Reliability Through Data Reconciliation

Abstract We propose a flexible simulator of an oil well that may be used for several forms of online, real-time reconciliation of data from existing measurement equipment. It turns out that data reconciliation used as part of the instrumentation philosophy on an oilfield constitutes a dissimilar, redundant level of instrumentation. This additional level of instrumentation may be used to make the existing measurement hardware more reliable by verifying the validity of measurement data. In addition, the technology may be used to replace permanently installed hardware in times of failure. Greater reliability is expected to contribute to greater system uptime by reducing the need for workovers. Introduction Data reconciliation is a technique that has traditionally been used in process control to verify measured data by reference to a process model. In this paper we consider a more active form of data reconciliation in which we use a model of the process to estimate a number of unknown variables on the basis of other, known variables in the process. Such estimated variables may be seen as virtual measurements of the process; therefore estimators based on data reconciliation are sometimes referred to as virtual sensors. They are also known as software sensors or soft sensors, which distinguishes them from their hardware counterparts. It turns out that soft sensors may be used with great success in the operation of chemical processes for supplementing, and in many cases even replacing, permanently installed hardware. There is a big potential for soft sensors in offshore oil production. First of all, even though the added value of permanently installed sensors is undisputed, downhole equipment is particularly expensive to install because of the nature of offshore operations. Therefore it is appealing to limit the number of downhole sensors to what is minimally required in order to get sufficient insight into the production process, and to use inferential techniques to make the picture complete. Secondly, it is widely recognized that downhole measurement equipment and the corresponding communication systems are prone to failure during installation in the well, during special events in the life of the well, or after a few years in operation due to harsh living conditions. Furthermore, it is prohibitively costly to repair or replace downhole equipment in offshore wells. Software sensors, as opposed to hardware sensors, typically do not break down. In fact, even though a soft sensor depends on the availability of hardware measurements that may be subject to errors, it does not necessarily depend on the availibility of aparticular piece of hardware. A soft sensor will work as long as the total set of available data contains enough information for the system to make up its mind. In this paper we propose a flexible simulator of an oil well that may be used for several forms of online, real-time data reconciliation..