LU Zhendong, LIU Chenglin, ZENG Xiaoxiang, YANG Hong, ZANG Qibiao, WU Yuping, LI Guoxiong, FENG Dehao. Shale oil size distribution models and their sensitivitiesJ. PETROLEUM GEOLOGY & EXPERIMENT, 2022, 44(4): 730-738. DOI: 10.11781/sysydz202204730
Citation: LU Zhendong, LIU Chenglin, ZENG Xiaoxiang, YANG Hong, ZANG Qibiao, WU Yuping, LI Guoxiong, FENG Dehao. Shale oil size distribution models and their sensitivitiesJ. PETROLEUM GEOLOGY & EXPERIMENT, 2022, 44(4): 730-738. DOI: 10.11781/sysydz202204730

Shale oil size distribution models and their sensitivities

  • With the rapid development of unconventional oil and gas resources, the demand for corresponding evaluation methods is increasing. At present, the evaluation methods for unconventional oil and gas resources are divided into analogy, statistical and genetic method. While constantly innovating evaluation methods, how to improve conventional methods and apply them to unconventional resource evaluation is also a focus and difficulty in current research. Taking a well as an unit and the EUR of the well as the unit's oil or gas reserves, a Pareto distribution model was established, and a program was compiled according to the principle of random sampling and skew sampling to analyze the sensitivity of number N, shape parameter and exploration coefficient E to the model. This method was applied to the shale oil resource evaluation in the X230 well block in Heshui area of Ordos Basin. Results show that the number of discoveries affects the size and dispersion of the parameters for oilfield distribution. The distribution model tends to be stable when the number is more than 300. Exploration coefficient has little influence on the sensitivity of distribution model, which is the limitation of taking EUR as evaluation unit. According to the variation of number N with shape parameter β, the number corresponding to cut-off point can be determined, that is, the sum of EUR of all wells is the recoverable resource of the area, which is 6.72×106 t. The result is consistent with the evaluation of oil and gas resource abundance. This method can provide guidance for unconventional oil and gas resources evaluation.
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