Acta Geophysica

, Volume 66, Issue 2, pp 191–201 | Cite as

Generating porosity spectrum of carbonate reservoirs using ultrasonic imaging log

  • Jie Zhang
  • Xin Nie
  • Suyun Xiao
  • Chong Zhang
  • Chaomo Zhang
  • Zhansong Zhang
Research Article - Applied Geophysics


Imaging logging tools can provide us the borehole wall image. The micro-resistivity imaging logging has been used to obtain borehole porosity spectrum. However, the resistivity imaging logging cannot cover the whole borehole wall. In this paper, we propose a method to calculate the porosity spectrum using ultrasonic imaging logging data. Based on the amplitude attenuation equation, we analyze the factors affecting the propagation of wave in drilling fluid and formation and based on the bulk-volume rock model, Wyllie equation and Raymer equation, we establish various conversion models between the reflection coefficient β and porosity ϕ. Then we use the ultrasonic imaging logging and conventional wireline logging data to calculate the near-borehole formation porosity distribution spectrum. The porosity spectrum result obtained from ultrasonic imaging data is compared with the one from the micro-resistivity imaging data, and they turn out to be similar, but with discrepancy, which is caused by the borehole coverage and data input difference. We separate the porosity types by performing threshold value segmentation and generate porosity–depth distribution curves by counting with equal depth spacing on the porosity image. The practice result is good and reveals the efficiency of our method.


Carbonate reservoir Porosity spectrum Well logging analysis Ultrasonic imaging logging 

List of symbols


Amplitude, L, m


Frequency, 1/t, Hz


Propagation distance, L, m


Average distance from the transducer to the borehole wall at the same depth, L, m


The ratio of number of pixels, n/n, 1


Unit volume particle number, n, 1


Radius of spherical particles, L, m


Wave propagation speed, L/t, m/s


Ultrasonic transmission speed in the drilling mud, L/t, m/s


Shale volume content, L3/L3, %


Wave impedance, m/L2t, g/cm3 m/s


Amplitude attenuation coefficient, L/L, 1


Reflection coefficient, L/L, 1


Near-borehole formation interval transit time, t, s


Water interval transit time, t, s


Matrix interval transit time, t, s


Shale interval transit time, t, s


Wavelength of ultrasound, L, m


Medium viscosity, mt/L2, Pa s


Kinematic viscosity of fluid, mt/L2, Pa s


Density, m/L3, g/m3


Density of fluid, m/L3, g/m3


Near-bore formation density, m/L3, g/m3


Density of matrix, m/L3, g/m3


Density of particles, m/L3, g/m3


Density of water/fluid, m/L3, g/m3


Attenuation factor, L/L, 1


Porosity, L3/L3, %


Foreground average porosity, L3/L3, %


Background average porosity, L3/L3, %



This research is supported by National Natural Science Foundation of China (Grant nos. 41504094 and 41404084). The authors thank the editor and the two reviewers for their constructional comments and suggestions. Dr. Xin Nie’s visiting research in Georgia Institute of Technology is supported by China Scholarship Council (CSC).

Compliance with ethical standards

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.


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Copyright information

© Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences 2018

Authors and Affiliations

  1. 1.Key Laboratory of Exploration Technologies for Oil and Gas Resources (Yangtze University)WuhanChina
  2. 2.School of Geophysics and Oil ResourceYangtze UniversityWuhanChina
  3. 3.Georgia Institute of TechnologyAtlantaUSA
  4. 4.Jianghan Oilfield Branch of Sinopec GroupQianjiangChina

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