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New Intelligent Model of Cuttings Logging Based on Grey Clustering

  • INNOVATIVE TECHNOLOGIES OF OIL AND GAS
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Chemistry and Technology of Fuels and Oils Aims and scope

With the deepening of exploration and development, the lithology of the drilling strata becomes more complex. Using the digital technology for processing the data obtained by the cuttings logging helps to provide accurate lithological data and evaluate clamping of the formation interface. However, the existing logging digitization technology relies on element logging and is restricted by the large error of the cuttings logging instrument, the disunity of multi-source data, and the poor pertinence of data. In this paper, we propose an intelligent identification model of the cuttings logging based on grey clustering analysis. First, the grey prediction method is used for processing the in-depth instrument data, and then the extended Kalman filter is used to standardize and unify the multi-instrument data. Finally, the identification model based on the grey clustering method is applied to identify the cuttings. The results of the simulation analysis and field application show that the identification model proposed in this paper can accurately identify the rock strata. Compared with the traditional methods, the accuracy of the proposed has been greatly improved. The field applications show that the model provides important theoretical support for the development of rock-cutting digital technology.

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Authors and Affiliations

  1. School of Electrical Engineering and Information, Southwest Petroleum University, Chengdu, 610500, China

    Haiying Xu & Jiansheng Liu

  2. School of Mechanical Engineering, Southwest Petroleum University, Chengdu, 610500, China

    Gang Liu, Jiangna Cao & Shuo Yang

Authors
  1. Haiying Xu
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  2. Gang Liu
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  3. Jiangna Cao
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  4. Shuo Yang
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  5. Jiansheng Liu
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Correspondence to Haiying Xu.

Additional information

Translated from Khimiya i Tekhnologiya Topliv i Masel, No. 4, pp. 72–76, July–August, 2021.

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Xu, H., Liu, G., Cao, J. et al. New Intelligent Model of Cuttings Logging Based on Grey Clustering. Chem Technol Fuels Oils 57, 653–664 (2021). https://doi.org/10.1007/s10553-021-01290-3

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  • DOI: https://doi.org/10.1007/s10553-021-01290-3

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