Integrated Physical and Digital Chalk Relative Permeability Evaluation: A Case Study

被引:0
|
作者
Grader, Abraham [1 ]
Birkedal, Knut Arne [2 ]
Engelman, Robert [1 ]
Birkeland, Kristoffer [2 ]
Aarseth, Nils -Andre [2 ]
机构
[1] Halliburton, Tananger, Norway
[2] AkerBP, Lysaker, Norway
来源
PETROPHYSICS | 2024年 / 65卷 / 02期
关键词
D O I
10.30632/PJV65N2-2024a1
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
The Valhall chalk field has produced more than 1 billion barrels of oil equivalents over the last 40 years, primarily from the homogeneous Tor Formation. The underlying Hod Formation is more heterogeneous and is less maturely developed. The extent of heterogeneity poses a challenge in the evaluation of multiphase fluid flow properties. The objective of the work was to use digital core analysis to generate early relative permeability data to leverage and compare with conventional physical steady-state relative permeability data. Accurate digital and physical description of capillary pressure and relative permeability in the high -porosity chalk is complicated by both low permeabilities and heterogeneity. The main challenge with chalk is that flow occurs in a nano -environment. Physically, the nanoenvironment translates to low permeability, difficult rock preparation, and extensive experimental time, especially for steady-state flow experiments. Representative threedimensional (3D) digital rocks were generated using a combination of X-ray computed tomography (CT) and focused ion beam -scanning electron microscopy (FIBSEM) methods. The digital rocks were used to simulate two-phase flow and generate relative permeabilities and sensitivity to wettability. Physical steady-state and digital relative permeabilities on several core plugs and subsets are compared in this study, which discusses the advantages of performing both as part of the formation evaluation process. The physical and digital results compare reasonably well. The physical results provide a relative permeability anchor, and the digital results provide the leverage of early results, parametric sensitivities, and quality assurance. Hence, integration between digital and physical core analysis yields a robust understanding and input for uncertainty modeling.
引用
收藏
页码:149 / 157
页数:9
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