## 8 Conclusions  
We demonstrated the feasibility of using the CSEM method to monitor the subtle resistivity changes inside the TU Delft campus low-enthalpy reservoir model. In this feasibility study, we determined a survey design--including the survey configuration, source frequency, and source offset--that allows for the CSEM monitoring of the resistivity changes in the TU Delft campus reservoir with sufficient confidence. The results of the study indicated that the \(z\)-component determined with a surface-to-borehole CSEM is sensitive to resistivity changes of different volumes and contrasts, suggesting its suitability for monitoring changes in the reservoir due to heat production over decades.  
Through this study, we showed that the CSEM monitoring of the TU Delft campus geothermal reservoir seems possible, even in the presence of undesired effects. Among these effects, survey repeatability errors had the largest impact on CSEM monitoring. The effect of the steel casing was negligible 100 m away from it. When we changed the properties of the casing from steel to composite, we found that the electric field response was only affected within the casing. Generally speaking, the CSEM method with a customized acquisition setup can be used to detect small resistivity changes in the TU Delft campus low-enthalpy reservoir with high confidence, which will not be obscured by undesired effects.  
Overall, the results of this feasibility study demonstrate that the CSEM has high potential as a viable technology for monitoring and managing low-enthalpy geothermal reservoirs, such as the TU Delft campus reservoir. The results of our study indicate that time-lapse CSEM surveys can provide information to make well-informed management decisions, possibly extending the production lifetime of low-enthalpy reservoirs. The approach followed in this study can serve as a framework for future CSEM field tests and, when successful, eventually for monitoring campaigns. This also includes monitoring high-enthalpy geothermal reservoirs.  
**Author Contributions:** Conceptualization, M.E., D.W., G.D. and E.S.; methodology, M.E., D.W. and E.S.; software, M.E. and D.W.; validation, M.E., D.W., G.D. and E.S.; formal analysis, M.E., D.W., G.D. and E.S.; investigation, M.E.; resources, G.D.; data curation, M.E.; writing--original draft preparation, M.E.; writing--review and editing, M.E., D.W., G.D. and E.S.; visualization, M.E.; supervision, D.W., G.D. and E.S.; project administration, G.D.; funding acquisition, G.D. All authors have read and agreed to the published version of the manuscript.  
This project received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 956965, [[https://cordis.europa.eu/project/id/956965](https://cordis.europa.eu/project/id/956965)]([https://cordis.europa.eu/project/id/956965](https://cordis.europa.eu/project/id/956965)), accessed on 15 December 2020.  
Not applicable.  
**Data Availability Statement:** All data and Python scripts supporting the findings of this study are available upon request from the corresponding author.  
The authors declare no conflict of interest.  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} CSEM & Controlled-source electromagnetic \\ TU Delft & Delft University of Technology \\ EM & Electromagnetic \\ ERT & Electrical resistivity tomography \\ MT & Magnetotelluric \\ SNR & Signal-to-noise ratio \\ FDEM & Frequency-domain electromagnetic \\
2D & Two-dimensional \\
1D & One-dimensional \\
3D & Three-dimensional \\ \end{tabular}