Volume 44 Issue 1
Jan.  2016
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WENG Dingwei, FU Haifeng, LU Yongjun, ZHENG Lihui, MA Jianjun. A Model for Predicting the Volume of Stimulated Reservoirs[J]. Petroleum Drilling Techniques, 2016, 44(1): 95-100. DOI: 10.11911/syztjs.201601018
Citation: WENG Dingwei, FU Haifeng, LU Yongjun, ZHENG Lihui, MA Jianjun. A Model for Predicting the Volume of Stimulated Reservoirs[J]. Petroleum Drilling Techniques, 2016, 44(1): 95-100. DOI: 10.11911/syztjs.201601018
shu

A Model for Predicting the Volume of Stimulated Reservoirs

  • 1.

    College of Petroleum Engineering, China University of Petroleum(Beijing), Beijing, 102249, China;

  • 2.

    Langfang Branch, PetroChina Research Institute of Petroleum Exploration and Development, Langfang, Hebei, 065007, China;

  • 3.

    Jiudong Operational Zone, PetroChina Yumen Oilfield Company, Jiuquan, Gansu, 735200, China

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  • Received Date: April 06, 2015
  • Revised Date: October 29, 2015
    Graphical Abstract
    • Abstract
  • In order to better understand the stimulated reservoir volume (SRV), to improve the SRV technology and predict it more accurately, large-scale physical simulation tests were deployed to analyze the relationship between acoustic events and fracture morphology. Based on the results of the physical simulation tests, a SRV predicting model was built for calculating the stimulated reservoir volumes with different fracture conductivity, the viscosity of fracturing fluid and net pressure. The result showed that calculated SRV is in inverse proportion to fracturing fluid viscosity, and in linear relationship with both fracture conductivity and net pressure. The SRV is the most sensitive to fracturing fluid viscosity, followed by fracture conductivity, and then the least to net pressure. The SRV model has been used to predict the stimulated reservoir volume in 7 fractured wells in a domestic tight oil field, the fitting curve for SRVs and post-fracturing oil production rate was made to be a linear relationship, with the coefficient of correlation 0.840. It is indicated that the SRV predicting model was in better correlation with the post-fracturing oil production rate, which, in the future, can be taken as the guidance of SRV fracturing.
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    • References (19)
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