Ontology based data warehouse modeling for managing carbon emissions in safe and secure geological storages

Abstract

The carbon emissions are flooding into the atmosphere because of modern industry activities, burning of fossil fuels, land cleaning (etc.), contributing to global warming and associated climatic changes. These emissions are in the form of CO2. Hydrocarbon seeps, gas chimneys, exposure of geological structures on the earth's surface may also be causing carbon evaporations into the atmosphere. Presently, the salient issue is how to control and manage the carbon emissions. Capturing and storing these carbon emissions into sub-surface geological structural highs are typical solutions for million of years into the future. These solutions are derived through a process of geosequestration, which has been evolved from methodical views of ecology (ecosystems surrounding the sources of CO2 emitters), petroleum systems, geology, geophysics and geomorphology. In the present study, the authors propose an ontology based warehouse modeling of multiple data dimensions acquired from different knowledge domains. In geological and geophysical exploration domains, multiple data dimensions (entities/objects) are described and documented as done by numerous petroleum exploration companies. For example, geological structures and quality reservoirs are key domains, which are prerequisites for any geological storage. Several issues and challenges, faced by oil and gas industries, especially the data associated with carbon emissions - their data organization and management, are briefly discussed. Ontology focuses issues of semantics, conceptualization, and contextualization, while organizing exploration data dimensions. Data relationships that have been conceptualized are denormalized to attain fine-grained data structuring, which subsequently facilitate data mining and data visualization procedures. Several multidimensional star and snow-flake schemas are constructed to address the issues of data organization associated with current carbon emissions in the oil and gas industries and also manufacturing industries. The data structures that belong to different domain ontologies, are integrated in a warehouse environment. Data views extracted from these warehouse models are interpreted in the form of geological structures. Our study also ensures that these carbon emission storages are free from adverse structures, fractures and fissures, which otherwise causative to carbon leaks and emissions.