A visualization software tool has been developed to aid in the analysis of the numerical output generated by a 3-D gravel pack simulator. The tool provides animated 3-D graphics showing the condition of moving fluids and the progress of gravel placement within the wellbore. The advantages, limitations, and pitfalls in implementing the 3-D visualization for analysis of gravel pack simulation results are addressed.
The ability to identify events of interest at the surface and sub-surface, and use event information for various workflows and analyses is a key enabler for a variety of surveillance, monitoring, and optimization workflows. The scalability, extensibility, and maintainability of an event management system is directly related to the conceptual model used to represent events, the ease with which relationships between events can be encoded in the form of rules, and the type of rule engine that performs the analysis necessary to extract useful, actionable information from the frequently updated event database. This paper summarizes our experience with building a well surveillance application using semantic web technologies. Events are modeled using the web ontology language (OWL) and relationships between events expressed as rules in the semantic web rule language SWRL. An offthe-shelf rule engine aggregates the values of lower level attributes related to well performance and not only infers the well status ("alert" or "no-alert") but also provides the entire chain of reasoning that led to the particular well status. Although more work needs to be done to translate the reasoning into a form that is comprehensible to the domain experts, even the raw information is a valuable aid in understanding and validating the rule base. We discuss the advantages of using semweb technologies for event management: the relatively low code complexity, the ability to remove existing rules or add new rules of arbitrary complexity at run time, and the ease of encoding domain knowledge into events and rules. Evaluation of time performance of our application for different number of wells is presented. The broader significance of this work is in the context of understanding the right technology (or combination of technologies) to build logical, extensible, and maintainable systems for processing field events.
BP's FIELD OF THE FUTURE for North American Gas Strategic Performance Unit is a ground-breaking initiative which utilizes advanced automation, collaboration and analytic tools to enable major reductions in well intervention timing, as well as, prevent and recover lost volumes more quickly. This effort requires a phased, multi-discipline approach and encompasses changes in technology, business process and people. FIELD OF THE FUTURE begins with upgrading foundational equipment and systems, such as, current automation and field telecoms. From a systems standpoint, FIELD OF THE FUTURE requires enhancement of NAG's data management approach towards collection, storage and retrieval of significantly increased data (100× or more), from field operations. Another key component of change is the design and installation of Advanced Collaborative Environments (ACEs). ACEs are integral in this phase, as they enable multi-disciplinary teams working in collaborative spaces, to successfully interact during the decision-making process. Even with the enhanced foundational systems, the influx of new and vast amounts of data will reach beyond personnel capability to utilize effectively, without the new technologies. To manage the additional data, FIELD OF THE FUTURE leverages integrated advanced visualization, modeling and intelligent applications functionality. These are then merged into the business process to discover areas for optimization in day-to-day operations. This leads to greater productivity, as well as, reduced decision cycle time. Taking this one step further, FIELD OF THE FUTURE identifies viable solutions (both current and futuristic), which can further enhance benefits through analytic and business process management tools. These can empower the organization to do more with less - a problem we will confront within the North American Gas SPU, in the next five years. The success of the program lies in the ability to integrate accurate, real-time data with people and their daily work activities. To achieve program goals, FIELD OF THE FUTURE is currently testing and refining enhancements in automation, collaboration, data/applications and processes by partnering with three Pilot Assets across North America. The ultimate measure of the program's success will be based on key performance indicators, described herein, which demonstrate real value to the Assets. These include: FIELD OF THE FUTURE has the potential to impact every aspect of field operations and must be strategically aligned with other BP corporate initiatives. Thus, FIELD OF THE FUTURE must have executive alignment and active executive leadership to enable change. Finally, FIELD OF THE FUTURE is not about individual technologies, but about the integration of tools and capabilities spanning people, process and technology. The presentation paper will give an update on the current status of work at the three Pilots and share key Lessons Learned by NAG FIELD OF THE FUTURE, in this journey. Introduction There is a high level of production operations activity around the digital oil field and many papers (ref 1–5); have been published on this topic. Within SPE, a Technical Interest Group was formed three years ago and has published (ref 2), three papers defining the topic and setting-up a framework for evaluating levels of implementation. In addition, BP, as well as, others support Joint Industry Project activity, like Smart Fields at Stanford University (ref 3), where key companies in the industry are working collectively on state-of-the-art solutions.
Chevron has a vision to transform upstream workflow processes through implementation of innovative solutions that encompass changes in process, organization, and enabling technologies. This effort is creating a sustainable intelligent energy organization. This paper highlights Chevron’s experiences throughout this ongoing transformation. Chevron has a wide range of assets in numerous diverse operating systems with many drivers that must successfully address variables such as: current state (process, organization, and technology), asset type and maturity, work force, and return on investment. There are four key areas that must work in unison for transformation to become sustainable: Strategic Management Framework: A compelling future vision, aligning guiding principles, strategies, and tactics with the vision to implement and sustain transformation of upstream workflows. Governance Framework: Integrating a diverse set of interdependent governance systems involving corporate, business units, and external entities. Solution Lifecycle Management (SLM): A framework to address key considerations, such as managing transformation roadmaps, developing workflow and technology solutions, capturing the value of solutions, and offering integrated support to ensure sustainability. Organizational Capability: Organizational capability framework focused on building key competencies (e.g., multidisciplinary virtual teams) and ensuring new competencies are addressed. With the plethora of drivers and conditions highlighted above, sustaining upstream transformation requires a well orchestrated management framework. The body of work created by Chevron Upstream lays the foundation for a sustainable intelligent energy organization and paves the way to a transformed future.
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