Abstract
One of the requirements to realize electricity production from geothermal energy in the Netherlands is the exploration of the deep subsurface. Currently, detailed geological information below 5 kilometer is sparse. The magnetotelluric (MT) method, a passive electromagnetic method, is a candidate to acquire this information by geophysical surface exploration. Using
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the MT method, it is possible to image the subsurface resistivity structures. This is achieved by measuring the time-variations in the electromagnetic field at the surface of the Earth. Due to their specific resistivity response related to hydrothermal alteration mineralogy, MT is commonly applied for the exploration of volcanic geothermal systems. Being potentially useful for geothermal exploration, MT has no track record in sedimentary basins such as the Netherlands. Since the resisivity of the subsurface in the Netherlands is mainly controlled by porosity and permeability, MT can be utilized to detect, for example, porous formations or open faults and fractures. Two challenges are face when deploying MT in the Netherlands. First, distortion of the signal by cultural electromagnetic noise. Second, the conductive subsurface, making it hard to distinguish resistivity contrasts. As MT data acquired in the Netherlands are not available, data of geothermal projects, located in Philippines and Turkey are used for processing, modelling and interpretation. For re-processing of the Turkish data, a dedicated processing tool is developed. Of both projects the 3-D resistivity models produced by different inversion algorithms are qualitatively and quantitatively compared and interpreted. The Turkish geothermal system is interpreted as a layered system consisting of a conductive layer of volcanic rocks, an ophiolite complex and a limestone formation which forms the geothermal reservoir. The geothermal system is heated through faults and fractures by pluton some distance away. The geothermal project in Philippines, is characterized by the resistivity of the clay alteration mineralogy of a paleo hydrothermal system. The volcanic activity left a temperature imprint of alteration mineralogy on the resistivity model, overestimating the actual temperatures present in the subsurface. A more accurate interpretation is a fracture controlled geothermal system heated by remnant heat of the paleo volcanic system and cooled down from below. The two studied geothermal projects illustrate that besides geophysical information, also geochemical and geological data are required when interpreting a geothermal system. The lessons learned from the two geothermal projects are translated to the Dutch circumstances. Poor data can be partly avoided with good survey preparation and practice, while dedicated processing tools can improve the data quality after acquisition.Additionally, a successful exploration strategy of deep potential geothermal reservoirs can be achieved when using geological information derived from seismic data as ``a priori'' information in the inversion model.
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