Experimental study on the mechanical controlling factors of fracture plugging strength for lost circulation control in shale gas reservoir

The geological conditions of shale reservoir present several unique challenges. These include the extensive development of multi-scale fractures, frequent losses during horizontal drilling, low success rates in plugging, and a tendency for the fracture plugging zone to experience repeated failures. Extensive analysis suggests that the weakening of the mechanical properties of shale fracture surfaces is the primary factor responsible for reducing the bearing capacity of the fracture plugging zone. To assess the influence of oil-based environments on the degradation of mechanical properties in shale fracture surfaces, rigorous mechanical property tests were conducted on shale samples subsequent to their exposure to various substances, including white oil, lye, and the filtrate of oil-based drilling fluid. The experimental results demonstrate that the average values of the elastic modulus and indwelling hardness of dry shale are 24.30 GPa and 0.64 GPa, respectively. Upon immersion in white oil, these values decrease to 22.42 GPa and 0.63 GPa, respectively. Additionally, the depth loss rates of dry shale and white oil-soaked shale are determined to be 57.12% and 61.96%, respectively, indicating an increased degree of fracturing on the shale surface. White oil, lye, and the filtrate of oil-based drilling fluid have demonstrated their capacity to reduce the friction coefficient of the shale surface. The average friction coefficients measured for white oil, lye, and oil-based drilling fluid are 0.80, 0.72, and 0.76, respectively, reflecting their individual weakening effects. Furthermore, it should be noted that the contact mode between the plugging materials and the fracture surface can also lead to a reduction in the friction coefficient between them. To enhance the bearing capacity of the plugging zone, a series of plugging experiments were conducted utilizing high-strength materials, high-friction materials, and nanomaterials. The selection of these materials was based on the understanding of the weakened mechanical properties of the fracture surface. The experimental results demonstrate that the reduced mechanical properties of the fracture surface can diminish the pressure-bearing capacity of the plugging zone. However, the implementation of high-strength materials, high-friction materials, and nanomaterials effectively enhances the pressure-bearing capacity of the plugging zone. The research findings offer valuable insights and guidance towards improving the sealing pressure capacity of shale fractures and effectively increasing the success rate of leakage control measures during shale drilling and completion. © 2023 The Author

An investigation on the best-fit models for sugarcane biomass estimation by Linear Mixed-Effect Modelling on Unmanned Aerial Vehicle-Based Multispectral Images: a case study of Australia

Due to the worldwide population growth and the increasing needs for sugar-based products, accurate estimation of sugarcane biomass is critical to the precise monitoring of sugarcane growth. This research aims to find the imperative predictors correspond to the random and fixed effects to improve the accuracy of wet and dry sugarcane biomass estimations by integrating ground data and multi-temporal images from Unmanned Aerial Vehicles (UAVs). The multispectral images and biomass measurements were obtained at different sugarcane growth stages from 12 plots with three nitrogen fertilizer treatments. Individual spectral bands and different combinations of the plots, growth stages, and nitrogen fertilizer treatments were investigated to address the issue of selecting the correct fixed and random effects for the modelling. A model selection strategy was applied to obtain the optimum fixed effects and their proportional contribution. The results showed that utilizing Green, Blue, and Near Infrared spectral bands on models rather than all bands improved model performance for wet and dry biomass estimates. Additionally, the combination of plots and growth stages outperformed all the candidates of random effects. The proposed model outperformed the Multiple Linear Regression (MLR), Generalized Linear Model (GLM), and Generalized Additive Model (GAM) for wet and dry sugarcane biomass, with coefficients of determination (R2) of 0.93 and 0.97, and Root Mean Square Error (RMSE) of 12.78 and 2.57 t/ha, respectively. This study indicates that the proposed model can accurately estimate sugarcane biomasses without relying on nitrogen fertilizers or the saturation/senescence problem of Vegetation Indices (VIs) in mature growth stages

(Methoxo-κO)oxidobis(quinolin-8-olato-κ2 N,O)vanadium(V)

In the title complex, [V(C9H6NO)2(CH3O)O], the central VV atom is coordinated by the O atoms from the oxido and methoxo ligands and the N and O atoms of two bis-chelating quinolin-8-olate ligands, forming a distorted octa­hedral environment. In the crystal structure, weak inter­molecular C—H⋯O hydrogen bonds connect mol­ecules into centrosymmetric dimers which are, in turn, linked by weak C—H⋯π inter­actions into chains along the b axis

Prediction of drilling fluid lost-circulation zone based on deep learning

Lost circulation has become a crucial technical problem that restricts the quality and efficiency improvement of the drilling operation in deep oil and gas wells. The lost-circulation zone prediction has always been a hot and difficult research topic on the prevention and control of lost circulation. This study applied machine learning and statistical methods to deeply mine 105 groups and 29 features of loss data from typical loss block M. After removing 10 sets of noise data, the methods of mean removal, range scaling and normalization were used to pre-treat the 95 sets of the loss data. The multi-factor analysis of variance (ANOVA) and random forest algorithm were adopted to determine the 13 main factors affecting the lost circulation. The three typical deep learning neural network models were improved, the parameters in the models were adjusted, the neural network models with different structures were compared according to the PR curves, and the best model structure was built. The pre-treated loss data in 95 sets with 13 features were divided into the training set and test set by a ratio of 4:1. The model performance was evaluated using F1 score, accuracy, and recall rate. The trained model was successfully applied to the G block with severe leakage. The results show that the capsule network model is better than the BP neural network model and the convolutional neural network model. It stabilizes at 300 training rounds, with a prediction accuracy of 94.73%. The improved model can be applied to lost-circulation control in the field and provide guidance on leakage prevention and plugging operations

Experimental study on fracture plugging effect of irregular-shaped lost circulation materials

Using micro-visualization experimental device for the formation of fracture plugging zone, the plugging behavior of irregular-shaped lost circulation materials (LCMs) with different types and concentrations in fractures was experimentally analyzed. The results show that the sealing time decreases significantly with the increase of material concentration. When the concentration is 20%, the sealing times of materials LCM-1∼LCM-5 are 6s, 7s, 5s, 6s, 4s, respectively. The formation of fracture plugging zone includes two stages, and the main factors affecting the formation of fracture plugging zone are flatness, roundness, convexity and concentrations. Flatness affects the retention stage of LCMs through the matching degree between particle size and fracture width. Convexity and roundness affect the retention stage by increasing the friction coefficient between particles. The high-efficiency retention ability of irregular LCMs is characterized by strong matching to fracture width, and strong friction and sliding resistance between particles. It is recommended that the optimized geometric parameters of high-efficiency retention materials should meet the requirements of “low flatness, low roundness and low convexity” (flatness \u3c0.6, roundness \u3c0.6 and convexity \u3c0.8), which can improve the plugging effect significantly

DASICS: Enhancing Memory Protection with Dynamic Compartmentalization

In the existing software development ecosystem, security issues introduced by third-party code cannot be overlooked. Among these security concerns, memory access vulnerabilities stand out prominently, leading to risks such as the theft or tampering of sensitive data. To address this issue, software-based defense mechanisms have been established at the programming language, compiler, and operating system levels. However, as a trade-off, these mechanisms significantly reduce software execution efficiency. Hardware-software co-design approaches have sought to either construct entirely isolated trusted execution environments or attempt to partition security domains within the same address space. While such approaches enhance efficiency compared to pure software methods, they also encounter challenges related to granularity of protection, performance overhead, and portability. In response to these challenges, we present the DASICS (Dynamic in-Address-Space Isolation by Code Segments) secure processor design, which offers dynamic and flexible security protection across multiple privilege levels, addressing data flow protection, control flow protection, and secure system calls. We have implemented hardware FPGA prototypes and software QEMU simulator prototypes based on DASICS, along with necessary modifications to system software for adaptability. We illustrate the protective mechanisms and effectiveness of DASICS with two practical examples and provide potential real-world use cases where DASICS could be applied.Comment: 16 pages, 6 figure

Improving Robust Fairness via Balance Adversarial Training

Adversarial training (AT) methods are effective against adversarial attacks, yet they introduce severe disparity of accuracy and robustness between different classes, known as the robust fairness problem. Previously proposed Fair Robust Learning (FRL) adaptively reweights different classes to improve fairness. However, the performance of the better-performed classes decreases, leading to a strong performance drop. In this paper, we observed two unfair phenomena during adversarial training: different difficulties in generating adversarial examples from each class (source-class fairness) and disparate target class tendencies when generating adversarial examples (target-class fairness). From the observations, we propose Balance Adversarial Training (BAT) to address the robust fairness problem. Regarding source-class fairness, we adjust the attack strength and difficulties of each class to generate samples near the decision boundary for easier and fairer model learning; considering target-class fairness, by introducing a uniform distribution constraint, we encourage the adversarial example generation process for each class with a fair tendency. Extensive experiments conducted on multiple datasets (CIFAR-10, CIFAR-100, and ImageNette) demonstrate that our method can significantly outperform other baselines in mitigating the robust fairness problem (+5-10\% on the worst class accuracy

Editorial: Lost circulation control during drilling and completion in complex formations

Well drilling is a common method for Earth exploration, underground mineral resource extraction, and geological storage of nuclear waste and carbon dioxide. Drilling fluid circulates in the well during drilling, cooling the drill bit, transporting rock cuttings, preventing wellbore collapse, and balancing formation pressure. Lost circulation occurs when less fluid returns from the wellbore than is pumped into it, resulting in economic losses due to drilling fluid wastage and nonproductive time. Untreated losses can cause well control issues, poor hole cleaning, pack-offs, and stuck pipe, impairing normal drilling. Lost circulation incidents are more likely to occur with the increasing share of difficult wells (deep-water, deviated, horizontal, high pressure, high temperature) in the drilling portfolio. It is one of the most troublesome drilling problems. . .

The role of tidal interactions in the formation of slowly rotating early-type stars in young star clusters

The split main sequences found in the colour-magnitude diagrams of star clusters younger than ~600 Myr are suggested to be caused by the dichotomy of stellar rotation rates of upper main-sequence stars. Tidal interactions have been suggested as a possible explanation of the dichotomy of the stellar rotation rates. This hypothesis proposes that the slow rotation rates of stars along the split main sequences are caused by tidal interactions in binaries. To test this scenario, we measured the variations in the radial velocities of slowly rotating stars along the split main sequence of the young Galactic cluster NGC 2422 (~90 Myr) using spectra obtained at multiple epochs with the Canada-France-Hawai'i Telescope. Our results show that most slowly rotating stars are not radial-velocity variables. Using the theory of dynamical tides, we find that the binary separations necessary to fully or partially synchronise our spectroscopic targets, on time-scales shorter than the cluster age, predict much larger radial velocity variations across multiple-epoch observations, or a much larger radial velocity dispersion at a single epoch, than the observed values. This indicates that tidal interactions are not the dominant mechanism to form slowly rotating stars along the split main sequences. As the observations of the rotation velocity distribution among B- and A-type stars in binaries of larger separations hint at a much stronger effect of braking with age, we discuss the consequences of relaxing the constraints of the dynamical tides theory.Comment: 14 pages, 10 figures, 2 tables, accepted for publication in MNRA

Transmitted drug resistance and transmission clusters among ART-naïve HIV-1-infected individuals from 2019 to 2021 in Nanjing, China

BackgroundTransmitted drug resistance (TDR) is an increasingly prevalent problem worldwide, which will significantly compromise the effectiveness of HIV treatments. However, in Nanjing, China, there is still a dearth of research on the prevalence and transmission of TDR among ART-naïve HIV-1-infected individuals. This study aimed to understand the prevalence and transmission of TDR in Nanjing.MethodsA total of 1,393 participants who were newly diagnosed with HIV-1 and had not received ART between January 2019 and December 2021 were enrolled in this study. HIV-1 pol gene sequence was obtained by viral RNA extraction and nested PCR amplification. Genotypes, TDR and transmission cluster analyses were conducted using phylogenetic tree, Stanford HIV database algorithm and HIV-TRACE, respectively. Univariate and multivariate logistic regression analyses were performed to identify the factors associated with TDR.ResultsA total of 1,161 sequences were successfully sequenced, of which CRF07_BC (40.6%), CRF01_AE (38.4%) and CRF105_0107 (6.3%) were the main HIV-1 genotypes. The overall prevalence of TDR was 7.8%, with 2.0% to PIs, 1.0% to NRTIs, and 4.8% to NNRTIs. No sequence showed double-class resistance. Multivariate logistic regression analysis revealed that compared with CRF01_AE, subtype B (OR = 2.869, 95%CI: 1.093–7.420) and female (OR = 2.359, 95%CI: 1.182–4.707) were risk factors for TDR. Q58E was the most prevalent detected protease inhibitor (PI) -associated mutation, and V179E was the most frequently detected non-nucleoside reverse transcriptase inhibitor (NNRTI) -associated mutation. A total of 613 (52.8%) sequences were segregated into 137 clusters, ranging from 2 to 74 sequences. Among 44 individuals with TDR (48.4%) within 21 clusters, K103N/KN was the most frequent TDR-associated mutation (31.8%), followed by Q58E/QE (20.5%) and G190A (15.9%). Individuals with the same TDR-associated mutations were usually cross-linked in transmission clusters. Moreover, we identified 9 clusters in which there was a transmission relationship between drug-resistant individuals, and 4 clusters in which drug-resistant cases increased during the study period.ConclusionThe overall prevalence of TDR in Nanjing was at a moderate level during the past 3 years. However, nearly half of TDR individuals were included in the transmission clusters, and some drug-resistant individuals have transmitted in the clusters. Therefore, HIV drug-resistance prevention, monitoring and response efforts should be sustained and expanded to reduce the prevalence and transmission of TDR in Nanjing