Abstract

Reservoir simulation has become the de facto design and analysis tool to plan, develop, and manage oil and gas assets. With increasing complexity of flow networks and advanced recovery mechanisms in the fields, the model description and features of the reservoir simulator have also been progressively advancing.

The goal of a single, evolving, life-cycle model for oil and gas assets has many benefits for effective and efficient field development and exploitation. However, the size and complexity of the reservoir models often require characterization at several resolutions, thus ranging from full field strategic models to short range operational models. Full field strategic models can be used to evaluate various production scenarios and development strategies and to estimate future drilling and facilities requirements. Short range operational models concentrate on issues such as rate requirements, production decline analysis, etc. However, the approach to integrate and maintain these separate reservoir models while describing the same field is often ad hoc and many times, inconsistent.

This paper describes a new methodology for enhanced and effective use of reservoir simulation. Specifically, the application of a new method is presented to consistently integrate the full field strategic models and the short range operational models using a parametric system identification approach. The measurements from the field are used to continuously update the short range operational models over a moving time horizon, while simultaneously preparing the data for a history match of the full-field, strategic model. This hierarchical model structure at different scales avoids frequent and costly history-match runs of the larger strategic models without compromising on short term accuracy, for example, those required by production optimization. In addition, the hierarchical model structure improves effectiveness and efficiency in carrying out the simulation objectives. A case study of a full-field performance is presented to highlight the benefits of the method.

Introduction

The increasing availability of real-time measurements and remotely activated valves in an oilfield has made oilfield-wide optimization of operations a distinct possibility.[1] While the term real-time optimization (RTO) is certainly not new and RTO is practiced in elements of drilling or production operations,[2–4] the extent to which RTO is now feasible has increased dramatically. At the same time, the increased scope of RTO of oilfield operations entails significant complexity and creates challenges.

RTO technologies have been advanced, either within the oil and gas industry or in related industries, such as oil refining. While it would certainly be beneficial to further develop technologies for field-wide RTO, it is also useful to identify existing technologies suitable for the task, streamline such technologies for use in the oilfield, and ensure that such technologies are used prudently and ultimately add value Because elements of field-wide RTO can be manifested in many activities related to production optimization, one may be overwhelmed by the multitude of approaches and breadth of scope of field-wide RTO. Putting field-wide RTO in a concrete framework, as discussed in the next section, offers clear development and implementation benefits, in that it can catalyze progress by suggesting the path to long-term benefits which might not be immediately obvious from incremental improvements stemming from individual projects.

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