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Enregistrement W4401480054 · doi:10.56952/arma-2024-1023

Study on Fracture Initiation and Expansion of Coal Rock by CO2 Foam Fracturing

2024· article· en· W4401480054 sur OpenAlexaboutno aff
Yonggang Xie, Xuhao Fan, Changjing Zhou, Haizhu Wang, Zelong Mao, Bin Wang, Fengxiang Mao, Sergei Stanchits, Аlexey Cheremisin

Notice bibliographique

Revuenon disponible
Typearticle
Langueen
DomaineEngineering
ThématiqueGrouting, Rheology, and Soil Mechanics
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCoalFracture (geology)Petroleum engineeringGeologyGeotechnical engineeringEngineeringWaste management

Résumé

récupéré en direct d'OpenAlex

ABSTRACT: To investigate the crack initiation and propagation mechanism of CO2 foam fracturing coal rock. In this study, experiments were conducted on CO2 foam fracturing of coal rock using custom-designed indoor quasi-triaxial and true-triaxial fracturing equipment. The resulting fracture parameters (fracture area, width, fractal dimension) were quantitatively analyzed through CT scanning and topography scanning. The research investigated the influence of varying foam quality, temperature, and flow rate on the initiation and propagation of fractures in coal rock. The results indicate that with a higher CO2 foam mass fraction, the fractures exhibit a higher level of complexity and lower fracturing pressure. Specifically, the initiation pressure at 70% foam mass is 7.1% lower than that at 40% foam mass, As the quality of CO2 foam improves, the post-fracturing fracture area and fractal dimension increase, indicating a rougher fracture surface and enhanced conductivity. As the temperature rises, the foaming volume of the foam decreases, leading to a shorter half-life, reduced interaction with coal rock, and slightly higher initiation pressure; CO2 foam fracturing can maintain larger fracture widths and has a greater fractal dimension compared to conventional fracturing fluids. This study reveals the fracture initiation and propagation mechanism of coal rock by CO2 foam fracturing. 1. INTRODUCTION The rapid development of China's economy and society drives a surge in oil and gas consumption, while conventional resources dwindle. This reliance on foreign oil and gas constrains China's economic and social progress. Coalbed methane products mainly comprise methane, an associated gas generated during coal production. Coalbed methane products primarily consist of methane, an associated gas formed during coal production. Comparable to natural gas, this clean energy source boasts high heat levels (Zonghu, 2006). The energy generated per 1000m3 of coalbed methane is equal to the energy generated by 1 ton of fuel oil and 1.25 ton of standard coal. With a calorific value of up to 33.44MJ/m3, CBM matches the quality of high-grade coal (Bozhang, 2005). Aligned with the "double carbon" objective, the exploration and exploitation of coalbed methane embody key values of "economy, safety, and environmental protection", contributing to a reduction in greenhouse gas emissions. Positioned as a pivotal facet and growth trajectory within the energy sector, coalbed methane holds immense promise for expansion and implementation, poised to emerge as a vital avenue addressing societal energy needs in the years ahead (Lei, 2018). China possesses abundant coalbed methane resources, ranking second globally after Russia and Canada (Qingbo & Wenguang, 2008; CHO and KIM, 2013), surpassing the United States and Australia by a significant margin. Despite this abundance, China has maintained relatively low production of coalbed methane. The inherent characteristics of Chinese coalbed methane reservoirs, characterized by low pressure, low saturation, low permeability, and high adsorption, constitute the primary bottleneck hindering the accelerated development of coalbed methane (Yali et al., 2021). Based on statistical data, China's geological coalbed methane resources stand at 29.8×10^12 m3, with technically recoverable resources estimated at 11.2×10^12 m3. The majority of these resources are situated within the three main regions of Northeast China, North China, and Northwest China. The top four regions with the most significant deposits include Ordos Basin, Qinshui Basin, Eastern Yunnan and Western Guizhou, and Junggar Basin, accounting for 24.4%, 13.4%, 11.6%, and 10.4% of total reserves, respectively (Xiaozhi et al., 2022). Currently, the development of coalbed methane faces a number of challenges, including the unclear migration mechanism and stimulation process for horizontal wells. The conventional method of hydraulic fracturing is often utilized, but it yields limited fractures, higher initial fracturing pressure, and simplistic fracture networks. Further, this approach wastes significant amounts of water resources and can even damage surface environments (Shaokai & Deli, 2019; Johnson & Johnson, 2012; Bostrom et al., 2014; Shibing et al., 2014; Haizhu et al., 2015; Zhonghou et al., 2010; Xiaojiang et al., 2017; Zhonghou et al., 2011). In response to diverse geological and technological demands, a range of CO2 fracturing technologies have surfaced, including CO2 foam fracturing, pre-CO2 energy-increasing fracturing, quasidry CO2 fracturing, dry CO2 fracturing, and various other variants. Notably, CO2 foam fracturing involves the injection of liquid CO2 into the well using a dedicated CO2 pump truck. This liquid CO2 is combined with gel fluid during the process and utilized for sand fracturing purposes (Changlin et al., 2016; Ting et al., 2016; Jidong et al., 2004). Due to the distinctive structure of the foam system, it boasts exceptional capabilities in minimizing sand sedimentation rates, even under high sand ratios. This unique structure enables excellent suspension and efficient transport of sand particles within the system (Shaohua, 2014; Siwei et al., 2024; Bo et al., 2023). Based on field data, the CO2 foam fracturing process has demonstrated significant advantages over conventional water-based fracturing methods. It enables complete self-flowing drainage post-fracturing, resulting in a high flowback rate and shorter drainage time. Moreover, this process causes minimal damage to the formation and fractures, while yielding remarkable fracturing outcomes (Hui & Xuxing, 2018; Xuxing et al., 2019; Zhandong, 2010; Honglian et al., 2022; Junping et al., 2019). The fracture characteristics observed in laboratory-scale experiments can offer insights into field construction scenarios. However, the in-depth exploration of the fracture initiation mechanism in CO2 foam fracturing of coal rock remains relatively limited. This study aims to address this gap by conducting CO2 foam fracturing experiments on coal rock using self-designed indoor quasi-triaxial and true-triaxial fracturing experimental equipment. The integration of CT scanning and morphology scanning allows for the quantitative analysis of fracture parameters, such as fractal dimension, fracture width, and fracture area. Furthermore, the study investigates the influence of various factors, including foam quality, temperature, stress differential, and flow rate, on the initiation and propagation patterns of cracks in coal rock. The experimental findings uncover the laws governing crack initiation and propagation in coal rock fractured by CO2 foam, offering an experimental foundation for the application of CO2 foam fracturing in coalbed methane development and contributing to the advancement of CO2 foam fracturing technology.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,002
Score d'incertitude au seuil0,004

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,011
Tête enseignante GPT0,238
Écart entre enseignants0,227 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2024
Routes d'admission1
Résumé présentoui

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