A study on 4D inversion of time-lapse magnetotelluric data sets for monitoring geothermal reservoir

Abstract:

The productivity of geothermal reservoir, which is function of pore-space and fluid-flow path of the reservoir, varies since the properties of reservoir changes with geothermal electricity generation. The variation in the reservoir properties causes changes in electrical resistivity, time-lapse (TL) three-dimensional (3D) magnetotelluric (MT) methods can be applied to monitor the productivity variation of geothermal reservoir thanks to its sensitive to the electrical resistivity of deep subsurface. For an accurate interpretation of TL 3D MT data, a 4D MT inversion algorithm has been developed to simultaneously invert all vintage data in a time-coupled way. However, the changes in electrical resistivity of deep geothermal reservoirs are usually small generating minimum variation in TL MT responses. In order to reduce TL inversion artifacts emphasizing the TL changes, we upgrade the TL coupling of the original 4D inversion algorithm with active time constraint (ATC), which has been verified to be efficient for resistivity monitoring based on TL electrical resistivity surveys. In order to maximize the sensitivity to reservoir-region resistivity changes, we further developed a focused 4D MT inversion method by considering the distribution of reservoir fractures. To analyze the validity of the 4D algorithms, we make 4D MT inversion of synthetic TL data sets applying ATC and focusing methods, respectively, and compare their results those from the original 4D algorithm. The numerical tests find that ATC 4D inversion can be useful for conventional geothermal reservoirs, while the focused inversion algorithm can be better for monitoring engineering geothermal system (EGS) reservoir, within which new fracture can be actively developed by fluid circulation during production. This work is supported by KETEP granted by MOTIE, KOREA (NO. 20133030000220).