MagnetoTelluric in combination with seismic data for geothermal exploration. A. Manzella 1 V. Spichak 2. 1 National Research Council – Institute of Geosciences and Earth Resources(CNR-IGG), Pisa, Italy 2 GEMRC IPE RAS, Troitsk, Russia. Why resistivity?.
1National Research Council – Institute of Geosciences and Earth Resources(CNR-IGG), Pisa, Italy
2GEMRC IPE RAS, Troitsk, Russia
Geothermal waters have high concentrations of dissolved salts which provide conducting electrolytes within a rock matrix
The conductivities of both the electrolytes and the rock matrix are temperature dependent in a manner that causes a large reduction of the bulk resistivity with increasing temperature.
The resulting resistivity is also related to the presence of clay minerals, and can be reduced considerably when the clay minerals are broadly distributed.
From Anderson et al., WGC2000
From Pellerin et al., 1996
Resistivity should be always considered with care. Experience has shown that the apparent one-to-one correlation between low resistivity and the presence of fluids is not correct, since alteration minerals produce comparable, and often higher reduction of resistivity with respect to fluid flow.
From Flovenz et al., WGC2005
Moreover, although the geothermal systems have an associated low-resistivity signature, the converse is not true.
Seismic (reflection more often used)
Regional exploration: methodsMT examples
MinamikayabeGeothermal field, Japan
Takigami Geothermal Area, Japan
From Spichak 2003
Highly conductive areas with apparent resistivity values not exceeding 6 Ohm⋅m
From Ushijima et al., WGC 2005
“the low resistivity zone in the northeastern part is intensive and shallower than that in the southwestern par, in good agreement with the geological feature”
Mt. Amiata Geothermal Area, Italy
From Volpi et al., 2003
The interpretation revealed a good correlation between the feature of the geothermal field and the resistivity distribution at depth
From Romo et al., WGC 2000
The results suggest the presence of a highly attenuating and conductive zone along El Azufre Canyon, which corresponds with the production interval of wells LV-2 and LV-3/4. A graben structure is outlined.
Ogiri geothermal zone, Japan
From Uchida, 2005
3-D view of the resistivity model, from south. Shallow blocks to a 200m depth are stripped out and approximate locations of three faults are overlaid.
(2D and 3D reflection more often used)
Fracture/fault detection methods
Fracture/fault detection: methodsMT examples
Takigami Gothermal Area, Japan
Mt. Amiata Geothermal Area, Italy
From Tagomori et al., WGC 2005
“the large lost circulation occurred at the depth of 1300 m BSL for the well TT-14R (90 t/h) when the well crossed through the electrical discontinuity Fb”
From Fiordelisi et al., WGC 2000
Note the very steep conductor and its correspondence in location to the fault defined by seismic reflection data.
It is very effective for gas or for oil investigation (water flood). Very expensive
Not so easy to manage for geothermal since resolution is lower (VP and VS change is smaller than for oil)Monitoring
Phase change of pore fluid (boiling/condensing) in fractured rocks can result in resistivity changes that are more than an order of magnitude greater than those measured in intact rocks
Production-induced changes in resistivity can provide valuable insights into the evolution of the host rock and resident fluids.
No examples or applications found in literature
Some examples from SP (electric field) showing interesting results: is it possible to use the same kind of information in MT? To be definedMonitoring
SP monitoring methodsMonitoring
From Marquis et al., 2002
“the correspondence between the start (and the end) of the stimulation and the increase (and decrease) in ΔV suggests a casual relationship between the two”
It can be done
When resistivity and VP changes depends on the same effect (e.g., permeability/porosity change) a resistivity-velocity cross-gradients relationship can be established and incorporated in a joint inversion scheme.
This approach requires a strong assumption: could be valid only for limited volumes and depths
From Gallardo and Meju, 2004
“Evolution of the joint inversion process. Shown are the resultant resistivity and velocity models for each iteration. Note the gradual development of common structural features in both sets of models during the process.”
Travale Geothermal Area, Italy
Quality of inversion results improves when external data are used. Here we show inversion results using an homogeneous a priori model (above) or a detailed a priori model where shallow lithological units have been identified from a resistivity point of view. The resulting models appear like out-of-focus in the first case, whereas it provides useful information for comparison with known geological structure in the second case.
The key element in the joint interpretation is the use of geothermal reservoir simulators to obtain a final model complying with all available data, both geophysical and thermo-hydraulic. To be evolved!
MT provides a useful contribution to geothermal exploration and exploitation, through careful data acquisition, processing, modeling and interpretation.
Its integration with other geological and geophysical data, in particular seismic, will improve the imaging of static and dynamic processes of geothermal systems.