Integrated Instrumentation System Strategy for Deepwater Asset Management

Abstract

Abstract The DeepStar program sponsored a study to review emerging instrumentation technologies that can be applied to integrated real-time monitoring systems for optimizing subsea production assets. The objectives for such a system are to provide visualization of actual production operations and system behaviors, to enable rapid and in-context diagnostic capability for increasing production uptime and assuring oilfield process optimization. This paper discusses how the approach used for the study can be used to develop an integrated instrumentation strategy for deepwater asset management. It addresses the following areas of the study:Value Added FunctionsMeasurement TechnologiesTechnology Valuation and Prioritization The study focused on instrumentation technologies for offshore production assets in 6,000 to 10,000 ft of water. Introduction In order to assure maximum use of research funds, it was important to develop a process to map out a recommended path for future instrumentation research. The map will be based on a review of current and emerging instrumentation technologies, and will prioritize those with the most profound impact on increasing the value of subsea production asset. Prior studies have been conducted on specific sensor technologies without regard to how the contributions of the technology compares to other sensors in adding value to the production asset. These studies typically consider the sensor in one dimensional function; and not in a multi-purpose role as part of an integrated real-time monitoring system. This paper proposes a global view of sensor measurement in which data is fed into an integrated data platform for process monitoring. The data is also available for use by various software applications in solving specific production problems, and for asset management applications. Specific sensor technologies can therefore be valued based on their profit contribution in increasing the value of the production asset. An enabler for the efficient implementation of the sensor's multi-function role is the Value Added Function. Value Added Functions In this study, Value Added Function (VAF) is defined as a software module that applies data validation and data integration techniques to primary sensor data in order to solve a specific problem, thereby increasing the value of a production asset. Sensor measurement is read into a data integration platform for data validation and used for process monitoring. The same process measurement is also available to various VAFs for solving production problems and for asset management. This architecture forms the building block for real-time integrated monitoring system and infrastructure-wide (field-wide) optimization. The installation of a measurement sensor incurs a certain cost, while its usage in solving production problems reflects its value in generating profit. In other words, the value of an instrumentation technology is a function of the profit it is able to generate by solving a specific production problem. The value could also result from profits it generates by participating in solving multiple production problems. As an example, the value of pressure measurement could be reflected in its use for solving problems in both wax detection and leak detection.