Multidimentional Data Warehousing and mining - an Approach for Managing Multiple Reservoir Ecosystems

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...

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Main Authors: Nimmagadda, Shastri, Dreher, Heinz, Shtukert, O., Zolotoi, N.
Other Authors: Luis Gomes
Format: Conference Paper
Published: IEEE 2013
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/35809
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author Nimmagadda, Shastri
Dreher, Heinz
Shtukert, O.
Zolotoi, N.
author2 Luis Gomes
author_facet Luis Gomes
Nimmagadda, Shastri
Dreher, Heinz
Shtukert, O.
Zolotoi, N.
author_sort Nimmagadda, Shastri
building Curtin Institutional Repository
collection Online Access
description 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.
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spelling curtin-20.500.11937-358092023-02-13T08:01:34Z Multidimentional Data Warehousing and mining - an Approach for Managing Multiple Reservoir Ecosystems Nimmagadda, Shastri Dreher, Heinz Shtukert, O. Zolotoi, N. Luis Gomes Michael Huebner datawarehousing sedimentary basin data mining digital ecosystem ontology 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. 2013 Conference Paper http://hdl.handle.net/20.500.11937/35809 10.1109/INDIN.2013.6622940 IEEE restricted
spellingShingle datawarehousing
sedimentary basin
data mining
digital ecosystem
ontology
Nimmagadda, Shastri
Dreher, Heinz
Shtukert, O.
Zolotoi, N.
Multidimentional Data Warehousing and mining - an Approach for Managing Multiple Reservoir Ecosystems
title Multidimentional Data Warehousing and mining - an Approach for Managing Multiple Reservoir Ecosystems
title_full Multidimentional Data Warehousing and mining - an Approach for Managing Multiple Reservoir Ecosystems
title_fullStr Multidimentional Data Warehousing and mining - an Approach for Managing Multiple Reservoir Ecosystems
title_full_unstemmed Multidimentional Data Warehousing and mining - an Approach for Managing Multiple Reservoir Ecosystems
title_short Multidimentional Data Warehousing and mining - an Approach for Managing Multiple Reservoir Ecosystems
title_sort multidimentional data warehousing and mining - an approach for managing multiple reservoir ecosystems
topic datawarehousing
sedimentary basin
data mining
digital ecosystem
ontology
url http://hdl.handle.net/20.500.11937/35809