The Challenge of Federation of Information for Automated Surveillance of ESPs: Field Examples

Abstract

Real Time Production is not just a buzzword today. A number of assets is experimenting implementations of real time production systems and some have made the leap of faith and rely extensively on it to optimze part of their production processes. A number of trial and errors have enabled to construct a number of rules of thumbs in the design, implementation and operation of such system. Because of the easy (or easier) case for value generation, the surveillance and optimization of artificial lift systems have been preferential targets for such implementations (in this paper we will focus on ESP operations). One of the main operational issues related to the realisation of the value expect from this type of project is to ensure that all of the required information is correct. This is not a little feat! This paper describes the challenge of the federation of the information required to perform automated surveillance of ESP in remote wells. The end-to-end delivery of reliable workflows requires the following elements:–Validated streaming real time information (pump measurements, intake and discharge pressures etc...)–Validated episodic information (well test flowrates, choke and back pressure information)–Static information (tubing size, formation parameters etc...) The reliability of a real time production workflow in an automated system requires the insurance that all of these three types of information be correct. The evaluation of the dependency of reliable information of information to the quality and reliability of the final surveillance information is demonstrated through the use of graph analysis. This methodology enables to focus the field data capture in the right areas, which are not always intuitive. Field examples from South America demonstrate the value of such real time production workflows. Case histories also demonstrate instances of raising wrong alarms and the analysis of such event confirms the theoretical sensitivity analysis. The paper concludes with a number of recommendations towards the field practices related to the real time enabling of the production operations some that can be extended to the futuristic full field automation. Introduction The need for real-time or relevant data feed to support production workflows is not new. Permanent monitoring devices have been in use in the oil field industry since the beginning of the century for surface applications (earlier in the form of pressure and temperature strip charts). The field of downhole instrumentation has been tackled in various ways since the early 60s. Engel (1963) introduced an electromechanical gauge and showed data from 1959–1961. Since the mid 70s permanent electronic gauges have been deployed in wells on dry completions, and subsea in the early 80s (Bezerra et al, 1992). The value of such measurements was well recognized at that time, and it is not surprising that they are becoming more and more popular in the upstream oil and gas arena. The recent evolution of various information technologies brings new possibilities for deploying monitoring services to facilitate production workflow. The Digital Oil Field of the Future (DOFF) study, Cambridge Energy Research Associates, Inc., (CERA, 2003) identifies monitoring and control as one of five key technologies that will impact the oil and gas industry in the future. With a number of such implementations already in place, it is now possible to provide examples and recommendations for a successful realization of these technologies in the production environment.

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