Research on the Method of Evaluating the Pore Throat Structure of Rock Microscopically Based on the 3D Pore Network Model of Digital Core
Abstract - 166
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Keywords

Pore microstructure
Pore network model
Petroleum engineering
Oil-water two-phase flow
Low permeability fractured reservoir parameters Digital core

How to Cite

1.
Yan G, Yan W, Yuan Y, Gong X, Tang Z, Xueyuan B. Research on the Method of Evaluating the Pore Throat Structure of Rock Microscopically Based on the 3D Pore Network Model of Digital Core. Int. J. Petrol. Technol. [Internet]. 2022 Dec. 5 [cited 2024 May 3];9:44-53. Available from: https://www.avantipublishers.com/index.php/ijpt/article/view/1256

Abstract

In order to solve the problems of time-consuming, poor repeatability and inability to directly reflect the pore structure of the core by traditional experimental methods to obtain the reservoir parameters, a method was proposed to study the pore structure of inner core using digital core and pore network model. Firstly, the core CT scan image is processed by filtering and denoising, threshold segmentation and pore-throat network skeleton extraction. Then, the digital core and pore network model are constructed by digital image technology and maximum sphere algorithm, and the core physical parameters are statistically analyzed. Finally, a digital core pore network model is used to simulate oil-water two-phase flow. The results show that the digital core pore network model can better reflect the real core pore space characteristics and accurately reflect the pore throat distribution and morphology characteristics. Through practical application, the 3D pore network model of a digital core can accurately reflect the core's microporosity and throat structure and fully understand the mechanism of fluid flow in porous media, which has high application value. In addition, the method can be repeated many times, which is time-consuming and controllable and makes up for the limitations of conventional physical experiments.

https://doi.org/10.54653/2409-787X.2022.09.6
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Copyright (c) 2022 Ganggang Yan, Wende Yan, Yingzhong Yuan, Xiujun Gong, Ziqi Tang, Bai Xueyuan

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