Application of a Real-Time Dynamic Model-Based Production System for Operations and Surveillance of Oil & Gas Gathering Networks

In this paper we present a methodology for synchronized integration of a dynamic simulation model of the wells and production facilities with the real-time online data obtained from the production field. Through dynamic simulation, the production system can be characterized as a transient, multiphase operation capable of modeling time-dependent phenomena. The implementation incorporates development of an accurate dynamic model of the wells and the production network, as well as an online, real-time application which transfers data in a time synchronized manner between historian database and the simulation model at predetermined time steps. This system has been implemented by Pioneer Resources on the Oooguruk oil field which is the basis of this case study. One important outcome of this system is that it acts as “virtual instrumentation” for key unmeasured variables such as well flow rates. The system can also monitor the performance of specific equipment and support decisions to switch to production modes such as artificial lift. The system can be run offline as a look-ahead tool to predict future behavior given initial conditions or to run what-if scenarios. It has been shown that real-time models that match the field data improve understanding of the overall system, and provide the tools to translate vast amount of data into decision support for daily operational strategies. Introduction The upstream oil & gas industry faces the increasing challenge of maximizing overall profitability by enhancing hydrocarbon recovery, maintaining the field and reducing operating costs, and has been actively exploring technology applications that can assist in optimizing the value of the assets. This can only be achieved by refining relevant data into actionable information and delivering it on time to drive critical decisions. Detecting and resolving operational problems quickly can save significant amounts of money every day. The amount of available real-time data obtained from downhole instruments, surface SCADA and DCS systems can rapidly become overwhelming such that operations managers require tools to process these large amounts of data within their time constraints. A description of the benefits of developing the technologies to translate date into actionable information further was presented by Knott (2003). In petroleum fields, oil production is often constrained by the reservoir conditions, flow characteristics of the pipeline network, and the capacity of the surface facilities. In order to define the optimal operating conditions it is necessary to consider the interactions between the reservoir, wells, and surface facilities. Most of the realtime data which is available from increasingly sophisticated measurement and control systems is seldom used, however, for decision making as it mainly supports plant control services; in order to extract more value from these acquisition systems it is necessary to design and implement novel engineering applications that can translate the raw data into actionable information that can be used by engineering groups and management to support better decision-making. A number of authors have reported on alternative approaches to achieve this objective; Oberwinker et al. (2006) described an IT system that allows engineers to rapidly evaluate and solve potential problems and illustrated the applicability at a US field