Lithologic Reservoirs ›› 2026, Vol. 38 ›› Issue (2): 153-161.doi: 10.12108/yxyqc.20260214

• PETROLEUM EXPLORATION • Previous Articles     Next Articles

Optimized logging interpretation for tight glutenite reservoir based on beluga whale algorithm

PANG Zhichao1(), ZHANG Ben2(), DANG Wandi2, GAO Ming1, MAO Chenfei2, CHEN Guojun1   

  1. 1 Research Institute of Exploration and Development, Xinjiang Oilfield Company, PetroChina, Urumqi 830013, China
    2 Geological Research Institute, China National Logging Company, Xi’an 710021, China
  • Received:2024-11-21 Revised:2024-12-21 Online:2026-03-01 Published:2025-12-03

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Abstract:

To address the challenges of determining mineral composition and improving porosity estimation in deep glutenite reservoirs, taking the tight glutenite reservoirs of Cretaceous Qingshuihe Formation in the southern margin of Junggar Basin as an example, an optimized logging interpretation method based on the beluga whale optimization (BWO) algorithm was proposed, and the computational results of this method demonstrate higher consistency with the laboratory analysis data of core samples. The results show that: （1） The process of BWO-based optimized logging interpretation for reservoirs is as follows: By integrating data of core, thin section, and scanning electron microscopy, a multi-composition volumetric physical model of the study area is established; based on conventional logging data, a logging response equation is established and then solve it with BWO algorithm; with the least squares method as the basic theory, an optimized logging objective function is established by combining multiple volumetric physical model and logging response equation. （2） The proposed method demonstrates excellent global and local search capabilities, fast convergence, high computational accuracy, and strong scalability. Test simulations showed that the objective function stabilizes after approximately 40 iterations during logging curve inversion. The calculated mineral contents show good correlation with actual data, with mean absolute errors below 1.50% and mean relative errors below 11.50%. （3） The primary minerals of deep glutenite reservoir in the southern margin of Junggar Basin are quartz, feldspar, calcite, dolomite, and clay. The absolute errors for mineral content and porosity calculated by the BWO-based optimized logging interpretation method and the measured core data are less than 3.00% and 0.26%, respectively, significantly outperforming conventional methods.

Key words: beluga whale optimization algorithm, tight glutenite reservoir, multi-mineral volumetric physical model, optimal logging interpretation, geophysical inversion, Qingshuihe Formation, Cretaceous, southern margin of Junggar Basin

CLC Number: 

  • TE122

Fig. 1

Lithological characteristics of the glutenite reservoir in Cretaceous Qingshuihe Formation, southern margin of Junggar Basin"

Fig. 2

Pie chart of rock composition of the glutenite reservoir in Cretaceous Qingshuihe Formation, southern margin of Junggar Basin"

Fig. 3

Composition of clay minerals of the glutenite reservoir in Cretaceous Qingshuihe Formation, southern margin of Junggar Basin"

Fig. 4

Multicomposition volumetric physical model of the glutenite reservoir in Cretaceous Qingshuihe Formation, southern margin of Junggar Basin"

Fig. 5

Curve of the objective function changing with the number of iterations during BWO processing"

Fig. 6

Intersection results of inversion parameters of BWO-based optimized logging interpretation and structure actual parameters"

Table 1

Statistics of inversion reservoir parameter errors of BWO-based optimized logging interpretation"

储层参数 ϕ(石英) ϕ(长石) ϕ(方解石) ϕ(白云石) ϕ(黏土) 孔隙度
平均绝对
误差/%		 1.41 0.91 0.68 0.51 0.55 0.56
平均相对
误差/%		 3.08 2.32 9.81 6.09 7.87 11.42

Fig. 7

Workflow of BWO-based optimized logging interpretation"

Table 2

Logging response characteristic values of mineral framework components and pore fluid of the tight glutenite reservoir of Qingshuihe Formation, southern margin of Junggar Basin"

储层组分 GR/API DEN/(g·cm-3) AC/(μs·m-1) CNL/%
石英 12.0 2.65 182 -2
长石 56.8 2.55 200 -3
方解石 10.0 2.71 155 0
白云石 15.0 2.88 142 2
黏土 260.0 2.50 328 36
孔隙 0 1.00 620 100

Fig. 8

Logging interpretation results based on BWO for the tight glutenite reservoir in Qingshuihe Formation of well G1, southern margin of Junggar Basin"

Table 3

Absolute error of BWO and conventional optimization methods of the tight glutenite reservoir in Qingshuihe Formation of well G1, southern margin of Junggar Basin"

最优化方法 绝对误差/%
ϕ(石英) ϕ(长石) ϕ(白云石) ϕ(方解石) ϕ(黏土) 孔隙度
BWO
最优化		 2.31 2.94 0.18 1.18 0.72 0.26
常规
最优化		 5.54 6.12 1.98 3.29 4.83 1.13

Fig. 9

Logging interpretation results of BWO for the tight glutenite reservoir in Cretaceous Qingshuihe Formation of well G2, southern margin of Junggar Basin"

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