1.College of Resources, Shandong University of Science and Technology, Tai'an 271019, China
2.School of Geosciences, China University of Petroleum, Qingdao 266580, China
3.College of Mechanical & Electronic Engineering, Shandong Agricultural University, Tai'an 271018, China
4.Department of Nuclear Science and Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
mtlyab@sdau.edu.cn
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Li Zhang, Hua-Wei Yu, Yang Li, 等. Improved formation density measurement using controllable D-D neutron source and its lithological correction for porosity prediction[J]. Nuclear Science and Techniques, 2022,33(1):3
Li Zhang, Hua-Wei Yu, Yang Li, et al. Improved formation density measurement using controllable D-D neutron source and its lithological correction for porosity prediction[J]. Nuclear Science and Techniques, 2022,33(1):3
Li Zhang, Hua-Wei Yu, Yang Li, 等. Improved formation density measurement using controllable D-D neutron source and its lithological correction for porosity prediction[J]. Nuclear Science and Techniques, 2022,33(1):3 DOI: 10.1007/s41365-022-00988-1.
Li Zhang, Hua-Wei Yu, Yang Li, et al. Improved formation density measurement using controllable D-D neutron source and its lithological correction for porosity prediction[J]. Nuclear Science and Techniques, 2022,33(1):3 DOI: 10.1007/s41365-022-00988-1.
Controllable D-D neutron sources have a long service life, low cost, and non-radioactivity. There are favorable prospects for its application in geophysical well logging, since traditional chemical radioactive sources used for well logging pose potential threats to the safety of the human body and environment. This paper presents an improved method to measure formation density that employs a D-D neutron source. In addition, the lithological effect on the measured density was removed to better estimate the formation porosity. First, we investigated the spatial distribution of capture gamma rays through Monte Carlo simulations as well as the relationship between the ratio of capture gamma ray counts and formation density to establish theoretical support for the design of density logging tools and their corresponding data processing methods. Second, we obtained the far to near detector counts of captured gamma rays for an optimized tool structure, and then established its correlation with the density and porosity of three typical formations with pure quartz, calcite, and dolomite minerals. Third, we determined the values for correcting the densities of sandstone and dolomite with the same porosity using limestone data as the reference and established the equations for calculating the correction values, which lays a solid foundation for accurately calculating formation porosity. We observed that the capture gamma ray counts first increased then decreased and varied in different formations; this was especially observed in high-porosity formations. Under the same lithologic conditions (rock matrix), as the porosity increases, the peak value of gamma ray counts moves toward the neutron source. At different detector-source distances, the ratio of the capture gamma ray counts was well correlated with the formation density. An equation of the formation density conversion was established based on the ratio of capture gamma ray counts at the detector-source distances of 30 cm and 65 cm, and the calculated values were consistent with the true values. After correction, the formation density was highly consistent with the true value of the limestone density, and the mean absolute error was -0.013 g/cm,3,. The calculated porosity values were very close to the true values, and the mean relative error was 2.33%, highlighting the accuracy of the proposed method. These findings provide a new method for developing D-D neutron source logging tools and their well-log data processing methods.
Density measurementD-D Neutron SourceLithological correctionPorosity prediction
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