Quantitative Reservoir Characterization of Tight Sandstone Using Extended Elastic Impedance

Abstract

Quantitative inversion of reservoir properties plays a crucial role in the efficient development of tight sandstone reservoirs. Based on the theories of statistical rock physics and extended elastic impedance (EEI), a complete workflow for quantitative prediction of reservoir properties is developed and the key steps thereof are provided here. The square of S-velocity to P-velocity ratio (K), which is consistent with geological setting of a study area, is obtained from statistics of well data, the value of angle \(\chi\) most relevant to lithology and porosity is produced automatically by evaluating correlations of reservoir parameters with EEI, and the formulas that fit EEI with clay volume and with porosity are obtained. Then, angle \(\chi\) is applied to relevant EEI reflection coefficient data from amplitude variation with offset attribute cubes, the EEI related to clay volume and porosity is obtained through model-based constrained inversion on these data cubes, fitting formulas from well analysis are used to convert EEI data cubes to clay volume and porosity data cubes, and finally, the parameters of a tight sandstone reservoir are predicted quantitatively. The prediction results are consistent with production data from existing wells, indicating that the method proposed here is reliable.

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Acknowledgments

The study was funded by the Chinese National Science and Technology Major Project (Grant Number 2016ZX05047002). I am grateful to PetroChina Southwest Oil and Gas Field Company for providing the research data and samples.

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Correspondence to Chenglin Liu.

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Jiang, R., Liu, C., Zhang, J. et al. Quantitative Reservoir Characterization of Tight Sandstone Using Extended Elastic Impedance. Nat Resour Res (2020). https://doi.org/10.1007/s11053-020-09711-6

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Keywords

  • Extended elastic impedance
  • Tight sandstone
  • Quantitative reservoir characterization
  • Model-based constrained inversion
  • AVO attributes