Ontology based data warehouse modelling - a methodology for managing petroleum field ecosystems

Abstract

Abstract-Petroleum field ecosystems offer an interesting and productive domain for ontology based data warehousing model and methodology development. This paper explains the opportunities and challenges confronting modellers, methodologists, and managers operating in the petroleum business and provides some detailed techniques and suggested methods for constructing and using the ontology based warehouse. Ecologically sensitive operations such as well drilling, well production, exploration, and reservoir development can be guided and carefully planned based on data mined from a suitable constructed data warehouse. Derivation of business intelligence, simulations and vizualisation can also be driven by online analytical processing based on warehoused data and metadata.

Petroleum Ontology: An effective data integration and mining methodology aiding exploration of commercial petroleum plays

“…These horizons existing in a geological era, are not static, but are part of a dynamic petroleum ecosystem [13]. Warehoused data have been implemented, interpreting several geological structures which are used for prospect generation and evaluation.…”

“…12: Seismic -well -data domain and integration of attribute instances for -Metadata Ontologically, each field interpreted within a petroleum system cannot be isolated, but conceptually and logically, in a strict geological sense, fields are interconnected and communicative to each other by different structural patterns. Ecologically [13], if there is any change in the structural pattern within a field, there is a corresponding affect on the other field or data pattern.…”

“…Acquisition requires many different receiver configurations (sensor dimension), including laying geophones or seismometers (sensor arrays) on the surface of the earth or seafloor, towing hydrophones [1] - [5] behind a marine seismic vessel, suspending hydrophones vertically in the sea or placing geophones in a wellbore (as in a vertical seismic profile, VSP ontology, [6] and [13]) to record the seismic signal. A source (source or shot dimensions), such as a vibrator unit, dynamite shot, or an air gun (array of shots), generates acoustic or elastic vibrations that travel into the Earth, pass through strata with different seismic responses and filtering effects, and return to the surface to be recorded as seismic data.…”

Data warehousing and mining technologies for adaptability in turbulent resources business environments

“…These are classical mining methods, yet to be widely tested in resources business applications. Multidimensional modelling approaches (Nimmagadda and Dreher, 2007a, 2007b, 2008a, 2008b, used for warehousing resources data, are described in Section 4. Flahive et al (2004) and Bhatt et al (2004) describe ontologies in distributed environments.…”

“…As demonstrated in Figure 1, data from operational units gathered and stored in an integrated warehouse from which several data views are extracted for data-mining workflows. Exploration in a resources business is a key generalised dimension, in which hundreds of dimensions and attributes are described (Nimmagadda and Dreher, 2007a, 2007b, 2008b. Several other factors, based on processes in the exploration business from which these data dimensions conceptualised, are narrated in Figure 1.…”