Field Surveillance: Enhanced Monitoring and Smart Alarms Produce More Oil

Abstract

This article, written by Technology Editor Dennis Denney, contains highlights of paper SPE 102091, "A New Approach for Field Surveillance: Enhanced Monitoring Associating Smart Alarms To Produce More Oil," by A. Lentini and G. Fumia, Eni E&P; H. Malonga and F. Okassa, Eni Congo; and J.P. Le Cann and J. Lessi, SPE, Geoservices, prepared for the 2006 SPE Russian Oil and Gas Technical Conference and Exhibition, Moscow, 3–6 October. Managing wells produced with electrical submersible pumps (ESPs) must take into account limited pump-run life and production losses from ESP failures and shut in wells. Monitoring production and pump parameters is common, but real-time monitoring systems enable improving production conditions with rapid access to data that allows engineers to plan effective and timely remedial work. A system was field tested at an unmanned platform of a brown field with producing wells that use ESPs. The advanced information provided to the decision makers resulted in early production recovery and improved well inflow and outflow performance knowledge. Introduction The evolution of information technology has provided various new tools and opportunities to help maximize oil recovery while optimizing operational costs. Real-time data can increase the asset value only if the associated information can be analyzed fully in a timely and effective manner. The technology described here uses automated "smart alarms." It is intended to exploit the potential in the huge amount of information available from real-time monitoring of wells having ESPs. This surveillance system was implemented on an offshore satellite platform in Congo. The existing instrumentation was used and the data made available in real time to every location within the company's Congo network by use of terminal-server technology. During a first monitoring and optimization phase, an optimal setting was found for each well. Then, in a second surveillance phase, smart alarms were built to detect deviation from the optimal behavior by comparing current data with a signature specific for each well and based only on wellhead parameters. Background Data-collection systems can provide very large amounts of data from different sources. The drawback of such a situation is the risk of losing the relevant information because of data overload and the lack of appropriate, coherent, and consistent processing of these data. It is important to focus on parameters that are key to optimizing well production and avoiding production losses. If correctly processed, these parameters can be used efficiently to trigger alarms that can draw the operator's attention, enabling immediate appropriate action. The first step is to define processing that, when applied to specific data, will detect abnormal well behavior. The second step is to implement software that uses the data to trigger alarms. This software relies on "smart logic" to avoid any false alarm caused by a non-relevant situation, such as a planned shut-in of the well.