fax 01-972-952-9435. AbstractBenchmarked results on well construction projects show that many projects incurred significant cost over runs. Half of the mega projects since 1993 have been disasters resulting in a destruction of capital for oil companies. Insufficient drilling front-end loading and inadequate team organization have been identified as preventable causes of these over runs. Deepwater projects involve multiple challenges of new technology, geological uncertainty and, often, a fast track approach. The wells' portion of the total project cost often exceeds 50%. The huge price for intervention activities later in the life of these wells requires that the initial completion remain in place and function as planned for a long time. Predictable and distinctive drilling and completion performance is a must for the high cost projects that typify deepwater. This paper will describe a methodology that has been successfully applied with repeatable best in class results in the North Sea and Gulf of Mexico. This methodology addresses the need that teams are organized to fit the project (not the other way around) and that systems integration is treated as a high priority. The results typically achieved with this methodology are in the range 20 -23 days per 10,000 ft -best in class in both regions and 35% better than the average drilling time -with commensurate improvements in production and data acquisition. Short case histories of deepwater exploration and development wells are describedincluding a horizontal development well.The paper describes:-how the projects were organized, -how the teams were aligned to their objective and goals, -the processes that support these successful teams, -how the teams were motivated to perform, -how web based support can function to create colocation through the virtual world.The paper also contrasts this methodology with traditional operations.

Drilling systems automation depends on timely flow of accurate and relevant data from multiple sources to control equipment, machines and processes. The fragmented nature of the drilling operations business means that data must usually be shared among companies contracted to perform services, and the operator, and all companies must trust that data. This paper describes the issue of data ownership in terms of the application of drilling systems automation, and proposes solutions. Various parties in a drilling operation measure, collect, analyze and report data gathered during the drilling operation. They take actions to control the drilling process, avoid problems and improve performance, using information derived from the data. Data is used in pre-job planning, in real-time by those operating the drilling rig and various drilling tools, as well as periodically to advise the onsite drilling team. Data flow ranges from high-frequency, low-latency response loops at the wellsite to low-frequency, high-latency response loops in remote centers. The SPE Drilling Systems Automation Technical Section (DSATS) has identified OPC UA as the most suited communications protocol for multidirectional fast-loop control systems. In these environments, there is high likelihood that a controller from one supplier will access and use data created by another supplier. Drilling systems automation requires structured and organized data sharing between parties. This data sharing adds value to the drilling process. A conceptual data model describes at least three classes of data generated while drilling, and all lie within the confidentiality envelope of the operator or government agency. There is data that is the property of the data generator (such as equipment condition monitoring data), data that is restricted (such as formation evaluation data), and data that is shared in an "open data pool" for the purposes of drilling systems automation. Because ownership or control means responsibility for data quality, it is important that each data generator own its contribution to the shared data pool. The data aggregator – the party managing the shared data pool – is therefore not necessarily the owner of all data in the pool, but a caretaker of that data. This paper describes the history of data measurement, data flow and data ownership in the drilling industry. It will address data ownership issues pertaining to drilling systems automation and drilling performance improvement. A brief review of examples of data from academia and from within our own industry will assist in understanding the relationship between data ownership and intellectual property. The paper presents a data ownership and data sharing solution that provides an environment for drilling systems automation.

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Dayrate contracts have been the normal mode for drilling operations for a long time. The environment is well known and therefore comfortable to the participants. The operator retains control over all aspects of the operations; essentially the operator leases men and equipment