Analyzing Fractures Using Time-Lapse Electric Potential Data
- Jason Hu (Stanford University, Current: Arundo Analytics) | Roland Horne (Stanford University)
- Document ID
- Society of Petroleum Engineers
- SPE Annual Technical Conference and Exhibition, 30 September - 2 October, Calgary, Alberta, Canada
- Publication Date
- Document Type
- Conference Paper
- 2019. Society of Petroleum Engineers
- Fracture Characterization, Electrical Simulation, History Matching, Parameter Finding, Discrete Fracture Modeling
- 15 in the last 30 days
- 252 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 9.50|
|SPE Non-Member Price:||USD 28.00|
Characterizing the fractures is an important task to improve the understanding and utilization of hydraulic fracturing. As an approach to augment and improve on the existing methods, time-lapse electric potential measurements could be used to characterize subsurface features. In this study we investigated the characterization of fracture length and fracture density by using time-lapse electric potential data. A new borehole ERT (electric resistivity tomography) method designed specifically for hydraulic fracture characterization is proposed to better capture reservoir dynamics during hydraulic fracturing. This method uses high resolution electric potential data by implementing electrodes in or near boreholes and monitor electric potential distribution near the horizontal fracture zone. The time-lapse electric potential data generated by this tool were simulated and subsequently used to analyze fracture characteristics. Inverse analysis was then performed on the electric potential data to estimate fracture length and fracture density. Last, we performed sensitivity analysis to examine the robustness of the estimates in nonideal environments. The results of this work show that time-lapse electric potential data are capable of capturing flow dynamics during the fracturing process. Using the proposed borehole ERT method we successfully estimated the true fracture length and true fracture density of a constructed fracture model. We were able to determine the best locations in the constructed reservoir to place the electrodes, and through sensitivity analysis we found the maximum noise level of the electric potential data that can still allow the proposed method to make robust fracture length and fracture density estimates.
Our proposed method offers a new approach to make robust estimates of fracture length and fracture density. Electric potential data have been used mostly for well logging in the past. This study demonstrates a novel way of using electric potential data in unconventional development and opens possibilities for more applications such as production monitoring.
|File Size||1 MB||Number of Pages||16|
Adachi, J. I., Detournay, E., and Peirce, A. P. 2010. Analysis of the classical pseudo-3D model for hydraulic fracture with equilibrium height growth across stress barriers. International Journal of Rock Mechanics and Mining Sciences, 47(4), 625–639. https://doi.org/10.1016/j.ijrmms.2010.03.008.
Archie, G. E. 1942. The Electrical Resistivity Log as an Aid in Determining Some Reservoir Characteristics. Transactions of the AIME, 146(01), 54–62. https://doi.org/10.2118/942054-G.
Carrigan, C. R., Yang, X., LaBrecque, D. J.et al. 2013. Electrical resistance tomographic monitoring of CO2 movement in deep geologic reservoirs. International Journal of Greenhouse Gas Control, 18, 401–408. https://doi.org/10.1016/j.ijggc.2013.04.016.
Geuzaine, C. and Remacle, J.-F. 2009. Gmsh: a three-dimensional finite element mesh generator with built-in pre-and post-processing facilities. International Journal for Numerical Methods in Engineering 79(11), 0, 1309–1331. https://doi.org/10.1002/nme.2579.
Karimi-Fard, M. and Firoozabadi, A. 2001. Numerical Simulation of Water Injection in 2D Fractured Media Using Discrete-Fracture Model. Presented at the SPE Annual Technical Conference and Exhibition, New Orleans, 30 September-3 October. SPE-71615-MS. https://doi.org/10.2118/71615-MS.
Lagarias, J. C., Reeds, J. A., Wright, M. H.et al. 1998. Convergence Properties of the Nelder--Mead Simplex Method in Low Dimensions. SIAM Journal on Optimization, 9(1), 112–147. https://doi.org/10.1137/S1052623496303470.
Magnusdottir, L. and Horne, R. N. 2015. Inversion of Time-Lapse Electric Potential Data Reservoirs. Mathematical Geosciences, 47(1), 85–104. https://doi.org/10.1007/s11004-013-9515-9.
Nelder, J. A. and Mead, R. 1965. A Simplex Method for Function Minimization. The Computer Journal, 7(4), 308–313. https://doi.org/10.1093/comjnl/7.4.308.
Rin, R., Tomin, P., Garipov, T.et al. 2017. General Implicit Coupling Framework for Multi-Physics Problems. Presented at the SPE Reservoir Simulation Conference, Montgomery, 20-22 Februray. SPE-182714-MS. https://doi.org/10.2118/182714-MS.
Rios, L. M. and Sahinidis, N. V. 2013. Derivative-free optimization: A review of algorithms and comparison of software implementations. Journal of Global Optimization, 56(3), 1247–1293. https://doi.org/10.1007/s10898-012-9951-y.
Schmidt-Hattenberger, C., Bergmann, P., Kießling, D.et al. 2011. Application of a Vertical Electrical Resistivity Array (VERA) for monitoring CO2 migration at the Ketzin site: First performance evaluation. Energy Procedia, 4, 3363–3370. https://doi.org/10.1016/j.egypro.2011.02.258.