3-D Numerical Models for Temperature Prediction and Reservoir Simulation

Abstract

The prediction of reservoir temperatures and production behavior is crucial for planning a deep geothermal installation. We present a study regarding these issues using the example of a planned doublet in a Jurassic sandstone layer in the city of The Hague, The Netherlands.
In the first phase, the main objective is to find out whether there is a significant influence of the 3-dimensional structures of anticlines and synclines on the temperature field. To achieve this target, comprehensive petrophysical investigations were performed and a large scale 3-D-model has been built up. Several bottom hole temperatures, as well as petrophysical logs available in the area were used to calibrate the model. Profiles and cross sections extracted from the calculated temperature field allow a detailed study of the temperature in the surrounding of the planned location. Test runs with different thermal conductivities for each layer showed the importance of a proper determination of this thermal parameter for a reliable temperature prediction.
In the second phase of the project, a detailed 3-D numerical reservoir model was set up. The temperature model from the first phase provided the boundary conditions for the reservoir model.
Hydraulic parameters for the target horizons such as porosity and permeability were taken from data available from the nearby exploration wells. The aim is to predict the temperature evolution, both at the producer and injector location. The main interest lies in the issue whether production temperatures can be maintained throughout the years or not, and how far the cooling area around the injector extends. Several runs were performed, varying the hydraulic properties in a reasonable range. The geometry was modified as well, according to different locations of the producer. The model was designed in order to ensure its long term usage in the project. To accomplish this, the model will be constructed to allow iterative updates, assimilating new information gained during the drilling, testing and production phase.