Bernt Helge Hansen (StatoilHydro) presented the common oil and gas ontology, a component of the Norwegian OLF trade body-sponsored integrated operations project. The aim of integrated operations (IO) is for all fields and facilities to be compliant with the program and to develop a global IO support network. IO promises a ‘revolution in our way of working.’ Enablers are the semantic web, ISO15926 and other oil and gas ontologies and XML schemas. Project scope includes drilling, reservoir and production, operations and maintenance. Smart web services will move real time data from the historian to applications covering the whole range of oilfield activities from condition-based maintenance to fiscal metering.
Automation, automation ...
For Einar Landre (StatoilHydro), both the rationale for IO and the means are clear. An OLF study estimated that IO could produce savings of around $60 billion on the Norwegian continental shelf. The means are twofold first generation IO, which is well underway, involves moving work onshore, leveraging a high bandwidth infrastructure. Generation 2 IO involves more advanced solutions for information management, automation and ‘autonomy.’ Landre believes that in general, people make inferior decisions and that automation is the way forward. But today’s software was not designed for this. ‘We are trying to solve a set of non trivial problems on the boundary of research in IT.’ The answers lie in large scale networked systems, machine learning, Bayesian uncertainties and the Semantic Web.
‘Buzzword-compliant‘
Early work focuses on ‘socio-technical’ systems that combine humans and machines working to achieve common goals. Automation offloads the human element, making experts available to work on the ‘hard stuff.’ One persistent problem is the ‘buzzword compliant’ vendor. Here Landre suggests a standards based approach (using the IEEE 1471 recommended practice for architectural description of IT systems.) The aim is to extend from the IO feasibility project, building on IIP, ISO 15926, ProdML, DISKOS etc. The semantic model has proved a valuable to link data sources—solving the legacy systems and heterogeneous data sources issues.
High North
Nowhere is automation more important than in Norway’s high north. A new joint industry project is just kicking off to investigate second generation integrated operations—i.e. automation. The $18 million project is headed up by Nils Sandsmark. The high north was chosen because fields will be seabed completed and operations may be thousands of kilometers from the shore. Fields will be highly instrumented and digital with autonomous subsea controls and networks. Such remote operations will be challenging from the standpoint of security and regulations and will require a ‘zero’ environmental impact. ISO 15926 is to be extended to production optimization and real time data quality assurance. Model-based prediction and ‘smart agents’ technology also ran. The JIP is also to study the convergence of various XML formats (ProdML, daily, monthly production reporting etc.) into ISO 15926 which will then be extended to cover production optimization and readied for automated reasoning by ‘smart agents.’
DFKI
Semantic Web guru Leo Sauerman of the German DFKI artificial intelligence R&D center offered a backgrounder on deployment outside of oil and gas. For Sauerman, the semantic web promises ‘a consistent data model for integration of content from different organizations, providers, departments, disparate data sources and legacy data.’ Multilingual taxonomies use the user’s terminology and are queried by the ‘expressive’ sparql language. Extensible metadata incorporates unanticipated data sets, new requirements do not change code. Current semweb projects include WorldNet, US Census Data, Flickr Exporter, OntoWorld, RDF Book Mashup, DBPedia and ‘friend of a friend.’ Open linked data now includes some 2 billion ‘facts’ and 680 thousand ‘links.’ In a March 2008 announcement, Yahoo unveiled the Search Open Ecosystem, including support for semantic web standards. Other applications cited by Sauermann included Vodaphone Live which uses an RDF vocabulary for ringtones, metadata and content ratings. RDF has been used since 2000 by the Mozilla internet browser to configure its plugins.
Petronas
ISO 15926 and semantic technology is not restricted to Norway as Wan Hassan Wan Mamat (Petronas) demonstrated. Petronas shares the vision for an industry standard data model based on ISO 15926. The Petronas Carigali information model (PCIM) builds on ALCIM’s ‘myCIS’ Integrated Engineering and Asset Management data model and ISO 15926 reference data library. This covers front end engineering design, process control, electrical and instrumentation. 3D data model translations between applications go through IS5926 and an XMpLant interface. Compliance is mandatory for Petronas’ contractors. Like Norway, Petronas has an integrated operations center ‘PViC’ located in the Petronas twin towers which control operations on the Tangga Barat and Kumang fields.
National Oilwell Varco
Henning Jansen (National Oilwell Varco) believes that the Norwegian Continental Shelf is a world leader in high tech drilling and onshore drilling centers with real time decision making. Protocols such as WITSML, WITS, OPC, ODBC allow for the integration of independent service providers each with their own tools and platforms. While data exchange standards like WITSML are good, true integration remains elusive. So DNV created the PCA Drilling special interest group in 2007 and is working on an ISO 15926 ontology for drilling with participation from StatoilHydro, BP and ConocoPhillips.
DNV
Johan Wilhelm Kluever reported on the progress of the modeling, methodology and technology (MMT) special interest group. The MMT SIG works on the establishment and maintenance of correct and reliable reference data. Ontologies are used to record factual statements from domain experts. These are machine translated into a precise statement in the ontology. The MMT SIG cuts across other PCA activities, focusing on ISO 15926 Part 2—i.e. the data model and upper ontology. Part 2 has a ‘canonical’ described in the Express data modeling language with current implementations in OWL. A software development Wiki is available on trac.posccaesar.org.
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