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Collaborating Authors
Managing and Orchestrating Multi-Vendor Intelligent Oil Field Technology Environment to Enable Efficient Next Generation Production and Reservoir Management Workflows
David, Richard Mohan (Abu Dhabi Company for Onshore Petroleum Operations Ltd. (ADCO)) | Rao, Subba Rama (Abu Dhabi Company for Onshore Petroleum Operations Ltd. (ADCO)) | Reddicharla, Nagaraju (Abu Dhabi Company for Onshore Petroleum Operations Ltd. (ADCO))
Abstract E&P companies are increasingly instrumenting its fields and introducing new technologies with the objective to proactively monitor and surveillance of its wells, reservoir, and facilities for better operations and management. This brings in wide variety of technologies from multiple vendors in providing smart sensors, downhole equipment, instruments, and solutions along with existing legacy systems to support the digital journey. These technology implementations enable improvement in specific areas of the operations. However, in order to continuously build the digital infrastructure and realize its full potential, it requires seamless integration of real time data, technologies, workflows and business process. There is no single vendor integrated solution that covers the entire spectrum of the digital oil field environment. In this scenario, in general the operating companies have the key role to orchestrate these technology components to achieve the integration and seamless workflows. This paper discusses the business need of an Integrated Digital Oil Field Foundation (IDOFF) Framework (based on industry standards and protocols shall form the core foundation that integrates next generation products, technologies of the multi-vendor digital environment enabling smart workflows including in-house solutions. The IDOFF shall comprise of data standards, business process, data model and architecture, business logic, workflow automation, analytics environment. In IDOFF, the multi-vendor technologies are integrated seamlessly without additional effort in moving data between workflows and applications to achieve higher level of collaboration. The authors discuss the importance of operators to play a key role in orchestrating and building the digital oil field framework that supports multi-vendor environment to enable integrated solutions.
- Summary/Review (0.54)
- Overview > Innovation (0.35)
- Research Report (0.34)
Abstract Integrated Upstream workflows require efficient sharing of data across business disciplines involving planning studies, development, operations to carry our effective monitoring, surveillance of their reservoir and operations for better management of reservoir and production optimization. ADNOC requires quality, complete and timely multi-disciplinary data from its operating companies for efficiently monitoring its assets and provide informed directions. An Integrated Data Architecture and Data Governance Framework is being established to enable efficient deliver data to execute integrated upstream workflows in a multi-disciplinary and multi-vendor technology environment. The framework facilitates to standardize, streamline G&G, reservoir, production, operations data and processes, and enables integrated reservoir management workflows and inter disciplinary collaboration in a multivendor technology environment. The Framework provides guidance and best practices to build common data architecture foundation for integrated upstream workflows. The framework enables to efficiently govern the data across its lifecycle and makes the relevant business team and data custodians to take responsibility to validate, store and deliver static and real-time data in a timely manner for Integrated Upstream workflows. The framework components form a key foundation element for efficient integrated workflows towards realizing integrate operations, closed loop optimization, full benefit of Smart Field Investment.
- Energy > Oil & Gas > Upstream (1.00)
- Government > Regional Government > Asia Government > Middle East Government > UAE Government (0.38)
- Management > Asset and Portfolio Management > Integrated asset modeling (0.74)
- Management > Asset and Portfolio Management > Field development optimization and planning (0.59)
- Data Science & Engineering Analytics > Information Management and Systems > Data integration (0.54)
- Management > Strategic Planning and Management > Benchmarking and performance indicators (0.47)
Integrated Data Analytics and Visualization for Reservoir and Production Performance Management
Mohan, Richard (ADNOC) | Narayanan, Ram (ADNOC) | Al Yazeedi, Haifa (ADNOC) | Al Naqbi, Tayba (ADNOC) | Willems, Maarten (IPCOS) | Escorcia, Alvaro (Frontender) | Saputelli, Luigi (ADNOC, Frontender) | Abdulla, Nada (ADNOC) | Gioria, Gian Marco (IPCOS)
Abstract ADNOC operates its onshore and offshore fields through its operating companies. In order to effectively govern and steer the operations, it is essential for ADNOC to monitor, track and measure key reservoir and production performance indicators efficiently on time. In this regard, ADNOC Upstream has established an integrated reservoir and production performance visualization environment that enables upstream departments to efficiently monitor the performance of onshore and offshore operations at different levels from the headquarter in a collaborative manner with the operating companies. The integrated visualization environment is built on four key components, the upstream data hub, visualization, process automation and data governance which forms the common foundation for various upstream projects, enabling multi-project collaboration, reporting integrity, common business data and KPI definitions. The datawall in Thamama Collaboration Center is powered by the integrated reservoir and production performance visualization dashboards configured on objective based themes such as Reservoir Management, Production Assurance, Business Plan Assurance and others required by different departments. The visualization capability is enabling engineers and managers in the upstream directorate, to monitor key reservoir and production performance information on a daily and periodic basis, and the solution facilitates collaborative review sessions with OPCO team either on a regular or adhoc manner and to initiate and track actions. The integrated visualization environment shall be continuously enhanced to add more themes based on business needs, and to carry out advanced data analytics to predict and forecast performance leveraging the established foundation. Business processes shall be streamline through automation of the performance measurement processes to achieve higher degree of digital transformation.
- Energy > Oil & Gas > Upstream (1.00)
- Government > Regional Government > Asia Government > Middle East Government > UAE Government (0.78)
Copyright 2009, Society of Petroleum Engineers This paper was prepared for presentation at the 2010 SPE North Africa Technical Conference and Exhibition held in Cairo, Egypt, 14-17 February 2010. This paper was selected for presentation by an SPE program committee following review of information contained in an abstract submitted by the author(s). Contents of the paper have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Electronic reproduction, distribution, or storage of any part of this paper without the written consent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of SPE copyright. Abstract The oil and gas industry needs to plug the capability gap with pertinent technology that embraces the current trends to improving productivity. Digital oil fields have to engage the geosciences community and the business decision makers, surfacing knowledge from the plethora of accumulated data, both real-time and historical. Solutions must integrate not only the data, but extant applications and physical monitoring systems, and enable efficient collaboration between these facets to perform tasks faster and with more effectiveness and efficiency. With improved workflows and computing potential, it is now possible to ascertain the risk assessment and quantification of uncertainty inherent in improving productivity. The cost implied by poor predictions has to be mitigated by improved integration of disciplines and data fusion by adopting soft computing methods such as neural networks, fuzzy logic and probabilistic reasoning instilled into efficient workflows and processes.
- North America > United States (0.93)
- Africa > Middle East > Egypt > Cairo Governorate > Cairo (0.24)
- Information Technology > Data Science > Data Integration (1.00)
- Information Technology > Artificial Intelligence > Representation & Reasoning > Information Fusion (1.00)
- Information Technology > Architecture > Real Time Systems (1.00)
- Information Technology > Artificial Intelligence > Representation & Reasoning > Uncertainty > Fuzzy Logic (0.69)
Abstract The Chemical and Petroleum (C&P) Industry is waking up to the power of data to create more value, reduce cost, and gain competitive advantage. When dealing with Major Capital Projects (MCP), we have seen an increasing transition from paper to digital, from stand alone to collaborative, from product to outcome, and from CAPEX (capital expenditure) / OPEX (operational expenditure) to TOPEX (total expenditure). This includes a shift from the traditional engineering, construction and handover to the owner/operator lifecycle and, ultimately, to the full asset lifecycle. The extended asset lifecycle and more, as well as new requirements to manage, have increased complexity. This is mainly do to more disciplines needing to work together in an integrated way using a shared asset information model Data is the new natural resource. The amount of data the Engineering, Construction and Operation (EC&O) processes and activities produce, is authored in many different systems and consumed by many organizations and users in different formats. Not only is capturing their own data in their own systems of record (SOR) important to the C&P Industry, but so is external data, including unstructured data. The combination of SOR data with extended data can create additional value and provide new insights for better decision management. Another complication is the fact that the EC&O processes of large scale Major Capital Projects have changed. Delivery today is typically divided across multiple organizations, and supported by multi-level supplier networks, in order to share the risk.
- Information Technology > Information Management (1.00)
- Information Technology > Data Science > Data Mining (0.69)
- Information Technology > Communications > Collaboration (0.69)