Over the past 35 years, geothermal projects have been developed in the Upper Rhine Graben (URG) to exploit deep geothermal energy. Underneath approximately 2 km of sedimentary deposits, the deep target consists of a granitic basement, which is highly fractured and hydrothermally altered. Therefore, it has high potential as a geothermal reservoir. Despite dense 2D seismic data coverage originally acquired for oil exploration (for a target two-way traveltime between 300 and 700 ms), the faults at the top of the granitic basement (between 1400 and 4000 ms) are poorly imaged, and their locations remain uncertain. To gain a better understanding of this large-scale faulting and to ensure the viability of future geothermal projects, a 3D seismic survey was acquired in the French part of the URG during the summer of 2018. This paper describes how an integrated project, combining seismic data processing, high-end imaging, and enhanced interpretation, was conducted to improve the understanding of this complex basin for geothermal purposes. By revealing the deep granite layer and its complex associated fault network, the insight from this project can help accurately locate future production wells.

No abstract

No abstract

No abstract

This paper presents the lessons learnt from a seismic reprocessing performed to improve the seismic reservoir characterization of a Middle East carbonate reservoir. The reservoir characterization objective is to optimize the porosity modeling driven by seismic data; hence, improving seismic amplitudes was crucial as they drive the inversion process for elastic properties. The new seismic reprocessing sequence was focused on the restoration of genuine primary amplitudes and improvement of the angle stacks design at the reservoir. In order to monitor the seismic amplitudes quality improvement throughout the processing sequence, a thorough quality assessment strategy has been implemented for decision making. It has allowed adjusting the amount of testing depending on the quality of intermediate results at selected key steps. The results obtained by using this QC strategy showed the importance to monitor in details the amplitudes quality progress by tuning at an early time the processing parameters that impact all the remaining steps. At the end of the reprocessing, a cleaner dataset, less affected by multiples interferences, with a more consistent amplitude balance and optimized angle stacks design has been obtained. It is deemed to be more appropriate for pre-stack inversion purposes in view of seismic reservoir characterization.