Application of Digital Well Construction Planning Tool During Well Conceptualization Phase

Published: 09/21/2021

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Schlumberger Oilfield Services

Digital well construction tools are becoming more widely considered today for well design planning, enabling automated engineering and simultaneous team collaboration under a single solution. This paper shows the results of using a digital well construction planning solution during a project’s conceptual planning stage. This method shortens the time needed to estimate the well times and risk profile for a drilling campaign by applying smart engines to quickly and accurately perform critical offset analysis for defined well types that is required for project sanction.

With this solution, the Offset Well Analysis (OWA) process is done automatically based on the location of the planned well, trajectory and well architecture. Various information and reports (both subsurface and surface data) from neighboring wells is stored in cloud solutions, enabling ease of access and data reliability for both large or smaller scale data storage. The software selects the most relevant offset wells, displays the risk analysis and generates the stick chart. For a conceptual design, the risk levels can be manually set higher due to potential unknowns in surface and subsurface risks which can later be refined. Quick validation of the well design allows the engineer to design a conceptual drilling campaign quickly and more efficiently.

The solution minimizes the time to perform probabilistic time and risk estimations. It reduces the risk of biased decision making due to manual input and design. This allows for better-informed decisions on project feasibility, alignment of stakeholders, increased design reliability as well as reducing the amount of time and resources invested in OWA.

The work presented here is aimed at sharing the experience of applying a digital well construction planning solution specifically on the conceptual project stage and discuss the value it adds to the well design process.

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