4.7 Article

Elastic-Electrical Rock-Physics Template for the Characterization of Tight-Oil Reservoir Rocks

Journal

LITHOSPHERE
Volume 2021, Issue -, Pages -

Publisher

GEOSCIENCEWORLD
DOI: 10.2113/2021/3341849

Keywords

-

Funding

  1. National Natural Science Foundation of China [41974123]
  2. Postgraduate Research & Practice Innovation Program of Jiangsu Province
  3. Fundamental Research Funds for the Central Universities
  4. National Science and Technology Major Project of China [2017ZX05069-002]
  5. Jiangsu Province Science Fund for Distinguished Young Scholars [BK20200021]

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This study aims to characterize tight-oil reservoirs using a dual-porosity-clay parallel network electrical model and Hashin-Shtrikman and differential effective medium equations elastic model. By analyzing rock samples, log data, and microstructures, the effects of porosity and clay content on the elastic and electrical properties are studied to achieve good agreement between predictions and actual production reports.
Tight-oil reservoirs have low porosity and permeability, with microcracks, high clay content, and a complex structure resulting in strong heterogeneities and poor connectivity. Thus, it is a challenge to characterize this type of reservoir with a single geophysical methodology. We propose a dual-porosity-clay parallel network to establish an electrical model and the Hashin-Shtrikman and differential effective medium equations to model the elastic properties. Using these two models, we compute the rock properties as a function of saturation, clay content, and total and microcrack porosities. Moreover, a 3D elastic-electrical template, based on resistivity, acoustic impedance, and Poisson's ratio, is built. Well-log data is used to calibrate the template. We collect rock samples and log data (from two wells) from the Songliao Basin (China) and analyze their microstructures by scanning electron microscopy. Then, we study the effects of porosity and clay content on the elastic and electrical properties and obtain a good agreement between the predictions, log interpretation, and actual production reports.

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