François Bretaudeau

Advanced seismic processing/imaging techniques and their potential for geothermal exploration

Seismic reflection imaging is a geophysical method that provides greater resolution at depth than other methods and is, therefore, the method of choice for hydrocarbon-reservoir exploration. However, seismic imaging has only sparingly been used to explore and monitor geothermal reservoirs. Yet, detailed images of reservoirs are an essential prerequisite to assess the feasibility of geothermal projects and to reduce the risk associated with expensive drilling programs. The vast experience of hydrocarbon seismic imaging has much to offer in illuminating the route toward improved seismic exploration of geothermal reservoirs — but adaptations to the geothermal problem are required. Specialized seismic acquisition and processing techniques with significant potential for the geothermal case are the use of 3D arrays and multicomponent sensors, coupled with sophisticated processing, including seismic attribute analysis, polarization filtering/migration, converted-wave processing, and the analysis of the diffracted wavefield. Furthermore, full-waveform inversion and S-wave splitting investigations potentially provide quantitative estimates of elastic parameters, from which it may be possible to infer critical geothermal properties, such as porosity and temperature.

Practical Inversion of Electric Resistivity in 3D from Frequency-domain Land CSEM Data

EM prospection are method of choice for many applications such as deep water or geothermal prospection because of their sensitivity to electrical resistivity and their potential to investigate at depths of 500m or even more. However, the investigated areas in Europe are usually urbanised and industrialised so high level of cultural noise prevents from the use of MT. Land CSEM is an alternative. But cost and logistical constrains may limits to the use of a small number of transmitter positions, often only one. The inversion of CSEM data in the near field using a single transmitter position suffers from critical sensitivity singularities due to the unsymmetrical illumination. To overcome this problem we proposed an inversion framework adapted to this ill-conditioned inversion problem. The framework relies specifically on a robust Gauss-Newton solver, on model parameter transformations and data reformulation under the form of pseudo-MT tensors. We describe here the modelling and inversion approach implemented in our code POLYEM3D and describe the framework proposed for its practical application. We illustrate its application on synthetic cases and then show the application of the process to a real CSEM dataset acquired for thermal water prospection at a few kilometer from a nuclear power plant in France.