Digital oilfield

Experience and Perspectives of Deepwater Smart Fields Management

This paper describes field experiences and perspectives on a Smart Fields implementation for the Bonga deepwater field and uses the results of a post-implementation study to evaluate the business effects and lessons learned after 5 years.

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Smart Fields, Shell’s version of the digital oil field, aims to provide an operating field with the capabilities to optimize production in the short term and maximize life-cycle value in the long term. This paper describes field experiences and perspectives on a Smart Fields implementation for the Bonga deepwater field and uses the results of a post-implementation study to evaluate the business effects and lessons learned after 5 years.

Introduction

The digital-oilfield process involves continuous production optimization of an asset or group of assets through integration of people, tools, and process.

Shell’s version of the digital-oilfield process is called Smart Fields. Smart Fields began with the installation and monitoring of control systems in wells. This has expanded to cover field management and has been formulated as a value loop, as shown in Fig. 1.

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Fig. 1—Smart Fields value loop: measure, model, decide, execute.

The value-loop concept describes how the respective components that make up the Smart Fields (technology, people, and process) are linked to meet business objectives. In the production and operation phase, Smart Fields covers diverse solutions. However, the standard solution comes in the form of the Smart Fields Foundation Mark 1, which forms the building blocks for smartness of the field for real-time well monitoring and optimization, data acquisition and model-based optimization, virtual metering, production allocation, and integrated-production-system modeling (IPSM).

The standard Smart Fields Foundation Mark 1 architecture (Fig. 2) gives a clear description of the structure that makes up this system. The architecture is divided into the process and office domains with the data-acquisition-and-control architecture (DACA), which is the cybersecurity system that provides the secure link between office and the field. Customized work flows guide the staff with the proper steps in executing the process and collaboration at the right moment and thereby assist the assets in obtaining the overall benefit of Smart Fields deployment.

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Fig. 2—Standard Smart Fields Foundation Mark 1 architecture. PI=plant information data system.

This work flow, which represents the Smart Fields integration of people, tools, and process equally, shows at a high level the people involved in a process and the tools that support or enable that process, as well as their dependencies. According to a recent study across many Smart Fields assets, value erosion remains the biggest challenge in sustaining the gains from Smart Fields implementation. In a bid to address this gap, the sustainability assessment was conducted in various assets and refined the sustainability framework, with the following elements captured:

  • Smart Fields solutions need to be aligned with the business needs or objectives specific to the asset of interest.
  • A defined path for training and succession is critical for sustainability and needs to cover all spectrums of the solutions.
  • After implementation, clear ownership and sponsorship must be taken by the business or asset.
  • Process champions need to be appointed, with regular reviews of the work-flow process.
  • Top-quartile reliability and availability of the field instrument is crucial for the success of the project.

Smart Fields Foundation Mark 1 Implementation in Bonga Field

Bonga is a deepwater field sustained by water injection for pressure maintenance from the inception of production. Bonga field was completed with 18 producer wells and 14 water injectors at a water depth of 1000 m, with wells tied to a floating production, storage, and offloading vessel. The field is approximately 120 km southwest of Warri, Nigeria, in the Gulf of Guinea.

The Bonga Smart Fields Foundation Mark 1 comprises standardized architecture, data applications, and fully integrated work processes. Each staff member was trained on the use of required data application and participated in workshops that assisted in defining the roles and responsibilities of stakeholders to ensure that business objectives are met. The key business drivers for the implementation of Smart Fields in the Bonga field were

  • Minimize manual data entry and support seamless real-time data flow.
  • Support faster response time to production optimization through integrated-production-system optimization.
  • Enhance production allocation and forecasting.
  • Control access from the office domain to the process-control domain by use of DACA, thereby enhancing cybersecurity.
  • Provide robust well-, reservoir-, and facilities-management process.
  • Support a collaborative work environment through the defined Smart Fields work flow.

Bonga Smart Fields Post-Implementation Review

A post-implementation review was conducted following the successful implementation of the Bonga Smart Fields Foundation Mark 1. The purpose of the review was to

  • Determine the level of embedment of the Smart Fields Foundation solutions in the asset.
  • Review the level of competence in the use of Smart Fields Foundation Mark 1 tools.
  • Assess the awareness level of the Smart Fields solutions.
  • Evaluate the value of Smart Fields to the asset.
  • Identify areas of improvement in embedment of this solution and ensure sustainability.
  • Capture lessons learned for future deployment.

Post-Implementation Review of Key Bonga Smart Fields Processes

The following key processes of the Bonga Smart Fields project were evaluated as part of the review process.

Gather and Validate Well-Test Data. The previous well-test application was decommissioned because it did not interface with other Smart Fields applications and because of limited available support. Hence, the Fieldware Well Test (FWWT) application was commissioned as a well-test monitoring tool. The benefits of FWWT included minimizing manual data entry because all well-test data (during well-test operation) were transferred automatically.

Production Monitoring and Optimization. The Smart Fields application that supported this process is called Fieldware Production Universe, a data-driven application that provides real-time oil-, water-, and gas-production data from each well on a continuous basis. From the post-implementation review, it was confirmed that the Production Universe models are updated regularly on the basis of operational demands. The production estimates from this application assist in real-time production monitoring and optimization, which form the basis for discussion.

Enhanced Production-Allocation Process. The Bonga field production-­allocation process can be mathematically expressed as Reconciliation Factor=Fiscalized Ullage (Tank Dip) Volume/Production Universe Production Estimates. Bonga field production allocation is achieved by comparing the fiscalized production volume from the tank dipping against the Production Universe estimated volume from all the flowing wells, as shown in the expression. A health check of this process showed a high consistency over time and an outstanding average reconciliation factor of 0.975.

Integrated-Production-System Optimization and Forecasting. The Bonga production-system-optimization process is driven by a Smart Fields application called Integrated Production Modeling. This is a fully developed process in Bonga in which the IPSM is used to identify opportunities; the Bonga IPSM team comprises the reservoir engineer, process engineer, production technologist, and programmer. The IPSM models are updated monthly with well-test and production data in preparation for short-term and medium-term production meetings, where opportunities for production improvement are fed into the planning cycle. The process for IPSM-model validation and calibration involves populating the oilfield-manager database with field-performance data, while simulations are run and sensitivities are determined in order to history match rates and pressures.

Recommendation and Conclusion

After 5 years of implementation of Smart Fields solutions, Bonga has shown remarkable benefit as revealed by post-­implementation review. However, to sustain and improve on this process, the following findings from this case study should be noted:

  • Implementation of Smart Fields usually comes with a change in work culture, work process, and people. Technology is only an enabler; the true benefit is visible only after the integration of data collection and analysis transforms decision making and collaboration.
  • Full implementation of the process is necessary to ensure sustainability. Sustainability could be achieved if the solutions of Smart Fields are aligned with the business need of the asset, with a clear process for embedding.
  • Continuous training and retraining of staff members in Smart Fields tools and processes to ensure that any knowledge gaps in understanding or awareness of the Smart Fields process are closed. This is important because it sustains the embedment process. A learning gap could come from staff-member movement or a change in technology. Process champions need to be appointed and constantly updated with the latest trends in Smart Fields.
  • The business must take ownership and sponsorship of the solutions after initial implementation to ensure that value is unlocked continually.

This article, written by Special Publications Editor Adam Wilson, contains highlights of paper OTC 24078, “Smart Fields Management in Deepwater Field: Experience and Perspectives,” by Emmanuel Udofia, SPE, Olatunbosun Oni, Abdul Samad Chaker, and Ogbole Oghedegbe, Shell Nigeria Exploration and Production Company, prepared for the 2013 Offshore Technology Conference, Houston, 6–9 May. The paper has not been peer reviewed. Copyright 2013 Offshore Technology Conference. Reproduced by permission.