Ontology based data warehousing for mining of heterogeneous and multidimensional data sources

Heterogeneous and multidimensional big-data sources are virtually prevalent in all business environments. System and data analysts are unable to fast-track and access big-data sources. A robust and versatile data warehousing system is developed, integrating domain ontologies from multidimensional data sources. For example, petroleum digital ecosystems and digital oil field solutions, derived from big-data petroleum (information) systems, are in increasing demand in multibillion dollar resource businesses worldwide. This work is recognized by Industrial Electronic Society of IEEE and appeared in more than 50 international conference proceedings and journals

On Big Data guided Unconventional Digital Ecosystems and their Knowledge Management

Establishing the reservoir connections is paramount in exploration and exploitation of unconventional petroleum systems and their reservoirs. In Big Data scale, multiple petroleum systems hold volumes and varieties of data sources. The connectivity between petroleum reservoirs and their existence in a single petroleum ecosystem is often ambiguously interpreted. They are heterogeneous and unstructured in multiple domains. They need better data integration methods to interpret the interplay between elements and processes of petroleum systems. Largescale infrastructure is needed to build data relationships between different petroleum systems. The purpose of the research is to establish the connectivity between petroleum systems through resource data management and visual analytics. We articulate a Design Science Information System (DSIS) approach, bringing various artefacts together from multiple domains of petroleum provinces. The DSIS emerges as a knowledge-based digital ecosystem innovation, justifying its need, connecting geographically controlled petroleum systems and building knowledge of oil and gas prospects

GeoFault: A well-founded fault ontology for interoperability in geological modeling

Geological modeling currently uses various computer-based applications. Data harmonization at the semantic level by means of ontologies is essential for making these applications interoperable. Since geo-modeling is currently part of multidisciplinary projects, semantic harmonization is required to model not only geological knowledge but also to integrate other domain knowledge at a general level. For this reason, the domain ontologies used for describing geological knowledge must be based on a sound ontology background to ensure the described geological knowledge is integratable. This paper presents a domain ontology: GeoFault, resting on the Basic Formal Ontology BFO (Arp et al., 2015) and the GeoCore ontology (Garcia et al., 2020). It models the knowledge related to geological faults. Faults are essential to various industries but are complex to model. They can be described as thin deformed rock volumes or as spatial arrangements resulting from the different displacements of geological blocks. At a broader scale, faults are currently described as mere surfaces, which are the components of complex fault arrays. The reference to the BFO and GeoCore package allows assigning these various fault elements to define ontology classes and their logical linkage within a consistent ontology framework. The GeoFault ontology covers the core knowledge of faults 'strico sensu,' excluding ductile shear deformations. This considered vocabulary is essentially descriptive and related to regional to outcrop scales, excluding microscopic, orogenic, and tectonic plate structures. The ontology is molded in OWL 2, validated by competency questions with two use cases, and tested using an in-house ontology-driven data entry application. The work of GeoFault provides a solid framework for disambiguating fault knowledge and a foundation of fault data integration for the applications and the users

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 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

On data integration workflows for an effective management of multidimensional petroleum digital ecosystems in Arabian Gulf Basins

Data integration of multiple heterogeneous datasets from multidimensional petroleum digital ecosystems is an effective way, for extracting information and adding value to knowledge domain from multiple producing onshore and offshore basins. At present, data from multiple basins are scattered and unusable for data integration, because of scale and format differences. Ontology based warehousing and mining modeling are recommended for resolving the issues of scaling and formatting of multidimensional datasets, in which case, seismic and well-domain datasets are described. Issues, such as semantics among different data dimensions and their associated attributes are also addressed by Ontology modeling.Intelligent relationships are built among several petroleum system domains (structure, reservoir, source and seal, for example) at global scale and facilitated the integration process among multiple dimensions in a data warehouse environment. For this purpose, integrated workflows are designed for capturing and modeling unknown relationships among petroleum system data attributes in interpretable knowledge domains.This study is an effective approach in mining and interpreting data views drawn from warehoused exploration and production metadata, with special reference to Arabian onshore and offshore basins

On new emerging concepts of modeling petroleum digital ecosystems by multidimensional data warehousing and mining approaches

Petroleum system and its ingredients are narrated for each and every oil and gas field in each and everypetroleum-bearing sedimentary basin. A new concept of ecosystem and its digitization are emerging within the generic petroleum system. Significance of this concept is to make connectivity among petroleum systems through attributes of ingredients and their contextualization and specification. Most popularly known ingredients are geological structure, reservoir, source and seal rocks. Other ingredients involved are in the form of process of these ingredients such as maturation (of source rocks) and migration and timing (of formation of structure, reservoir and seal rocks). One can notice the connectivity among primary petroleum system ingredients, through different processes, such as maturation of source rocks and charging capability and migration of hydrocarbons into suitablestructural (structure) entrapment areas of reservoir. Unless the phenomenon of interconnectivity is understood; integration between ingredients and processes in the context of digital representation and visualization, petroleum system existence and its survival cannot be well explained. Its value cannot beadded in terms of petroleum accumulations and volumes, unless these phenomena are explicit. Authors propose ontology based data warehousing and data mining technologies, in which, conceptualization and contextualization of multiple data dimensions (petroleum system?s ingredients and processes), integration (within data warehouse environment) and data mining of interpretable emerging petroleum digital ecosystems are accomplished. Multidimensional data warehousingand mining facilitate an effective interpretation of petroleum systems, minimizing the ambiguities involved during structure and reservoir qualifications and quantifications

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

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

Improving interoperability on industrial standards through ontologies

Interoperability refers to the effective exchange of information and understanding to collectively pursue common objectives. System developers commonly use ontologies to enhance semantic and syntactic interoperability within this context. This work aims to evaluate the contribution of ontology in making explicit the meaning of the entities described in a Piping and Instrumentation Diagram (P&ID) model and to provide an architecture that allows the representation of a P&ID in ontological knowledge bases. To understand the semantics of the P&ID entities and relations, we map each class of the P&ID to the corresponding entity of the Offshore Petroleum Production Plant Ontology (O3PO). The ontology describes the definition of each vocable associated with the axioms that clarify and regulate the meaning and utilization of this vocabulary. We intend to guarantee that the integration of P&ID with other models respects the original semantics and avoids unintended data exchanges. We follow this ontological analysis with a case study of a model that conforms to the Data Exchange in the Process Industry (DEXPI) specification, intended to provide homogeneous data interchange between CAD systems from diverse vendors. The ontological analysis of the DEXPI P&ID specification, to build a relation with a well-founded ontology, raises a set of desirable properties for a model intended for use in interoperability. While achieving technical interoperability between DEXPI P&IDs and ontologies represented in OWL is evident, we identified several challenges within the realm of semantic interoperability, specifically concerning clarity/intelligibility, conciseness, extendibility, consistency, and essence. These issues present significant hurdles to achieving seamless systems integration. Moreover, if the DEXPI standard were to evolve into a de facto standard for representing P&IDs across a broader range of domains than initially intended, these highlighted issues could potentially bottleneck its adoption and hinder its integration into different systems.Interoperabilidade se refere à troca efetiva de informação e entendimento na busca por objetivos comuns. Neste contexto, desenvolvedores de sistemas comumente utilizam ontologias para aprimorar a interoperabilidade semântica e sintática. O objetivo deste trabalho é avaliar a contribuição da ontologia para tornar explícito o significado das entidades descritas em um modelo de Diagrama de Tubulação e Instrumentação (DTI) e fornecer uma arquitetura que permita a representação de um DTI em bases de conhecimento ontológicas. Para entender a semântica das entidades e relações do DTI, mapeamos cada classe do DTI para a entidade correspondente da Ontologia de Planta de Produção de Petróleo Offshore (O3PO). A ontologia descreve a definição de cada vocábulo associado com os axiomas que esclarecem e regulam o significado e a utilização desse vocabulário. Pretendemos garantir que a integração do DTI com outros modelos respeite a semântica original e, assim, evite trocas de dados não intencionais. Seguimos essa análise ontológica com um estudo de caso de um modelo que se conforma à especificação "Data Exchange in the Process Industry" (DEXPI), destinada a fornecer uma troca de dados homogênea entre sistemas CAD de diversos fabricantes. A análise ontológica da especificação DEXPI DTI, para construir uma relação com uma ontologia bem fundamentada, levanta um conjunto de propriedades desejáveis para um modelo destinado a ser usado na interoperabilidade. Embora a conquista da interoperabilidade técnica entre DTIs DEXPI e ontologias representadas em OWL seja evidente, diversos desafios foram identificados no âmbito da interoperabilidade semântica, especificamente em relação à clareza/inteligibilidade, concisão, extensibilidade, consistência e essência. Essas questões representam obstáculos significativos para alcançar uma integração de sistemas perfeita. Além disso, se o padrão DEXPI evoluir para um padrão de facto para a representação de DTIs em um conjunto mais amplo de domínios do que inicialmente pretendido, essas questões destacadas poderiam potencialmente atrasar sua adoção e dificultar sua integração em sistemas diferentes

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio