Mobile Networks and Management. 9th International Conference, MONAMI 2017, Melbourne, Australia, December 13-15, 2017, Proceedings

Research Article

Application of Fuzzy Comprehensive Evaluation Method for Reservoir Well Logging Interpretation While Drilling

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  • @INPROCEEDINGS{10.1007/978-3-319-90775-8_7,
        author={Zhaohua Zhou and Shi Shi and Shunan Ma and Jing Fu},
        title={Application of Fuzzy Comprehensive Evaluation Method for Reservoir Well Logging Interpretation While Drilling},
        proceedings={Mobile Networks and Management. 9th International Conference, MONAMI 2017, Melbourne, Australia, December 13-15, 2017, Proceedings},
        proceedings_a={MONAMI},
        year={2018},
        month={5},
        keywords={Fuzzy comprehensive evaluation Well logging Reservoir},
        doi={10.1007/978-3-319-90775-8_7}
    }
    
  • Zhaohua Zhou
    Shi Shi
    Shunan Ma
    Jing Fu
    Year: 2018
    Application of Fuzzy Comprehensive Evaluation Method for Reservoir Well Logging Interpretation While Drilling
    MONAMI
    Springer
    DOI: 10.1007/978-3-319-90775-8_7
Zhaohua Zhou1,*, Shi Shi1,*, Shunan Ma2,*, Jing Fu1,*
  • 1: PetroChina Research Institute of Petroleum Exploration and Development
  • 2: Chinese Academy of Science
*Contact email: zhaohua69@petrochina.com.cn, shishi69@petrochina.com.cn, mashunan@iie.ac.cn, fujing0602@126.com

Abstract

Reservoir classification and evaluation is the base for gas reservoir description. Well logging interpretation while drilling technique collects drilling logging signal in real-time through the sensor module, and transmits to the database server wirelessly. Well logging interpretation model is applied to reservoir information analysis, which is important to describe gas reservoirs accurately. Because of complicated geological conditions, there is a deviation in single well logging interpretation model. To solve the problem, a reservoir well logging evaluation while drilling method based on fuzzy comprehensive evaluation is proposed. Key parameters affecting reservoir evaluation, such as porosity, permeability and gas saturation are considered. Fully mining the information contained in GR, SP, AC and RT well logging data. Firstly, the reservoir is divided into gas, poor-gas, dry layer and water layer. For each well logging method, statistical method is used to calculate the subordinate intervals of each reservoir’s parameters, and the membership degree is calculated to form the evaluation matrix of the well logging method. Then, the weight of each parameter is selected to form the comprehensive evaluation weight matrix, and fuzzy comprehensive evaluation result of well logging is computed. Finally, the comprehensive evaluation results of different well logging methods are composed to evaluation matrix, and fuzzy comprehensive evaluation method is used again to get the final reservoir evaluation category, so as to provide scientific basis for gas field development decision making.