Abstract

A knowledge-based system has been developed which predicts relative permeabilities to describe the flow of fluids in oil, gas or condensate reservoirs. The software applies heuristic knowledge and artificial intelligence techniques to identify the appropriate experimental methods for measuring the relative permeabilities, and to decide on the mathematical models and computational steps to use to generate the data. The selected models and computational steps are used together with the inbuilt database to generate the relative permeability data which honour the physics of the flow system. Rules that relate the combination of field development scenario, fluid PVT properties, rock lithology and petrophysical properties are included in the knowledge base.

The paper describes the parts of the software which address the complex problems associated with relative permeability predictions in gas condensate reservoirs undergoing pressure depletion. The current version of the software runs on a PC under the Microsoft Windows operating system and exploits fully the graphical user interface for data input and output.

Introduction

The increasing emphasis on optimising recovery from gas condensate fields and the extensive development and use of reservoir simulators for predicting reservoir performance are together creating a widespread need for reliable basic data on rock flow behaviour. In general, in reservoir study involving two phase flow, the relative permeability is the parameter with the major control on reservoir performance. Relative permeabilities provide a basic description of the way in which the phases will move in the reservoir. Definition of the flow process can have a significant effect on the predicted gas/oil production rate and duration, and is important in calculating the volume of recoverable hydrocarbon reserves. The predicted production rates, the plateau level and duration, plus the expected water cut will all influence development plans. The number of wells, the balance between injectors and producers, the sizing of separation equipment, and design of facilities in general can all be impacted upon by the multiphase flow properties of the reservoir in the near wellbore region. Ultimately, together with many other inputs, relative permeability assists in determining reservoir economics, and hence guiding investment decisions.

Laboratory measurement of representative relative permeability data on a reservoir core-fluid system is a complex task. The experiments are costly, typically more than $100,000 each, and time consuming, often taking up to six months to complete. Accuracy is limited to the specific core samples and is bounded by narrow saturation limits. A fundamental theoretical approach to modelling multiphase fluid flow in porous rocks is prevented by the complex nature of the problem. Major difficulties arise in mathematically describing flow through a porous system where the lengths, diameters and connectivity of channels are largely unquantifiable. For gas condensate systems the issue is complicated further as the thermodynamic behaviour of a multicomponent system close to their critical region needs to be taken into account. As a result, the experimentally determined gas condensate relative permeabilities are few and usually present a wide range of scattering. Consequently, it is very difficult to determine a representative average function on any basis, with a reservoir unit basis being the most difficult.

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