Visualization as a Big Data Artefact for Knowledge Interpretation of Digital Petroleum Ecosystems
In the current upstream business environment, we examine the risk involved in the petroleum exploration and field development. Many sedimentary basins worldwide possess hundreds of petroleum systems with thousands of oil and gas fields, geographically scattered. A significant amount of unstruct...
| Main Authors: | , |
|---|---|
| Format: | Journal Article |
| Published: |
2017
|
| Online Access: | http://hdl.handle.net/20.500.11937/81150 |
| _version_ | 1848764326477824000 |
|---|---|
| author | Nimmagadda, Shastri Rudra, Amit |
| author_facet | Nimmagadda, Shastri Rudra, Amit |
| author_sort | Nimmagadda, Shastri |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | In the current upstream business environment, we
examine the risk involved in the petroleum exploration
and field development. Many sedimentary basins
worldwide possess hundreds of petroleum systems with
thousands of oil and gas fields, geographically scattered.
A significant amount of unstructured heterogeneous and
multidimensional data are locked up in many industrial
applications and knowledge domains. Our objective is
to bring the relevant data together, integrate and
visualize for adding values to the existing interpretation.
We simulate a Big Data guided digital petroleum
ecosystem (DPE) approach, a digital oil field solution, a
new direction in the analysis of a total petroleum system
(TPS), in which multiple sedimentary basins may have
been grouped, inheriting an interconnectivity between
the systems. The DPE is articulated in a framework,
organizing variety of data associated with the elements
and processes of complex petroleum systems and
integrating their data dimensions and attributes. We
develop an ontology based data warehousing and mining
artefacts. We present warehoused metadata, with slicing
and dicing of data views for visualization of new
prospects in the investigating area. We further
investigate the risk of exploratory drilling campaigns
and how the integrated framework, with visualization
and interpretation artefacts can holistically support the
delivery of high-quality products and services. |
| first_indexed | 2025-11-14T11:17:35Z |
| format | Journal Article |
| id | curtin-20.500.11937-81150 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:17:35Z |
| publishDate | 2017 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-811502021-01-07T07:46:46Z Visualization as a Big Data Artefact for Knowledge Interpretation of Digital Petroleum Ecosystems Nimmagadda, Shastri Rudra, Amit In the current upstream business environment, we examine the risk involved in the petroleum exploration and field development. Many sedimentary basins worldwide possess hundreds of petroleum systems with thousands of oil and gas fields, geographically scattered. A significant amount of unstructured heterogeneous and multidimensional data are locked up in many industrial applications and knowledge domains. Our objective is to bring the relevant data together, integrate and visualize for adding values to the existing interpretation. We simulate a Big Data guided digital petroleum ecosystem (DPE) approach, a digital oil field solution, a new direction in the analysis of a total petroleum system (TPS), in which multiple sedimentary basins may have been grouped, inheriting an interconnectivity between the systems. The DPE is articulated in a framework, organizing variety of data associated with the elements and processes of complex petroleum systems and integrating their data dimensions and attributes. We develop an ontology based data warehousing and mining artefacts. We present warehoused metadata, with slicing and dicing of data views for visualization of new prospects in the investigating area. We further investigate the risk of exploratory drilling campaigns and how the integrated framework, with visualization and interpretation artefacts can holistically support the delivery of high-quality products and services. 2017 Journal Article http://hdl.handle.net/20.500.11937/81150 http://creativecommons.org/licenses/by/4.0/ fulltext |
| spellingShingle | Nimmagadda, Shastri Rudra, Amit Visualization as a Big Data Artefact for Knowledge Interpretation of Digital Petroleum Ecosystems |
| title | Visualization as a Big Data Artefact for Knowledge Interpretation of Digital Petroleum Ecosystems |
| title_full | Visualization as a Big Data Artefact for Knowledge Interpretation of Digital Petroleum Ecosystems |
| title_fullStr | Visualization as a Big Data Artefact for Knowledge Interpretation of Digital Petroleum Ecosystems |
| title_full_unstemmed | Visualization as a Big Data Artefact for Knowledge Interpretation of Digital Petroleum Ecosystems |
| title_short | Visualization as a Big Data Artefact for Knowledge Interpretation of Digital Petroleum Ecosystems |
| title_sort | visualization as a big data artefact for knowledge interpretation of digital petroleum ecosystems |
| url | http://hdl.handle.net/20.500.11937/81150 |