Digital characterization methods of microscopic structure of cuttings in deep strata

ABSTRACT: Timely and accurate acquisition of rock mechanics parameters is of paramount importance for safe and efficient drilling operations. The real-time evaluation of complex wells during drilling typically requires precise rock mechanics parameters as a foundation. Traditional methods for obtaining these parameters primarily depend on laboratory mechanical experiments conducted on core samples, leading to inherent delays. Consequently, this study introduces a method for evaluating rock mechanics parameters based on rock cuttings. This paper utilizes experimental techniques such as scanning electron microscopy (SEM) and nanoindentation to observe and characterize the microstructure and mineral mechanical parameters of rock cuttings from the deep strata of the Tarim Basin. A comprehensive processing and fitting algorithm for SEM images is proposed, facilitating the digital reconstruction of the microstructure of rock cuttings and the establishment of a digital geometric model. By integrating the geometric model with mineral mechanical parameters obtained from nanoindentation experiments, the macro statistical average mechanical parameters of the rock cuttings are derived using finite element numerical simulation methods. The mechanical parameter evaluation method based on drilling cuttings proposed in this paper overcomes the dependence of conventional rock mechanics laboratory experiments on core samples. This advancement offers a novel approach for obtaining rock mechanical parameters from deep formations and enhances our understanding of the deformation and failure mechanisms of rocks under diverse geological conditions.

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Publication Details

Published
2025-06-08
DOI
https://doi.org/10.56952/arma-2025-0740
Primary Topic
Engineering Technology and Methodologies
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article
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Digital characterization methods of microscopic structure of cuttings in deep strata

Zhenyu J. Zhang, Jiaqi Luo, Yang Xia
Engineering Technology and Methodologies
article

Digital characterization methods of microscopic structure of cuttings in deep strata

Zhenyu J. Zhang, Jiaqi Luo, Yang Xia
article en

Abstract

ABSTRACT: Timely and accurate acquisition of rock mechanics parameters is of paramount importance for safe and efficient drilling operations. The real-time evaluation of complex wells during drilling typically requires precise rock mechanics parameters as a foundation. Traditional methods for obtaining these parameters primarily depend on laboratory mechanical experiments conducted on core samples, leading to inherent delays. Consequently, this study introduces a method for evaluating rock mechanics parameters based on rock cuttings. This paper utilizes experimental techniques such as scanning electron microscopy (SEM) and nanoindentation to observe and characterize the microstructure and mineral mechanical parameters of rock cuttings from the deep strata of the Tarim Basin. A comprehensive processing and fitting algorithm for SEM images is proposed, facilitating the digital reconstruction of the microstructure of rock cuttings and the establishment of a digital geometric model. By integrating the geometric model with mineral mechanical parameters obtained from nanoindentation experiments, the macro statistical average mechanical parameters of the rock cuttings are derived using finite element numerical simulation methods. The mechanical parameter evaluation method based on drilling cuttings proposed in this paper overcomes the dependence of conventional rock mechanics laboratory experiments on core samples. This advancement offers a novel approach for obtaining rock mechanical parameters from deep formations and enhances our understanding of the deformation and failure mechanisms of rocks under diverse geological conditions.

China University of Petroleum, Beijing (CN)
Openalex Percentile: Top 72%
Engineering Technology and Methodologies
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Digital characterization methods of microscopic structure of cuttings in deep strata — Zhenyu J. Zhang, Jiaqi Luo, et al. · (2025) | TGRS Research Map | TGRS