Search Results (1,005)

The energy performance of a building reflects its typical energy use and is influenced by factors such as the building envelope (insulation and windows), system efficiency (particularly for heating, cooling, and domestic hot water), and the integration of renewable energy sources. Improving energy performance helps save energy, boost energy independence and security, lower energy costs, and reduce the need for grid investments. Standardizing energy performance assessments enables benchmarking and comparison of building efficiency, encouraging informed decision-making. In this context, the paper presents a knowledge discovery-driven intelligent decision-making system, designed, developed, and tested to identify the best strategies for prioritizing buildings in the envelope process. The system combines data mining techniques with statistical analysis to precisely rank and thoroughly evaluate low-energy-performance buildings and to develop scenario-based strategies for enveloping the buildings to achieve high energy efficiency (associated with nearly zero-energy buildings) under real-world conditions. Testing of the proposed intelligent decision-making system was conducted using a real building database of approximately 3900 records, uploaded from the Romanian central administration website. Under the highest-performance scenario of the envelope-priority strategy, which includes nearly zero-energy building standards, energy savings exceeded 50% across all categories: 51.70% for healthcare, 53.40% for residential, 60.11% for administrative and office buildings, and 69.92% for educational institutions. Overall, the average savings across all building types were 59.81% (644.86 GWh/year). Full article

Niche and interspecific association are important components of community ecology and are of great significance for revealing the mechanisms of community assembly and its stability. In this study, the woody plant communities of Betula platyphylla Sukaczev forests in the Niyang River Basin of southeastern Qinghai–Tibet Plateau were taken as the research object. The niche, interspecific association, and community stability of dominant tree species in B. platyphylla forests were analyzed using the Levins index (B_L), Shannon index (B_S), Pianka index (O_ik), Schoener index (C_ik), variance ratio (VR), chi-square test, association coefficient (AC), Spearman rank correlation, and M. Godron stability methods. The results showed that a total of 71 woody plant species were recorded across 48 plots, mainly belonging to Rosaceae, Ericaceae, and Caprifoliaceae. B. platyphylla, Quercus aquifolioides Rehder & E. H. Wilson, Sorbus rehderiana Koehne, and Berberis gyalaica Ahrendt had relatively large niche breadths, indicating strong resource utilization ability and a wide range of spatial adaptation. They were the main constructive species and dominant species of B. platyphylla forest communities in this basin. The overall niche overlap of woody plant communities was relatively low, indicating relatively obvious differentiation in resource utilization among different species. Interspecific association analysis showed that the dominant species in the tree layer exhibited an overall significantly positive association, whereas those in the shrub layer exhibited an overall non-significantly positive association. The associations between species pairs were mainly non-significant, and the overall interspecific association was weak. Most species showed a relatively independent distribution pattern, reflecting weak interspecific competition within the community. Community stability analysis showed that the Euclidean distance between the tree layer and the theoretical stability point (20, 80) was 20.17, whereas that of the shrub layer was 27.98, indicating that the tree layer was more stable than the shrub layer. Overall, the community may not yet have reached a fully stable state. The results provide important references for biodiversity conservation, vegetation restoration, and sustainable forest management in alpine canyon ecosystems. Future studies should incorporate environmental factors such as soil properties and hydrothermal conditions to further reveal the ecological mechanisms driving community succession and stability. Full article

The main objective of this study is to investigate smoking dynamics, identify the most influential factors governing smoking behavior, and develop effective intervention strategies through the integration of fractional-order modeling, sensitivity analysis, optimal control theory, and artificial neural networks (ANNs). A nonlinear fractional-order compartmental model is formulated by dividing the population into potential smokers, light smokers, heavy smokers, and quit smokers. The smoking reproduction number is derived to characterize the transmission and persistence of smoking behavior within the population. To determine the impact of model parameters on smoking dynamics, both normalized forward sensitivity analysis and global sensitivity analysis based on Latin Hypercube Sampling (LHS) with Partial Rank Correlation Coefficient (PRCC) are performed. The obtained results identify the most sensitive transmission and progression parameters and demonstrate their important role in shaping smoking prevalence within the community. Furthermore, the classical integer-order model is compared with the fractional-order formulation, where the fractional model provides a more realistic description due to its ability to incorporate memory and hereditary effects associated with smoking behavior. An optimal control framework involving awareness and treatment strategies is further introduced to investigate effective smoking reduction policies. The numerical results demonstrate that awareness campaigns reduce smoking initiation, while treatment interventions increase smoking cessation, and the combined implementation of both strategies produces the most significant reduction in smoking prevalence. The consistency between the sensitivity analysis and optimal control results further supports the reliability of the proposed framework. Numerical simulations are carried out to analyze the qualitative and quantitative behavior of the system under different epidemiological scenarios. In addition, an ANN-based computational framework is employed as an efficient numerical tool to accurately approximate the complex dynamics of the proposed fractional-order smoking model with very low prediction error. Overall, the present study provides a comprehensive mathematical and computational framework for understanding, analyzing, and controlling smoking behavior within a population. Full article

This study aimed to examine variables associated with manipulation tendency levels in adults and to describe current patterns using a decision tree method as a classification-based analytical approach. The research sample consisted of 543 adults (358 women, 65.93%; 185 men, 34.07%) residing in Turkey, aged 18 to 45 years (M = 25.79, SD = 4.23). Data were collected using a researcher-developed personal information form, the Manipulation Scale in Human Relations, the Rosenberg Self-Esteem Scale, and the Relationship Scales Questionnaire. The total composite score of the Manipulation Scale was used as the outcome variable and is referred to throughout as “manipulation tendency.” Manipulation tendency scores were dichotomized into low versus high groups using a median split to facilitate C&RT-based classification. Classification and Regression Tree was used to examine the hierarchical structure of variables related to manipulation tendency levels and to identify classification patterns among study variables. The decision tree approach was used not merely as an alternative statistical technique, but as an interpretable classification framework capable of identifying hierarchical and conditional pathways associated with manipulation tendency. Data were stratified-randomly split into training and test sets (70/30), and tree complexity was tuned via cross-validation using cost-complexity pruning. Model performance indicated acceptable classification accuracy within this sample, with a test-set accuracy of 0.81 (sensitivity = 0.74, specificity = 0.88, precision = 0.86, F1 = 0.79) and training accuracy of 0.86. The findings indicated several influential variables in classifying manipulation tendency levels, ranked by importance: preoccupied attachment style, self-esteem, age, dismissive attachment style, gender, secure attachment style, and fearful attachment style. Preoccupied attachment style was identified as the most salient variable in differentiating between high and low manipulation tendency groups. The decision tree structure showed that younger adults with higher preoccupied attachment scores were more frequently classified into the high manipulation tendency group. Self-esteem emerged as the second most influential variable, with lower self-esteem levels being more commonly observed among individuals classified in the high manipulation tendency group. Age also played a notable role in classification, with higher manipulation tendency classifications occurring more frequently among younger individuals. Dismissive attachment style contributed to the differentiation of manipulation tendency levels, particularly within specific attachment and age profiles. Gender-related patterns indicated that men were more frequently classified into higher manipulation tendency groups, especially among individuals with low self-esteem. Overall, the findings highlight the multifactorial and hierarchical nature of manipulation tendency classifications. They contribute to the literature by showing how attachment-related characteristics, developmental factors, and psychological variables jointly differentiate manipulation tendency profiles. These findings highlight the value of decision tree modelling for translating conventional psychological predictors into interpretable classification profiles of manipulation tendency. Full article

Osteoarthritis (OA) is a highly prevalent joint disorder traditionally considered a consequence of mechanical cartilage wear; however, it is now recognized as a complex, multifactorial disease driven by interconnected molecular and cellular mechanisms. This narrative review synthesizes current knowledge on key pathogenic pathways underlying OA progression, with a focus on inflammatory signaling, subchondral bone remodeling, and dysregulation of mineral metabolism. Chronic low-grade inflammation promotes catabolic responses in chondrocytes and contributes to cartilage degradation. In addition, obesity influences OA pathogenesis through both biomechanical loading and adipokine-mediated inflammatory mechanisms. Alterations in the receptor activator of nuclear factor kappa-B/receptor activator of nuclear factor kappa-B ligand/osteoprotegerin (RANK/RANKL/OPG) axis disrupt bone homeostasis and promote pathological subchondral remodeling, while imbalances in inorganic phosphate metabolism contribute to crystal deposition and further joint damage. These processes interact synergistically, driving disease progression. Current therapeutic strategies remain largely symptomatic and do not adequately target underlying molecular drivers. A deeper understanding of these mechanisms may facilitate the development of disease-modifying therapies. Full article

Background and Objectives: Surfactant protein B (SFTPB) is a surfactant-associated protein secreted by alveolar type II epithelial cells that plays a critical role in maintaining alveolar stability and surface tension. Although SFTPB is closely associated with pulmonary epithelial differentiation, its clinical significance in different non-small cell lung cancer (NSCLC) subtypes remains unclear. This study investigated the clinicopathologic and prognostic significance of SFTPB expression in lung adenocarcinoma (AD) and lung squamous cell carcinoma (SCC) using The Cancer Genome Atlas (TCGA) dataset. Materials and Methods: SFTPB mRNA expression data and clinicopathologic information were obtained from TCGA cohorts of AD and SCC patients. Patients were stratified into high- and low-expression groups according to median SFTPB expression levels. Associations between SFTPB expression and clinicopathologic variables were analyzed, and correlation analyses were performed with major oncogenic genes. Overall survival (OS) and relapse-free survival (RFS) were evaluated using Kaplan–Meier survival analysis and log-rank testing. Multivariate Cox proportional hazards regression analyses were performed after adjustment for age, sex, and pathological stage. Results: In AD, high SFTPB expression was significantly associated with lower pathologic stage (p = 0.011) and lower N stage (p = 0.006). SFTPB expression showed significant negative correlations with EGFR (R = −0.140, p = 0.002) and BRAF (R = −0.177, p < 0.001) and a positive correlation with TP53 (R = 0.128, p = 0.004). Patients with high SFTPB expression demonstrated significantly improved OS compared with those with low expression (p < 0.001), while a trend toward prolonged RFS was observed without statistical significance (p = 0.089). Multivariate analysis confirmed high SFTPB expression as an independent favorable prognostic factor in AD (HR = 0.551, 95% CI = 0.405–0.748, p < 0.001). In SCC, high SFTPB expression was also significantly associated with lower pathologic stage (p = 0.009) and lower N stage (p = 0.007). SFTPB expression showed significant negative correlations with SOX2 (R = −0.176, p < 0.001), PIK3CA (R = −0.143, p = 0.002), and TP53 (R = −0.101, p = 0.026). In contrast to AD, high SFTPB expression was significantly associated with poorer OS (p = 0.026), whereas no significant difference in RFS was observed (p = 0.307). Multivariate analysis demonstrated that high SFTPB expression was an independent adverse prognostic factor in SCC (HR = 1.347, 95% CI = 1.028–1.767, p = 0.031). Conclusions: SFTPB expression is significantly associated with clinicopathologic characteristics and molecular signatures in both AD and SCC. However, its prognostic implications differ according to histologic subtype. High SFTPB expression independently predicts favorable survival in AD but unfavorable survival in SCC, suggesting distinct lineage-specific biological roles in NSCLC. These findings support SFTPB as a subtype-specific prognostic biomarker reflecting differential differentiation states and lineage context in NSCLC. Full article

Background and Objectives: Systemic inflammation, nutritional impairment, and immune dysregulation are important determinants of outcomes in advanced malignancies. The C-reactive protein–albumin–lymphocyte (CALLY) index is a composite biomarker that reflects these biological domains, but its prognostic relevance in de novo metastatic gastric adenocarcinoma has not been well defined. Materials and Methods: This multicenter retrospective cohort study included 234 patients with de novo metastatic gastric adenocarcinoma treated between January 2015 and December 2025. Baseline CALLY was calculated before systemic treatment. A cohort-specific CALLY threshold of 1.21 was obtained using conventional ROC analysis, with all-cause mortality status at last follow-up as the binary outcome. Survival was evaluated using Kaplan–Meier analysis and Cox proportional hazards regression. To avoid guarantee-time bias, treatment exposure variables that became known only after treatment initiation, including the number of chemotherapy cycles delivered, were excluded from the baseline Cox models. Diagnosis period was included in the multivariable model to account for treatment-era heterogeneity. Results: Overall, 133 patients (56.8%) were classified as low-CALLY and 101 (43.2%) as high-CALLY. Median OS was significantly longer in the high-CALLY group than in the low-CALLY group (13.9 vs. 8.6 months; log-rank p < 0.001). Low CALLY was associated with inferior OS in univariable analysis (HR: 1.77, 95% CI: 1.31–2.38; p < 0.001) and remained associated with worse OS after adjustment for baseline clinicopathological factors, first-line treatment category, and diagnosis period (adjusted HR: 1.77, 95% CI: 1.24–2.53; p = 0.002). The PFS difference between the CALLY groups was not statistically significant (HR: 1.15, 95% CI: 0.87–1.51; p = 0.326). Conclusions: Low baseline CALLY was independently associated with shorter OS in this retrospective cohort. These findings support CALLY as a practical candidate prognostic biomarker, while external validation and time-to-event-based cut-off assessment are needed before clinical implementation. Full article

Background: Hepatocellular carcinoma (HCC) is a leading indication for liver transplantation (LT), representing a curative treatment option for selected patients. A remaining clinical challenge is the recurrence of HCC after transplantation, impacting long-term graft and patient survival. The impact of different bridging therapies (BTs) such as transarterial chemoembolization (TACE), local ablation or liver resection on recurrence rates remains unclear. We assessed post-transplant HCC recurrence and survival focusing on the role of pre-transplant bridging therapies. Methods: Adult recipients undergoing LT for HCC at Hannover Medical School from January 2007 to September 2022 were retrospectively analyzed (n = 185). Recurrence was defined as confirmed intra or extrahepatic HCC after LT. Overall survival (OS) and recurrence-free survival (RFS) were analyzed using Kaplan–Meier estimation and log-rank testing; multivariable Cox proportional hazards regression was used to identify independent factors influencing OS. Results: Pre-transplant BT was administered in 85.4% of patients, consisting of only TACE, (n = 20; 10.8%), local ablation, (n = 32; 17.3%), liver resection (n = 27; 14.6%) or a multimodal approach (n = 50; 27%). Post-transplant HCC recurrence rate was 9.2% with a median time to recurrence of 845 days (range 126–3978 days). Patients with post-transplant HCC recurrence had a significantly higher prevalence of viral hepatitis (70.6% vs. 57.1%; p = 0.01), higher pre-transplant AFP peak levels (37.5 vs. 10 ng/mL; p = 0.03), larger tumor sizes (median 3.95 cm vs. 2.6 cm; p = 0.03) and more poorly differentiated tumors (G3; 25.0% vs. 5.3%, p = 0.04). Kaplan–Meier analysis showed significant overall differences in OS and RFS among bridging therapy groups (p = 0.03). In the subgroup of early HCC < 3 cm, local ablation was associated with significantly improved OS compared to TACE (p = 0.035). Last measured pre-transplant AFP < 15 ng/mL was a significant predictor of both improved OS (p = 0.006) and RFS (p = 0.008), whereas peak AFP did not reach significance after correction. Multivariable Cox regression revealed HCC recurrence, high recipient BMI and low LabMELD as independently associated with reduced OS after LT. Median OS after HCC recurrence was 13 months. Conclusions: Our monocentric retrospective data indicate that post-transplant HCC recurrence is uncommon but remains a challenge regarding life expectancy and is influenced by pre-transplant bridging therapy. In the subgroup of early HCC < 3 cm, local ablation was associated with significantly improved OS compared to TACE. Last measured pre-transplant AFP < 15 ng/mL was associated with both improved OS and RFS, suggesting that treatment response may also represent a prognostically relevant factor. Further prospective validation of contemporary locoregional and systemic bridging approaches, especially in the context of tumor biology and treatment response, is warranted. Full article

Background: Infection with HIV increases the risk of developing hepatocellular carcinoma, and the albumin–bilirubin grade assesses liver function and has been shown to be prognostic. We evaluated the albumin–bilirubin score/grade and the HIV status of hepatocellular carcinoma patients in Zimbabwe and explored the impact on median survival. Methods: A 10-year retrospective observational study of hepatocellular carcinoma patients was conducted at a single tertiary-level cancer center in Harare, Zimbabwe. Survival probabilities were estimated using the Kaplan–Meier method, and differences between groups were compared using the log-rank test and Cox proportional hazards regression. Results: A total of 95 participants were evaluated, of whom 72.6% were male. Most HCC cases were diagnosed using imaging and serum alpha-fetoprotein, with 59% presenting at Barcelona Clinic Liver Cancer stage C or D. Compared with patients who were HIV-negative, patients who were HIV-positive (OR 2.2; 95% CI 1.54–5.26, p = 0.0008) or had an unknown HIV status (OR 4.2; 95% CI 2.2–8; p < 0.0001) had higher odds of being at ALBI grade 3 at the time of HCC diagnosis. ALBI grade 1 patients had better median survival compared to grade 2 and 3 patients, though this result was statistically insignificant (grade 2: HR = 1.45, 95% CI: 0.30–7.13; grade 3: HR = 1.47, 95% CI: 0.28–7.60). Regarding HIV status, median survival was 2.4 months for HIV-positive patients and 2.6 months for HIV-negative patients (p = 0.51); HIV positivity was not significantly associated with median survival (HR = 1.50, 95% CI: 0.46–4.91). Only 30.5% of patients received cancer therapy, all of which was palliative, with no observed survival benefit. Conclusions: The majority of hepatocellular carcinoma patients in Zimbabwe were diagnosed at an advanced stage, with hepatitis B or C viral infections and alcohol consumption identified as primary risk factors. Median survival rates were low. Neither HIV infection nor ALBI score grading had a significant impact on median survival. Full article

Objective: The present study aimed to determine clinical and surgical variables associated with postoperative morbidity and 10-year mortality in isolated mitral valve replacement (MVR) and to assess the association between sex and postoperative outcomes. Materials and Methods: A total of 1629 patients undergoing isolated MVR in one center during the period between January 2000 and December 2015 were retrospectively analyzed. Hospital records provided demographic, clinical, echocardiographic, and operative data. Cox regression analyses were used to determine factors associated with postoperative morbidity and long-term mortality. The Kaplan–Meier method was used to analyze long-term survival, and the log-rank test was used to compare the groups. Results: A total of 866 (53.1%) patients were male and 763 (46.9%) were female, and the average age was 63.8 ± 10.9 years. There were no significant differences in female and male patients regarding basic demographic and clinical characteristics. The first 30-day in-hospital morbidity rate was also significantly greater in women than in men (25.7% vs. 20.6%; p = 0.015). The in-hospital mortality was more prevalent among women (5.0% vs. 3.0%; p = 0.043). Age, sex (female), diabetes mellitus, pulmonary hypertension, chronic obstructive pulmonary disease, critical preoperative condition, high body mass index, longer cardiopulmonary bypass time, and low left ventricular functioning were significantly associated with postoperative morbidity in multivariable analysis. The total mortality rate during a 10-year follow-up was 33.2%, which was considerably higher among women compared to men (36.3 vs. 30.5; p = 0.013). Kaplan–Meier analysis demonstrated significantly lower long-term survival in female patients (log-rank p = 0.011). Conclusions: Morbidity and mortality following isolated MVR are closely related to patient-related factors. Female sex showed a significant adjusted association with higher 10-year mortality in multivariable analysis, warranting careful long-term risk assessment in female patients. Full article

Detecting infrared moving targets in low-altitude remote sensing scenes remains challenging due to strong clutter, scale inconsistency, and residual interference. Because these factors are often coupled in complex scenes and cannot be handled effectively by a single operation, a three-stage progressive Decoupled Separation, Enhancement, and Purification (DSEP) framework is proposed. The method integrates edge-preserving background decoupling, scale-consistent spatial screening, and residual-response purification into a non-iterative feedforward pipeline. Experiments on six representative self-collected infrared sequences and six selected scenes from the public SIRST dataset suggest that DSEP produces relatively compact and spatially continuous target responses while suppressing background interference. On the self-collected dataset, the method can achieve SCRG and BSF values up to 10.61 and 7.38, respectively, with a processing time of 0.009–0.016 s per frame. Compared with representative spatial filtering, local contrast, and low-rank decomposition methods, DSEP shows a relatively favorable balance between detection performance and low-latency processing efficiency. Although the performance gain becomes smaller in some SIRST scenes, the proposed method still shows generally stable detection performance across the evaluated scenes. Full article

As they are home to numerous significant ecosystems, natural resources, and a growing population, coastal regions are among the most vital locations on Earth. This study, pertaining to the east coast of the UAE, integrates nine distinct characteristics to provide a thorough methodology for assessing integrated coastal vulnerability. Land use and land cover (LULC), nearshore bathymetry, coastal geomorphology, coastal slope, shoreline erosion and deposition, population density, wave and tide, and nearshore benthic features are important parameters that are examined. For the first time, coastal benthic features are included to assess coastal vulnerability in this region. By combining the variably weighted rank values of the nine variables, an Integrated Coastal Vulnerability Index was created, which divides the coastline into low-, moderate-, and high-risk categories. The methodology improves the precision of regional risk assessments by combining these factors with data from real-time coastal surveillance. Approximately 26.4% of the UAE’s 178 km east coast (or 47.1 km) is at high risk, followed by 17.3% (or 30.9 km) at moderate risk and 56.3% (or 100.2 km) at low risk. The offshore areas of the east coast of the UAE are prone to shoaling and tunneling effects from incoming high waves at certain areas due to the concave-shaped bathymetry and medium-range canyons present, which exacerbate storm surges or tsunamis due to the shoaling effect. For a 3 m rise in sea level, most significantly, 5.58 km² of plantation and 14.39 km² of residential areas will be damaged in the Kalba and Fujairah regions. Additional commercial spaces totaling 1.07 km² will also have an impact, adding to the existing 2.59 km² of oil bunkers in Fujairah. More than 40,000 people who live within 3.0 m of the UAE’s east coast in six separate districts—Kalba, Fujairah City, Mirbah and Qidfa, Khorfakkan, Dadna and Bidya, and Dibba—will be impacted if a tsunami wave or storm surge of three meters strikes the east coast. Our results are intended to assist government agencies, coastal planners, and policymakers in the Northeast Emirates (Fujairah and Sharjah) in creating sustainable and successful adaptation and mitigation plans for areas most vulnerable to coastal hazards. In addition to enhancing scientific knowledge of coastal vulnerabilities, this integrative method is a useful tool for making well-informed decisions in the face of shifting socio-economic and climatic situations. Full article

Human development is increasingly expected to reflect progress in health, education, living conditions, and sustainability. Yet evidence on how specific Sustainable Development Indicators (SDIs) relate to such progress remains limited, especially in studies that jointly consider cross-income heterogeneity, high-dimensional indicators, and nonlinear relationships. This study examines the SDI–HDI relationship across low-, lower-middle-, upper-middle-, and high-income countries using 408 World Bank SDG indicators and UNDP HDI series for 1990–2020. An interpretable Random Forest framework, combined with SHAP rankings and Partial Dependence Plots, identifies the most influential predictors and marginal associations with HDI. The model shows strong predictive performance across income groups and marked heterogeneity in the predictors associated with HDI. In low-income countries, HDI is mainly associated with early-life health conditions and human capital; in lower-middle-income countries, electrification and service access become more prominent; and in upper-middle- and high-income groups, digital connectivity, higher education, and institutional factors gain importance. Mortality-related indicators are consistently associated with lower predicted HDI, whereas literacy, electricity access, and internet use are associated with higher HDI. These results highlight how AI-based analytical tools can support sustainable economic development by identifying income-specific development priorities and structural constraints. They also suggest that disparities in health, education, infrastructure, and digital connectivity may influence the conditions under which entrepreneurial opportunities emerge or remain constrained across development stages. Overall, the SDI–HDI relationship is nonlinear and income-specific, supporting more differentiated, data-driven development strategies. Full article

With high renewable penetration, power system oscillations become more complex. Since internal control details of renewable stations are often inaccessible, classic participation analysis relying on detailed models is difficult to apply, making weak node identification urgently needed. To address this problem, this paper proposes a residue-centered impedance-based method for small-signal stability in renewable energy-dominated power systems. First, an equivalent state-space model is built from station impedance models, linking the black-box impedance and white-box state-space participation analysis. Then, the physical essence of weak node identification is analyzed, and a residue-centered participation factor is introduced as the indicator. Subsequently, the effect of the station impedances at weak nodes on system stability is quantified. Finally, the method is validated on a four-station testing system and a real-life renewable energy-dominated power system. The rank correlation between the proposed method and the traditional state-space method is close to 1, demonstrating its effectiveness for system-level weak node identification. The proposed method provides engineering guidance for parameter tuning and damping control in practical power systems, which can help improve renewable energy accommodation and support low-carbon, secure, and sustainable power system operation. Full article

Fracability evaluation is essential for hydraulic fracturing interval selection and stimulation optimization in ultra-low permeability sandstone reservoirs. Conventional brittleness-based methods derived from shale reservoirs are insufficient for characterizing fracture initiation difficulty, fracture propagation resistance, natural fracture interaction, and post-fracture conductivity in tight sandstone formations. In this study, the Chang 6 ultra-low permeability sandstone reservoir in Block H was investigated by integrating triaxial rock mechanical testing, Kaiser acoustic emission stress measurement, FMI/MCI image-log interpretation, and logging-based dynamic-to-static mechanical parameter conversion. The results show that the reservoir is characterized by relatively high stiffness and strength, with an average static Young’s modulus, Poisson’s ratio, and compressive strength of 24.05 GPa, 0.21, and 131.97 MPa, respectively. The all-sample average maximum and minimum horizontal principal stresses are 35.70 MPa and 29.91 MPa, respectively. After excluding the anomalous C6-19 stress-memory response, the representative average ${\sigma }_H$ and ${\sigma }_h$ are 37.06 MPa and 30.95 MPa, respectively, with a representative stress difference of 6.12 MPa. A multi-factor integrated fracability index was established by considering brittleness, natural fracture development, compressive strength, equivalent fracture propagation resistance, and effective confining pressure. The average fracability indices of Wells L7 and L26 are 0.624 and 0.596, respectively, indicating relatively favorable fracturing potential. The proposed workflow provides a geomechanically constrained method for relative sweet-spot ranking and preliminary hydraulic fracturing design in ultra-low permeability sandstone reservoirs. Full article