To explore underground geothermal reservoirs and understand the natural processes of a geothermal system requires a way to visualise the subsurface environment and simulate underground processes. 3D computer modelling is the critical tool used for these visualisations and simulations, which conceptualise how the system “works”.
Conceptualisation offers explanations for processes such as subsurface fluid flow directions, interactions between different parts of the reservoir (e.g. upflow vs. outflow), the types of geothermal surface features (e.g. hot water springs, mud pools, steam vents, etc), and predictions for where the hottest part of the reservoir is located, and its depth. It also provides insights into information gaps and highlights the datasets required to fill those gaps.
3D visualisation models are a way to visualise and integrate many different spatial datasets (including any attribute with x,y,z coordinates) on a single platform.
These can include surface and subsurface data and information, including digital terrain models, geological maps, cross-sections and well logs (e.g., rock types, minerals), geophysical data (e.g., resistivity, gravity, magnetics, seismic tomography), geothermal fluid chemistry, and reservoir information (e.g. temperature, feed zones). The modelling process allows for interpolation between data points to build block volumes and isosurfaces (which represent points of equal values in a 3D surface).
Spatial relationships between selected datasets are easily viewed and manipulated, which lets the user assess interactive relationships between datasets and explore the on-going processes within a geothermal system. Models are used to assist with decision making during any stage of a geothermal system development, from the initial stages of exploration through to management of the producing geothermal field.
3D numerical reservoir models simulate reservoir processes, such as heat and fluid flow through a volume of rock, and are based on scientific laws, such as Conservation of Mass and Energy. These models are calibrated using real data.
In a numerical model, the area of interest is split, or discretised, into either points or small volumes, and the governing equations are solved for each of these. Rock properties, such as porosity, permeability, specific heat capacity and thermal conductivity, are assigned to all parts of the model. Sometimes this is done using a 3D geological model such as those visualised above, but other approaches are used. In recent times, much effort has been devoted to investigating the uncertainty in the rock properties in the parts of the model where there is no information, such as between wells.
Once the spatial properties of the model are defined, the user specifies other boundaries. For example, at the top of the model, atmospheric pressure, average temperature and some form of precipitation may be defined. At the bottom of the model, heat sources are added based on the best estimate of the location and temperature of hot upflows at the base of the geothermal system. Other features, such as wells, rivers, clay seals and faults, can also be built into the model.
Numerical reservoir models are commonly calibrated to pre-development measurements of temperature and pressure in wells (i.e. the natural state of the geothermal reservoir before fluid extraction). After heat and fluids have been extracted from a geothermal system, the model can be calibrated using ongoing measurements of heat (enthalpy) and steam flow.
A well-calibrated model gives the user confidence that the model is appropriate for forecasting future reservoir responses to changes, including management decisions. It is important to note that many different sets of parameters can produce a good model calibration, which means that a range of outcomes are possible for forecasts of the future. Uncertainty analysis techniques are used in models to explore the range and likelihood of different outcomes.
We ask questions of models, such as:
In the Geothermal:The Next Generation research programme, we are creating, testing and using a range of geological, geophysical, chemical and reservoir models to better understand deep geothermal systems in the Taupō Volcanic Zone.