A quick and rigorous approach for estimating reservoir permeability from dfi ts

Yuzhe Cai, Arash Dahi Taleghani, Robert Hawkes

Research output: Contribution to conferencePaperpeer-review

1 Scopus citations


Diagnostic fracture injection tests (DFITs) have been widely studied and implemented in unconventionalreservoirs to derive properties such as closure stress, pore pressure, and permeability. During a DFIT, asmall volume of water is pumped into a formation to create a small-sized crack. Formation permeabilityis typically obtained by means of modeling fluid leakoff during the shut-in period. Early studies haveassumed a constant fluid pressure boundary condition on the fracture walls or a constant leakoff rate intothe formation. However, the results deduced based on these assumptions may introduce significant errorsbecause the fluid pressure inside a fracture dissipates quickly as the fluid leaks off into the formation. Inthis study, we propose a material balance approach to obtain formation permeability using DFIT data. Theproposed analysis takes into account fluid leakoff during both fracture propagation and well shut-in periods.To model fluid leakoff during fracture propagation, we adopt the superposition principle to decomposethe problem into two separate problems; we then obtain the analytical solution. Two synthetic cases arepresented to validate the proposed analysis. The results suggest that the proposed approach provides a goodestimation of formation permeability. This approach has broad field application potential, as it can be usedeven when pressure data contains significant levels of noise. In addition, the solution is more accurate thanthose provided in available studies of formation permeability estimation using DFITs data, especially whenformation permeability is not extremely tight.

Original languageEnglish (US)
StatePublished - 2020
EventSPE Annual Technical Conference and Exhibition 2020, ATCE 2020 - Virtual, Online
Duration: Oct 26 2020Oct 29 2020


ConferenceSPE Annual Technical Conference and Exhibition 2020, ATCE 2020
CityVirtual, Online

All Science Journal Classification (ASJC) codes

  • Fuel Technology
  • Energy Engineering and Power Technology


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