- Conference Article
- 10.2118/227868-ms
Well Lifecycle Data Management - From Portfolio Ranking, Design Concept Through Plug & Abandon
- Oct 13, 2025
- J P De Wardt + 5 more +5
Abstract The global quest for greater value from wells achieved success through well construction improvements contributing to economic production. The stage is set to unlock further value through a well lifecycle approach. Well Lifecycle applications need to solve two interconnected challenges: ability to uniformly quantify all the constituent factors contributing to the long-term outcome of a well, and ability to connect multiple static, transient, and in motion data in a meaningful manner across multiple disciplines. Increased value from wells requires a shift from siloed behaviors to full lifecycle unhindered workflow. A system of systems framework can create a context-driven federation for linkage of sub systems and multiple data sources for their intended use. Fully leveraged value can only be achieved when the well's data is comprehensively managed, contains context and is accessible in time to all involved for comprehensive lifecycle asset value while safeguarding against risk. This paper proposes an approach to well lifecycle workflow and data management that maximizes the well value contribution to enhance field development value. Data is an asset that must be competently managed and utilized to maximize the impact it has on business value. Currently, the two-way flow of information across the well lifecycle is broken or stifled. For example, the final user has limited input and access to the initial design. This failure to flow accurate data drives up risk across multiple aspects of the well lifecycle. The System of Systems approach has been successfully applied to both the defense and space exploration sectors as they evolved over the last decade. This approach offers an opportunity to deliver a framework onto which robust modern data management and utilization methods can be constructed. In time, access to all well data regardless of the stage in the lifecycle in a manner that is efficient and communicates the data context can be achieved with modern data management systems. This will enable significantly greater value realization from the operation of the wells and the associated subsurface modelling. Currently this is not practiced in wells lifecycle, for example, through the poor management of wellbore survey data routinely leading to greater uncertainty in subsurface models negatively impacting field development decisions. This paper furthers the application of a System of Systems methodology and workflow to manage the inherent complexity of interconnected interactions throughout a wells lifecycle. It also introduces industry best practices for managing data in this environment. These best practices will include data attributes (frequency, latency, …), context (data set description and changes made over time), uncertainty (deviations from the intended source value or derived parameters), various industry data standards, etc.
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