WeChat Mini Program
Old Version Features

Experimental Investigation of a C-S-H Nanocrystalline Nucleus Modified with PCE Dispersant on the Early-Age Mechanical Behavior of Oil Well Cement Paste

MATERIALS(2025)

CNPC Engn Technol R&D Co Ltd

Cited 0|Views6
Abstract
For the exploration and development of oil and gas reservoirs in shallow, cold regions and deep oceans, oil well cement (OWC) pastes face the challenge of slow cement hydration reactions and the low early-strength development of cement stone at low temperatures, which can cause the risk of fluid channeling and the defective isolation of the sealing section during the cementing construction process. To address the above challenges, a nanoscale hydrated calcium silicate (C-S-H) crystal nucleus, DRA-1L, was synthesized. Its application performance and action mechanism were studied. The structural characterization of DRA-1L revealed that its crystal structure resembles that of amorphous C-S-H gel, with a size distribution ranging from 20 to 200 nm. The addition of DRA-1L significantly shortens the transition time of static gel strength, preventing the channeling of OWC paste and promoting the strength development of cement stone at low temperatures. Moreover, the mechanism by which DRA-1L enhances the early strength of cement stone was studied. Results indicated that the nanoscale DRA-1L with nucleation effect reduces the barrier to C-S-H gel formation and accelerates cement hydration, which leads to the increased compactness and early strength of cement stone.
More
Translated text
Key words
nanocrystalline nucleus,early strength,early hydration,hydrated calcium silicate,OWC paste
上传PDF
Bibtex
收藏
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined