Data geo-Science Approach for Modelling Unconventional Petroleum Ecosystems and their Visual Analytics
Storage, integration and interoperability are critical challenges in the unconventional exploration data management. With a quest to explore unconventional hydrocarbons, in particular, shale gas from fractured shales, we aim at investigating new petroleum data geoscience approaches. The data ge...
| Main Authors: | , , , |
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| Format: | Conference Paper |
| Published: |
2021
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| Online Access: | http://hdl.handle.net/20.500.11937/86495 |
| _version_ | 1848764838492241920 |
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| author | Nimmagadda, Shastri Ochan, Andrew Namugenyi, Christine Reiners, Torsten |
| author_facet | Nimmagadda, Shastri Ochan, Andrew Namugenyi, Christine Reiners, Torsten |
| author_sort | Nimmagadda, Shastri |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Storage, integration and interoperability are critical
challenges in the unconventional exploration data
management. With a quest to explore unconventional
hydrocarbons, in particular, shale gas from fractured shales,
we aim at investigating new petroleum data geoscience
approaches. The data geo-science describes the
integration of geoscience-domain expertise, collaborating
mathematical concepts, computing algorithms, machine learning
tools, including data and business analytics.
Further, to strengthen data-science services among
producing companies, we propose an integrated
multidimensional repository system, for which factual
instances are acquired on gas shales, to store, process and
deliver fractured-data views in new knowledge domains.
Data dimensions are categorized to examine their
suitability in the integrated prototype articulations that use
fracture-networks and attribute dimension model
descriptions. The factual instances are typically from
seismic attributes, seismically interpreted geological
structures and reservoirs, well log, including production
data entities. For designing and developing
multidimensional repository systems, we create various
artefacts, describing conceptual, logical and physical
models. For exploring the connectivity between seismic
and geology entities, multidimensional ontology models
are construed using fracture network attribute dimensions
and their instances. Different data warehousing and mining
are added support to the management of ontologies that can
bring the data instances of fractured shales, to unify and
explore the associativity between high-dense fractured
shales and their orientations.
The models depicting collaboration of geology,
geophysics, reservoir engineering and geo-mechanics
entities and their dimensions can substantially reduce the
risk and uncertainty involved in modelling and interpreting
shale- and tight-gas reservoirs, including traps associated
with Coal Bed Methane (CBM). Anisotropy, Poisson's
ratio and Young's modulus properties corroborate the
interpretation of stress images from the 3D acoustic
characterization of shale reservoirs. The statistical analysis
of data-views, their correlations and patterns further
facilitate us to visualize and interpret geoscientific
metadata meticulously. Data geo-science guided integrated
methodology can be applied in any basin, including frontier
basins. |
| first_indexed | 2025-11-14T11:25:43Z |
| format | Conference Paper |
| id | curtin-20.500.11937-86495 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:25:43Z |
| publishDate | 2021 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-864952022-01-20T02:40:48Z Data geo-Science Approach for Modelling Unconventional Petroleum Ecosystems and their Visual Analytics Nimmagadda, Shastri Ochan, Andrew Namugenyi, Christine Reiners, Torsten Storage, integration and interoperability are critical challenges in the unconventional exploration data management. With a quest to explore unconventional hydrocarbons, in particular, shale gas from fractured shales, we aim at investigating new petroleum data geoscience approaches. The data geo-science describes the integration of geoscience-domain expertise, collaborating mathematical concepts, computing algorithms, machine learning tools, including data and business analytics. Further, to strengthen data-science services among producing companies, we propose an integrated multidimensional repository system, for which factual instances are acquired on gas shales, to store, process and deliver fractured-data views in new knowledge domains. Data dimensions are categorized to examine their suitability in the integrated prototype articulations that use fracture-networks and attribute dimension model descriptions. The factual instances are typically from seismic attributes, seismically interpreted geological structures and reservoirs, well log, including production data entities. For designing and developing multidimensional repository systems, we create various artefacts, describing conceptual, logical and physical models. For exploring the connectivity between seismic and geology entities, multidimensional ontology models are construed using fracture network attribute dimensions and their instances. Different data warehousing and mining are added support to the management of ontologies that can bring the data instances of fractured shales, to unify and explore the associativity between high-dense fractured shales and their orientations. The models depicting collaboration of geology, geophysics, reservoir engineering and geo-mechanics entities and their dimensions can substantially reduce the risk and uncertainty involved in modelling and interpreting shale- and tight-gas reservoirs, including traps associated with Coal Bed Methane (CBM). Anisotropy, Poisson's ratio and Young's modulus properties corroborate the interpretation of stress images from the 3D acoustic characterization of shale reservoirs. The statistical analysis of data-views, their correlations and patterns further facilitate us to visualize and interpret geoscientific metadata meticulously. Data geo-science guided integrated methodology can be applied in any basin, including frontier basins. 2021 Conference Paper http://hdl.handle.net/20.500.11937/86495 fulltext |
| spellingShingle | Nimmagadda, Shastri Ochan, Andrew Namugenyi, Christine Reiners, Torsten Data geo-Science Approach for Modelling Unconventional Petroleum Ecosystems and their Visual Analytics |
| title | Data geo-Science Approach for Modelling Unconventional
Petroleum Ecosystems and their Visual Analytics |
| title_full | Data geo-Science Approach for Modelling Unconventional
Petroleum Ecosystems and their Visual Analytics |
| title_fullStr | Data geo-Science Approach for Modelling Unconventional
Petroleum Ecosystems and their Visual Analytics |
| title_full_unstemmed | Data geo-Science Approach for Modelling Unconventional
Petroleum Ecosystems and their Visual Analytics |
| title_short | Data geo-Science Approach for Modelling Unconventional
Petroleum Ecosystems and their Visual Analytics |
| title_sort | data geo-science approach for modelling unconventional
petroleum ecosystems and their visual analytics |
| url | http://hdl.handle.net/20.500.11937/86495 |