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Inversion of Time-Lapse Electric Potential Data to Estimate Fracture Connectivity in Geothermal Reservoirs

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Abstract

An inverse modeling approach was developed to characterize fracture connectivity in geothermal reservoirs using an injection of a conductive fluid and time-lapse electric potential measurements. Discrete fracture networks with sparsely connected fractures were modeled and a flow simulator was used to solve electric fields as a conductive tracer flows through the fracture networks. The electric potential difference between well pairs drops progressively in time as the conductive fluid fills interconnected fractures along paths from the injector toward the producer. Therefore, the fractional connected area of reservoirs could be estimated using inverse modeling to match the response to other fracture networks by comparing time histories of the electric potential. This method was compared to estimating fractional connected area using tracer return curves alone and the study showed that locations of connected areas were estimated better using the electric potential approach. A sensitivity analysis was performed to study the effect of fractional connected area on time-lapse electric potential and tracer return data. The study verified the advantages of using electric potential measurements instead of only the tracer return curves.

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Acknowledgments

This research was supported by the US Department of Energy, under Contract DE-EE0005516. The Stanford Geothermal Program is grateful for this support.

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  1. Department of Energy Resources Engineering, Stanford University, 367 Panama St., Stanford, CA,  94305, USA

    Lilja Magnusdottir & Roland N. Horne

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  1. Lilja Magnusdottir
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Correspondence to Lilja Magnusdottir.

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Magnusdottir, L., Horne, R.N. Inversion of Time-Lapse Electric Potential Data to Estimate Fracture Connectivity in Geothermal Reservoirs. Math Geosci 47, 85–104 (2015). https://doi.org/10.1007/s11004-013-9515-9

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