Casing, liner and completion running operations are key activities during the well construction process. Failure to reach the required setting depth may have a significant impact on well economics due to additional construction costs, deferred production and lost reserves. A substantial proportion of NPT (Non-Productive Time) associated with these operations is due to stuck pipe, and over many years the industry has made a concerted effort to reduce this. A new advanced advisory system has been developed to enhance the monitoring of running tubulars into a wellbore. This web based system integrates real-time data, analytical capability and informative displays to identify early warning indicators associated with stuck pipe, mud losses and other anomalies. The system has been used to actively monitor more than seventy casing, liner and completion running operations in offshore wells located in the Caspian Sea, offshore Trinidad, the North Sea and the Gulf of Mexico. Early benefits that have been realised include improved responses to stuck pipe early warning indicators, closer control of trip schedules, greater collaboration between offshore and onshore communities, and better informed and more impactful decision making. The system is currently being deployed at scale to offshore drilling rigs and is expected to bring additional benefits of standardisation, embedment of good practice and know how, and enhanced organisational capability. As the industry drills longer, deeper, and more complex wells, the installation of longer and heavier tubulars into close tolerance wellbores will be required. This means that a deeper knowledge of the underlying physics and a better understanding of the limitations of tubular running equipment are required. It is envisioned that this advisory system will prove to be a mechanism to gain deeper insights into the casing running process, generate ideas for better designs and drive enhanced operational decision making. This paper describes the concept, system design and infrastructure requirements. Case studies from various field deployments are illustrated and conclusions from experience to date summarised.

Today, even relatively basic drilling operations generate substantial amounts of real-time data, both at surface and downhole, all paid for by the Operator. This data can stagnate as a commodity, archived in a database or a drawer. Or it can be transformed into an asset enabling optimized well delivery through immediate, informed, collaborative decision-making. This transformation from data object to value-adding asset is made by intelligent use of real-time data management that drives ergonomic data display -the right data to the right people at the right time -applied automated data analysis and monitoring by exception, and correlative and predictive techniques comparing real-time with planned, historical and 'what-if' data. Such sophisticated data management only becomes truly and consistently effective when governed by industry-accepted standards, provided in a vendor-neutral manner that makes the raw data source irrelevant. This paper describes the ongoing evolution of an independent real-time data management infrastructure, service and solution. This includes acquisition-to-application dataflow, all wholly within industry standards, powering a variety of data management and monitoring modules optimizing various well operations. Real world examples highlight how such solutions support the performance of wellbore construction teams to achieve their key goal: to deliver wells safely, quickly, accurately, consistently and cost-effectively. IntroductionDrilling for oil and gas is costly, dangerous and complex. Errors made during the wellbore construction can potentially damage a company's reputation. The stakes are already high, but inefficient well delivery can cause a significant financial impact. With the risks well understood, Operators are under pressure to improve their efficiency in well delivery and find ways to predict situations that could have a negative impact on HS&E or the bottom line.