LIN Jingqi, MENG Xin, LI Qingqing, CAO Zhifeng, ZHANG Kai, MU Li. Characterization Method and Application of Electrical Imaging Logging in Conglomerate Reservoir: A Case Study in Mahu Sag of Junggar Basin[J]. Petroleum Drilling Techniques, 2022, 50(2): 126-131. DOI: 10.11911/syztjs.2022059
Citation: LIN Jingqi, MENG Xin, LI Qingqing, CAO Zhifeng, ZHANG Kai, MU Li. Characterization Method and Application of Electrical Imaging Logging in Conglomerate Reservoir: A Case Study in Mahu Sag of Junggar Basin[J]. Petroleum Drilling Techniques, 2022, 50(2): 126-131. DOI: 10.11911/syztjs.2022059

Characterization Method and Application of Electrical Imaging Logging in Conglomerate Reservoir: A Case Study in Mahu Sag of Junggar Basin

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  • Received Date: August 15, 2021
  • Revised Date: February 24, 2022
  • Available Online: March 10, 2022
  • Because the conglomerate reservoir in Mahu Sag of Junggar Basin has rich electrical imaging logging data, the processing method and further applications of electrical imaging logging data for conglomerate reservoirs were studied to make full use of the advantage of high-resolution electrical imaging in rock composition, heterogeneity, and reservoir structure characterization. Considering the resistivity difference of rock compositions in electrical ima-ging of conglomerate reservoirs, the cut-off value of resistivity was determined through core calibration, and the calcu-lation method for the relative content of gravel, sand, and argillaceous parts as well as the grain size analysis method of cumulative pseudo-grain-size probability curves were constructed. Through mathematical statistics, the methods for calculating the sorting coefficient, porosity, fracture porosity, and high-precision resistivity were established. Based on the understanding of the main controlling factors of conglomerate reservoirs, it was proposed that the energy storage indexes for evaluating the reservoir performance of conglomerate reservoir could be used to develop a new method for identifying reservoir fluid properties by the variance of apparent formation water resistivity spectra and reservoir indexes on the basis of electrical imaging. The energy storage indexes mainly included the rock composition factor, porosity of electrical imaging logging, heterogeneity factor, and fracture factor, etc. The research results show that the electrical imaging logging data can effectively evaluate the physical properties and oil-bearing properties of conglo-merate reservoirs, with good application effects in evaluation of field exploration. It has provided a reference for further application of electrical imaging logging data in conglomerate reservoirs.
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