bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quantifying Non-API Proppant Transport and Fracture Permeability as a Function of Solids Loading and Particle Shape
Authors: Leonardi C. R. , Laniewski-Wollk L. , Di Vaira N. J. 
Published: August 2024

ABSTRACT:
The use of non-API proppant in hydraulic fracturing has the potential to significantly reduce the cost of hydraulic fracturing operations. However, the influence of particle angularity on proppant transport in rough fractures is not well understood. This work utilises direct numerical simulation (DNS) to quantify changes in fracture permeability as a function of proppant aspect ratio, solid volume fraction, and fracture width. High-fidelity simulations of proppant transport through realistically-textured fractures were conducted using an established numerical framework based on the lattice Boltzmann method and discrete element methods. Particle angularity was captured via clumps of overlapping spheres and the fracture surfaces were described by a power spectral density. The results show that fracture permeability, which is a proxy for injection pressure, smoothly decreases with increasing proppant concentration for all proppant and fracture characterisations. No distinct screen-out was observed, irrespective of particle shape, which contradicts the prevailing assumption that screen-out instantaneously occurs at some threshold of proppant concentration and fracture width. Interestingly, the change in fracture permeability with particle angularity was found to be non-monotonic (decreasing, then increasing, and then decreasing again). It is hypothesized that increases in permeability are a result of the preferential alignment of particles with the flow streamlines. This requires further investigation, along with the analysis of more complex clump shapes such as triangles and tetrahedra. The developed permeability-concentration curves clearly show the influence of particle angularity on injection pressure and can be used to help inform operational decision making when non-API proppant is proposed in reservoir stimulation.

1 INTRODUCTION
The American Petroleum Institute (API) defines criteria for the classification and quality control testing of sand used in hydraulic fracturing. These metrics include sieve analysis for size distribution, sphericity and roundness (minimum &gt; 0.6), acid solubility, turbidity, and crush resistance. The imperative to reduce well completion costs has led to the exploration and deployment of lower-cost products which do not meet one or more of the API criteria. In some limited scenarios, the properties of non-API proppant are deliberately sought (e.g. the use of angular, non-spherical particles to increase pack stability in the fracture due to locking, thereby reducing flow-back to the well). An important consideration associated with the use of non-API proppant is the effect on stimulation efficacy and estimated ultimate recovery (EUR).
Simulating Cyclic Hydraulic Injection-Induced Fatigue with an Improved Discrete Element Method Model
Authors: Xia Chang , Zhao Qi 
Published: August 2024

ABSTRACT:
Cyclic hydraulic fracturing (CHF) is currently used for subsurface energy extraction. However, a numerical model that can reproduce the hydraulic fatigue damage is not yet available. In this study, we have developed a fully coupled hydro-mechanical damage model using the Discrete Element Method (DEM). This model incorporates a novel time-dependent failure model to simulate the hydraulic fatigue response. Additionally, we employed the Grain-Based Model (GBM) to simulate heterogeneous incipient cracks, which permit fluid flow after breakage. We numerically calculated the hydraulic injection induced fatigue under varying levels of fluid pressure. These calculations have been validated by laboratory results, demonstrating a reasonable consistency in breakdown pressures. We have thoroughly investigated the effects of CHF on fracture network propagation, providing potential guidance for practical subsurface energy exploitation.

1. INTRODUCTION
Hydraulic stimulation has been widely employed to create a permeable reservoir for subsurface energy extraction since the 1940s (Lecampion et al. 2018; Zimmermann et al. 2019). This process involves injecting pressurized fluids into reservoirs, leading to the formation of complex fracture networks composed of newly developed fractures and reactivated existing ones (Li et al. 2022). However, this stimulation treatment can trigger seismic events, potentially causing earthquakes and leading to public disapproval (Grigoli et al. 2017).
Breakdown pressure, a crucial parameter in hydraulic stimulation, is influenced by rock properties, field stress, and fluid pressure (Xi et al. 2021). The breakdown pressure is generally high due to large field stress and fracture toughness. Consequently, the large pressures and injection fluid volumes have resulted in significant safety concerns (Ellsworth 2013). The goal of stimulation is to devise an advanced injection scheme that can control hydraulic fracturing propagation while simultaneously reducing unwanted seismic events (Majer et al. 2007). In this regard, numerous efforts have been made to develop effective stimulation strategies. Cyclic Hydraulic Fracturing (CHF) is one such strategy aimed at optimizing the development of fracture networks while minimizing environmental impact (Hofmann et al. 2018; Yoon et al. 2015; Zang et al. 2013). In contrast to conventional hydraulic fracturing, which adopts continuous injection, CHF employs periodic high- and low-injection pressures (Zhuang et al. 2019). The fluid-rock interaction within the incipient fracture tips can cause hydraulic fatigue, thus making it possible to adopt a lower breakdown pressure to reduce seismic risks (Rao and Ramana 1992; Zhuang et al. 2019). In addition, the permeability of rock is enhanced during CHF compared to conventional hydraulic fracturing (Zimmermann et al. 2019).
Measurement of Crack Tip Opening Displacement and Strain Fields Using Global Digital Image Correlation (DIC)
Authors: Bhandari Tushar , Deb Debasis 
Published: August 2024

ABSTRACT:
The assessment of fracture properties such as crack tip opening displacement (CTOD), plastic zone size, and crack development is essential for understanding the behavior of cracks and fractures in geological materials. Crack displacement requires full-field strain measurement as the strain field develops in front of the propagating crack. The point-based strain measurement devices, such as strain gauge and extensometers, fails to capture crack growth. This study proposes a Finite Element based Digital Image Correlation (FE-DIC) method for measuring fracturing process especially, crack tip displacement and associated strain localization. The paper outlines the FE-DIC algorithm and its validation with numerical images and laboratory testing. The numerical images are created using Irwin's near-crack tip displacement approximation function around a center crack in an infinite plate under equibixial tension (Irwin, 1957). In the laboratory, the Mode I three-point bending fracture test is performed on a cuboidal slab of sandstone and basalt rock with a center notch. The results show that the FE-DIC method can capture the non-linear displacement field as the crack propagates and also estimate plastic zone around the crack. The findings of this study provide evidence supporting the efficacy of the global FE-DIC method in visualizing strains and fracture propagation.

1 INTRODUCTION
The study of the rock fracturing process is crucial for designing various geotechnical projects such as mines, dams, reservoir, underground nuclear waste disposal, and tunnels (Guo et al., 2023; Xing et al., 2022). Most rocks exhibit strain-softening to brittle behavior and fail without any prior indication. To understand the failure mechanism of rocks due to fracture propagation, the insight of full field deformation under various loading conditions is a necessity. Critical challenges in characterizing the crack-induced rock failure includes locating the crack, estimating its propagation path and identifying the strain localization zone in the crack tip where the stress-strain relationship is non-linear, which acts as the precursor of the macroscopic crack extension known as Fracture Process Zone (FPZ) (Qiao et al., 2023). These challenges are more prominent while dealing with brittle materials like rock, which fails at low strain and thus demands a robust fullfield deformation measurement method.
Incorporating Roughness Degradation Within the Critical State Framework: Modeling the Shear Behavior of Rock Joints
Authors: Matsuoka Yuki , Kikumoto Mamoru , Ogata Sho , Kishida Kiyoshi 
Published: August 2024

ABSTRACT:
Rock masses are characterized by numerous structural discontinuities, such as joints and faults, which exert a significant influence on their deformation responses. Therefore, it is important to develop a constitutive model that can accurately anticipate the mechanical response of rock joints. A previous study proposed an elastoplastic constitutive model based on the critical state framework originally developed in soil mechanics. The fundamental assumption of this model is that a rock joint reaches a critical state, where the shear stress and aperture is uniquely determined relative to the applied normal stress, after a large shear displacement. This model accounts for the joint matching by evaluating the difference in joint aperture between the current and the critical state. However, its applicability to rock joints remains incomplete, particularly in accommodating the influence of roughness degradation. Roughness degradation on joint surfaces can lead to a reduction in the asperity angle, resulting in a decrease in aperture at the critical state and a dilatancy response. In this study, we extend the aforementioned model by introducing a state parameter to account for the changes in critical state aperture. The proposed model effectively captures alterations in the shear response associated with the roughness degradation, providing a more comprehensive understanding of the mechanical behavior of rock joints.

1. INTRODUCTION
The precise anticipation of rock mass behavior is critical in designing and maintaining rock structures such as tunnels, dam foundations, geological repositories for radioactive waste, and energy storage facilities. Within the rock mass, numerous discontinuities, such as faults and joints, characterized by reduced stiffness and strength compared to the rock materials, exert a significant influence on the overall rock mass behavior. In addition, alterations in stress conditions within the rock mass resulting from subsurface activities can induce slippage of these discontinuities, precipitating the failure or collapse of the entire rock mass. Therefore, comprehending and managing the slip behavior of discontinuities, particularly those surrounding underground structures, represents one of the critical challenges in rock engineering.
Although various studies have explored slip/shear behavior, the surface roughness (Barton, 1973) and interlocking (Zhao, 1997a) of rock joints are important factors influencing shear behavior under applied stress conditions common in rock engineering. Numerous numerical methodologies have been proposed to forecast the behavior of discontinuities in rock. Nevertheless, enhancing constitutive models to incorporate geological characteristics of in-situ joints remain imperative.
Dual-Target Predictive Intelligence Model for Predicting D90 Particle Size and Total Concentration of Lost Circulation Materials
Authors: Shang Guanyi , Yang Heng , Feng Yongcun , Li Xiaorong 
Published: August 2024

ABSTRACT:
Lost circulation events occur frequently during the drilling process. Due to their sudden and difficult to predict nature, they are often difficult to control in the field, resulting in low success rates and increased costs. Therefore, accurate formulation of lost circulation materials (LCMs) is essential for effective lost circulation management. However, the current lack of clear guidelines for LCM formulation in the field introduces uncertainty and subjectivity. Traditional machine learning methods struggle with the diversity of LCM types and combinations, making direct formulation recommendations difficult. In particular, the D90 size of the primary bridging particles and the total concentration of LCMs are essential for successful control of lost circulation. This study presents a dual-target deep learning model designed to predict these critical parameters, thereby aiding in the precise formulation and optimization of LCMs. By selecting eleven key features as model inputs, the model can understand complex relationships within the data by exploiting connections between layers and weighting adjustments. Test results show high accuracy and robustness, with R2 values of 0.91 for D90 particle size and 0.83 for material concentration, providing valuable guidance for LCM development and optimization.

1. INTRODUCTION
Lost circulation, a frequent and unpredictable challenge in drilling, significantly impacts oil industry operations. This phenomenon, where drilling fluids are lost into formations through well walls, leads to various drilling issues like well control problems, hole instability, and production inefficiencies, ultimately resulting in increased nonproductive time and costs (Feng & Gray, 2017). The complexity and unpredictability of geological conditions exacerbate these challenges, highlighting the need for effective management strategies.
Lost circulation materials (LCMs) are the basis for successful loss control (Zhang et al.,2016). The effectiveness of the LCMs depends on its suitability for the loss conditions and drilling fluid type (Zhou et al.,2022). The characteristics of lost circulation determine the key performance of LCMs (Xu et al., 2022). Central to their function is the adjustment of particle size within the drilling mud to effectively seal pores and fractures addressable by mud alone (White, 1956). Optimal particle size and distribution are vital; overly small particles fail to bridge gaps, while excessively large ones cannot penetrate cracks, underscoring the importance of precise selection for efficient and effective sealing.
Experimental Study on CO2 Fracturing of Continental Shale with Dense Laminas
Authors: Zhang Xiaohuan , Zhang Shicheng , Zou Yushi , Ma Xinfang , Xiong Dong , Liu Li , Yang Peng , Zhu Danyang 
Published: August 2024

ABSTRACT:
Using CO2 to increase shale oil production is a practical requirement to ensure energy security and reduce carbon emissions. Therefore, studying the fracture propagation mechanics of CO2 fracturing is of great significance. This article applies a triaxial fracturing simulation system combined with a CO2 control system to perform supercritical CO2 (SC-CO2) fracturing, CO2 aqueous solution (CO2 aqs) fracturing, slick water fracturing, and gel fracturing on continental shale. The results indicate that CO2 fracturing has the effect of reducing breakdown pressure, and the breakdown pressure of supercritical CO2 fracturing and CO2 aqs pre-immersion fracturing is lower than that of slick water fracturing. The artificial fractures induced by low-viscosity slick water fracturing in shale with dense laminas are easily inhibited by the laminas, and it is difficult to propagate in the direction of fracture height. The ultra-low viscosity and strong diffusivity of SC-CO2 lead to multiple laminas and micro-fractures being activated, and the main fracture is not obvious. The main fracture width of CO2 aqs pre-immersion fracturing is relatively large, the fracture propagation path is tortuous, and multiple laminas are activated. The complexity of the fracture induced by CO2 aqs solution is 75% higher than that induced by slick water. The effect of CO2-water-rock interaction on fracture propagation cannot be ignored. In addition, there is a significant positive correlation between the complexity coefficient of fractures and acoustic emission shear activity ratio.

1. INTRODUCTION
The success of the United States in the efficient development of marine shale oil has sparked a wave of exploration and development of unconventional oil and gas resources worldwide (Zou et al. 2020). Under the tectonic background of the foreland basin, the Jurassic in the Sichuan Basin of China is located in a sedimentary environment of deep to semi-deep lakes, forming a large and stable set of dark shale interbedded with carbonate or siltstone formations, laying an important material foundation for the formation and enrichment of shale oil (He et al. 2022). However, the strong heterogeneity, complex lithology, and dense laminas of continental shale pose challenges for fracturing development (Guo et. 2023). To improve the effect of reservoir stimulation, CO2 fracturing technology was explored and applied in the oilfield (Li et al. 2020). CO2 as a fracturing fluid can effectively reduce formation damage and increase formation pressure, and help reduce greenhouse gas emissions (Li et al. 2022). Therefore, studying the fracture propagation mechanics of CO2 fracturing is of great significance.
Reservoir Fine Evaluation of Horizontal Well Multi-Stage Fracturing Based on Unsupervised Cluster Machine Learning
Authors: Wang W. C. , Ma X. F. , Zou Y. S. , Zhang S. C. , Liu L. , Yang P. , Zhao Z. W. , Zheng A. , Wang X. , Yang L. F. 
Published: August 2024

ABSTRACT:
The accuracy of comprehensive evaluation is low, the effect of multi-stage and multi-cluster design is poor, and it is difficult to ensure the maximum stimulation efficiency. The comprehensive quality of reservoirs is quantitatively evaluated by considering the physical properties and fracability of reservoirs based on logging data. This evaluation integrated reservoir quality (RQ) and completion quality (CQ) from a geology-engineering perspective, a model is established using the entropy weight method (EWM) and the analytic hierarchy process (AHP). Then, the unsupervised Gaussian Mixture Model (GMM) clustering is applied to categorize the composite quality index (CQI), resulting in the development of a novel evaluation model for multi-cluster fractured. The evaluation and clustering are conducted using Jimusaer shale oil well A in Xinjiang and Ordos Basin well B in Qingcheng as case studies. Upon comparing the results with the actual oil production, it is discovered that: the comprehensive quality can be quantitatively characterized by the evaluation model; the GMM can accurately identify good fracability zones, and the coincidence rate with the results of the oil production is as high as 83.3%, which confirms the accuracy of the proposed method, provides a good technical foundation for optimizing the location of multi-stages and multi-clusters.

1. INTRODUCTION
Under the current background of unconventional oil and gas exploitation with low quality aiming at cost reduction and efficiency improvement, an important step to carry out multi-stage and cluster stimulation for low and ultralow permeability reservoirs is to determine good reservoir quality (RQ) and completion quality (CQ) (Hu et al., 2018). Usually, there are problems such as parameter diversification and inaccurate quantification in quality evaluation (Lei et al., 2019; Lei et al., 2022), and unreasonable position of multi-stage and perforation cluster, resulting in low production after reservoir stimulation (Miller et al., 2011; Wigger et al., 2014).
A Study of the Collapse of Fractured Sandstone Strata Characterized by High In-Situ Stress Differences in Deep Formations
Authors: Xu Zehao , Zhang Wen , Liu Xiangjun , Liang Lixi , Jing Yadong 
Published: August 2024

ABSTRACT:
Under the condition of high in-situ stress differences, the issue of wellbore instability in fractured sandstone formations is prominent. Through rock mechanics experiments combined with the theory of weak planes, a quantitative study on the mechanical characteristics of fractured sandstone and the collapsing area around the wellbore was conducted. The results indicate that the matrix strength of tight sandstone is high, but the presence of fractures increases the likelihood of failure in fractured sandstone, resulting in a reduction of its overall strength to 14% of the matrix strength. Under vertical well conditions, compared to uniform horizontal in-situ stress conditions, the risk of fracture instability caused by high horizontal stress differences increases. However, when the fracture orientation aligns with the direction of maximum principal stress, the risk of fracture instability is the lowest. When formations develop fractures with low to moderate dip angles, drilling in the direction of maximum horizontal stress can lead to a larger collapse area for wells with moderate inclinations; if drilling in the direction of minimum principal stress, the maximum collapse area decreases as the fracture angle increases. The study results have certain guidance significance for the safe and efficient development of deep oil and gas resources.

1. INTRODUCTION
The deepest oil and gas wells today have reached depths of up to 9000 meters. The successful exploitation of ultra-deep oil and gas resources critically depends on advancements in petroleum engineering and rock mechanics (Xie et al., 2021). However, the geological conditions of deep formations are complex, and the three high characteristics (high temperature, high pressure, and high H2S content) of formations lead to prominent wellbore instability issues (Han et al., 2021). For instance, due to the influence of natural fractures, the safe drilling density window is narrow, and situations where wellbore collapse and leakage coexist may occur. Therefore, wellbore instability in fractured sandstone formations under high in-situ stress differences is one of the key scientific issues that deep drilling engineering needs to consider.
Pore Pressure Prediction in Deep Complex Formations Based on Well-Seismic Combination
Authors: Yang Zixuan , Ye Chenxi , Wang Qian , Zhai Wenbao , Tan Peng , Chen Zhaowei 
Published: August 2024

ABSTRACT:
With the development of oil and gas drilling technology, oil and gas exploration and development have moved towards deep to ultra-deep layers. Due to its deep burial depth, deep formations face various challenges such as high temperature, high pressure, and high stress. The prediction of formation pore pressure is a core factor of drilling design optimization and risk prevention. In order to improve the prediction accuracy on the basis of existing pre-drilling formation pore pressure prediction methods, the logging data and actual drilling data of the drilled wells were combined with the seismic data. In this paper, a set of high accuracy pore pressure prediction method based on well-seismic combination are formed by using the interval-controlled interval velocity modeling method and the well-controlled interval velocity correction method. The method is applied to a deep well in Tarim Basin. This well was designed to exceed a depth of 8,000 meters. The predicted pore pressure coefficient of the well is between 1.04 and 1.22 g/cm3. The measured pore pressure coefficient after drilling was between 1.07 and 1.22 g/cm3. Actual analysis has demonstrated the accuracy and reliability of pore pressure prediction, providing support for pre-drilling pressure forecasts.

1. INTRODUCTION
In recent years, with the acceleration of China's exploration and development of deep oil and gas resources, the demand for ultra-deep well drilling technology has become increasingly urgent, and higher requirements have been put forward for ultra-deep well drilling technology. However, the engineering geological conditions of ultra-deep formations are extremely complex, and the design of wellbore structures under multiple pressure systems is difficult, which also poses great challenges to efficient and safe drilling. Therefore, for ultra-deep and complex formations, solving the problem of accurate prediction of formation pore pressure under complex geological conditions has great practical significance for oil and gas drilling. At the same time, it also provides strong technical support for the exploration and development of ultra-deep oil and gas resources.