IEEE Access (Jan 2024)

A Feasibility Study of Land CSEM Surveys With a Near-Casing Source for Hydraulic Fracturing Monitoring

  • Yao Lu,
  • Handong Tan,
  • Dikun Yang,
  • Zhigang Wang,
  • Yunjian Yang,
  • Liangjun Yan,
  • Wei Wan,
  • Hanbing Wang

DOI
https://doi.org/10.1109/ACCESS.2024.3370623
Journal volume & issue
Vol. 12
pp. 32238 – 32252

Abstract

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The land controlled-source electromagnetic (CSEM) method dynamically monitors reservoir fluid by contrasting electrical conductivity between hydraulic fracturing fluids and surrounding rock formations. In hydraulic fracturing monitoring, the underground steel casings represent significant high-conductivity objects that require accurate and rapid numerical modeling for understanding the CSEM responses and optimizing the survey configurations. To efficiently simulate the steel well casings, we made use of the modified finite volume method (FVM) with the concept of edge conductivity equivalence that avoids the computational cost of grid refinement down to millimeters or centimeters for the casing. The new algorithm is satisfactorily validated by a numerical comparison against a trusted program Dipole1D and a commercial program COMSOL. Then the algorithm is used to investigate the characteristic CSEM responses of injected fracturing fluid due to a galvanic electromagnetic (EM) source grounded near the head of steel-cased well, an unconventional configuration that can maximize the data anomaly by channeling more excitation current to the deep reservoir. In particularly, we simulated two fracturing scenarios with different fluid migration directions: one with a high-resistivity cap layer as the background and the other with a realistic heavy oil fracturing site from Karamay in Xinjiang, China. Our simulation shows that the configuration of near-casing excitation significantly enhances the electric-field anomalies of the fluid injection, which is the most prominent as the galvanic effect at low frequencies. These phenomena highlight the crucial role of steel casing in the CSEM method for hydraulic fracturing monitoring.

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