Experiences in Gas-condensate Well Test Analysis Using Compositional Simulation
Authors: Bertram D.A. , van de Leemput L.E.C. , McDevitt B.S. , Al Harthy N.M.A. 
Published: December 2007

Experiences in Gas-condensate Well Test Analysis Using Compositional Simulation D.A. Bertram, L.E.C. van de Leemput, B.S. McDevitt, N.M.A. Al Harthy, SPE members, Petroleum Development Oman Copyright 1997, Society of Petroleum Engineers, Inc.

The use of a compositional reservoir simulator to analyse perforated and hydraulically fracced gas-condensate well tests is described. Key physical issues which drove the need for simulation are the impact of retrograde condensation and fracture flow dynamics on well productivity. Modelling of these effects using innovative features such as capillary Number-dependent relative permeability assignments and inter-gridblock non-Darcy flow is described. The value of relevant core, log and PVT data is discussed. Finally, history matching and analysis of selected perforated and fractured well tests is presented. The described modelling approach is particularly useful for analysis of well tests involving gas-condensate flow, although the approach has also been found useful to improve understanding of both dry gas and undersaturated oil well tests.

The principal advantage of simulation over analytical modelling is in identifying and understanding the specific physical effects governing well productivity. This has helped members of the multi-discipline team appreciate the quality and impact of their basic data, facilitated focus on key uncertainties and promoted ownership of the model results.

Critical success factors for this work were extensive data collection and a versatile equation of state simulator which permitted user-definable algorithms for specialised programming of saturation functions and well inflow equations.

Introduction

Appraisal testing of deep gas-condensate reservoirs in the Sultanate of Oman was conducted to calibrate performance predictions for both perforated and hydraulically fractured wells; some 20 well tests were conducted over a 4-year period. Due to low reservoir permeability, most of the well tests were conducted with flowing bottomhole pressures significantly below the estimated reservoir hydrocarbon dew point pressures. To quantify the impact of gas-condensate flow phenomena on well productivity, many of the tests were analysed both analytically and using a compositional reservoir simulator. The simulation results were used to calibrate full-field model performance predictions 1 and optimise well design.

Although initially time-consuming and data intensive, analysis of these multi-phase problems using a simulator was pursued because of the following perceived benefits:–rigorous accounting for all relevant physical effects and quantified impact of uncertainties–improved ability to diagnose WHY the wells behave the way they do with attendant benefit to design optimisation and forecasting–improved communication with other disciplines by clearly showing the impact of specific data uncertainties on well performance, e.g. The impact of fracture properties (width, length, permeability, etc.) could be shown directly, instead of via the complex (for gaswells) analytical expression "dimensionless fracture conductivity".–direct calibration of forecasting models

Demonstrated understanding of the depletion performance of these reservoirs was one vital aspect in generating stakeholder confidence to proceed with a multi-billion dollar long-term gas export project. Consistency of the models with the extensive, relatively low cost petrophysical and well performance data was crucial to show that the models ultimately reflect physical reality. Correct identification and modelling of the relevant physics required the co-ordinated effort of an integrated petroleum engineering (PE) team, laboratory research and sophisticated simulator functionality. This paper details the well test modelling experiences to date including well testing objectives/design, basic data & model design and selected key results.

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