Abstract
The existing models for fracture toughness characterization based on nanoindentations that account for the fracture length are limited to simple (ideal) geometries that are absent in shales. The present study proposes two conceptual models to estimate the fracture length created by nanoindentations in shales. It also presents a workflow to apply the conceptual models and uses machine learning, enabling a systematic and automated analysis. The conceptual models assume that the induced fracture is in the first mode to determine the fracture toughness. In this study, fracture toughness is also determined by the energy method that relates the load-displacement hysteresis to the fracture toughness without restricting the fracture mode. The present study sheds light on the complexities of characterizing fracture toughness using nanoindentations and has applications in the petroleum industry. The conceptual models are appealing for formation characterization using small pieces, such as drill cuttings, when large samples (~2.5 cm) required for conventional tests are unavailable. The conceptual models have applications in estimating fracture toughness when the induced fracture patterns become more complex.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
