtukert, Olga ; Zolotoi, Nikita
Author_Institution :
PTS, Schlumberger, Moscow, Russia
fYear :
2013
fDate :
29-31 July 2013
Firstpage :
529
Lastpage :
534
Abstract :
Many sedimentary basins comprise of numerous oil and gas fields. Each field has multiple oil and gas producing wells and each drilled well has multiple reservoir pay zones, with each pay zone having different fluids - either oil or gas and both. From a sedimentary basin scale, a super-type dimension is distinguished into its atomic and non-divisible dimensions, such as reservoir and structure. In database terminology, cardinality is representative of the set of elements-, and attributes and their relationships. Here, each element is interpreted as a dimension, narration of multiple dimensions for multiple elements within the context of a petroleum ecosystem. Ontology based cardinalities are described for designing constraints and business rules among multidimensional data models, to maintain integrity and consistency of the cardinalities. For the purpose of analyzing petroleum ecosystem and its reservoir connectivity, ontologies based cardinalities are described. Though sedimentary-basin ontology narrates, connectivity among structures, reservoirs, seals, source and other processes, such as migration and timing of occurrence or existence of these elements, but we focus on an approach exploring connections among multiple reservoirs and traps within a petroleum ecosystem. This approach minimizes the ambiguity during interpretation and management of reservoir ecosystems´ limits or boundaries.
Keywords :
data mining; data warehouses; ecology; hydrocarbon reservoirs; ontologies (artificial intelligence); petroleum industry; sediments; atomic dimensions; business rules; cardinality consistency; cardinality integrity; gas fields; gas producing wells; multidimensional data mining; multidimensional data models; multidimensional data warehousing; multiple reservoir ecosystem management; multiple reservoir pay zones; nondivisible dimensions; oil fields; oil producing wells; ontology-based cardinalities; petroleum ecosystem; reservoir connectivity; sedimentary-basin ontology; Data mining; Ecosystems; Ontologies; Petroleum; Reservoirs; Rocks; Seals; data mining; datawarehousing; digital ecosystem; ontology; sedimentary basin;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Informatics (INDIN), 2013 11th IEEE International Conference on
Conference_Location :
Bochum
Type :
conf
DOI :
10.1109/INDIN.2013.6622940
Filename :
6622940
Link To Document :
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