Search Results (503)

A reliable geothermal risk assessment methodology is key to any business decision. To be effective, it must be based on widely accepted principles, be easy to apply, be auditable, and produce consistent results. In this paper, we review the key characteristics of a geothermal project and propose a novel approach derived from risk and uncertainty definitions used in the hydrocarbon industry. According to the proposed methodology, the probability of success is assessed by estimating three different components. The first is the geological probability of success, which is the likelihood that the geological model on which the geothermal project is based is correct and that the key fundamental geological elements are present. The second, the temperature threshold, is defined as the probability that the fluid is above a certain reference value. Such a reference value is the one used to design the development. Such a component, therefore, depends on the end use of the geothermal resource. The third component is the commercial probability of success and estimates the chance of a project being commercially viable using the Reverse Enthalpy Methodology. Geothermal projects do not have a single parameter that represents their monetary value. Therefore, in order to estimate it, it is necessary to make an initial assumption that can be revisited later in an iterative manner. The proposed methodology works with either the capital expenditure of the geothermal facility (power plant or direct thermal use) or the drilling cost as the initial assumption. Varying the other parameter, it estimates the probability of having a net present value (NPV) higher than zero. Full article

Natural polymer materials are increasingly utilized in drilling fluid additives. Starch has come to be applied extensively due to its low cost and favorable fluid loss reduction properties. However, its poor temperature resistance and high viscosity limit its application in high-temperature wells. This study innovatively introduces for the first time diatomite as an inorganic material in the modification process of starch-based fluid loss additives. Through synergistic modification with acrylamide and acrylic acid, we successfully resolved the longstanding challenge of balancing temperature resistance with viscosity control in existing modification methods. The newly developed fluid loss additive demonstrates remarkable performance: It remains effective at 160 °C when used independently. When added to a 4% sodium bentonite base mud, it achieves an 80% fluid loss reduction rate—significantly higher than the 18.95% observed in conventional starch-based products. The resultant filter cake exhibits thin and compact characteristics. Moreover, this additive shows superior contamination resistance, tolerating 30% NaCl and 0.6% calcium contamination, outperforming other starch-based treatments. With starch content exceeding 75%, the product not only demonstrates enhanced performance but also achieves significant cost reduction compared to conventional starch products (typically containing < 50% starch content). Full article

Osteosarcoma is one of the most common primary bone malignancies, typically occurring around the knee. However, the forearm is a rare site, with tumors in the proximal ulna being extremely uncommon. Primary sarcoma in this location presents a surgical challenge due to the complex anatomy and limited reconstructive options. We report a rare case of a 19-year-old female with non-metastatic, high-grade giant cell-rich osteosarcoma involving the right proximal ulna. To our knowledge, this is only the second reported adult case of this histological subtype in this location. The patient was treated at a specialized oncology center with neoadjuvant and adjuvant chemotherapy, along with wide intra-articular resection for local tumor control. Reconstruction was achieved using a novel, customized 3D-printed articulating cement spacer mold with plate osteosynthesis. Artificial elbow ligamentous reconstruction was performed using FiberTape and FiberWire sutures passed through drill holes, and the triceps tendon was reattached to the cement mold using an endobutton. This cost-effective and personalized surgical approach allowed successful joint reconstruction while maintaining elbow stability and function. Our case highlights a feasible reconstructive option for rare and anatomically challenging osteosarcoma presentations, contributing to the limited literature on proximal ulna giant cell-rich osteosarcoma. Full article

The accurate prediction of static formation temperature (SFT) is essential for ensuring safety and efficiency in ultra-deep well drilling operations. Excessive downhole temperatures (>150 °C) can degrade drilling fluids, damage temperature-sensitive tools, and pose serious operational risks. Conventional methods for SFT determination—including direct measurement, temperature recovery inversion, and artificial intelligence models—are often limited by post-drilling data dependency, insufficient spatial resolution, high computational costs, or a lack of adaptability to complex wellbore geometries. In this study, we propose a new pseudo-3D Kriging interpolation framework that explicitly incorporates real wellbore trajectories to improve the spatial accuracy and applicability of pre-drilling SFT predictions. By systematically optimizing key hyperparameters (θ = [10, 10], lob = [0.1, 0.1], upb = [20, 200]) and applying a grid resolution of 100 × 100, the model demonstrates high predictive fidelity. Validation using over 5.1 million temperature data points from 113 wells in the Shunbei Oilfield reveals a relative error consistently below 5% and spatial interpolation deviations within 5 °C. The proposed approach enables high-resolution, trajectory-integrated SFT forecasting before drilling with practical computational requirements, thereby supporting proactive thermal risk mitigation and significantly enhancing operational decision-making on ultra-deep wells. Full article

Emergencies can occur unexpectedly and require immediate action, especially in aviation, where time pressure and uncertainty are high. This study focused on improving emergency evacuation in airport and aircraft scenarios using real-time decision-making support. A system based on the Asynchronous Advantage Actor–Critic (A3C) algorithm, an advanced deep reinforcement learning method, was developed to generate faster and more efficient evacuation routes compared to traditional models. The A3C model was tested in various scenarios, including different environmental conditions and numbers of agents, and its performance was compared with the Deep Q-Network (DQN) algorithm. The results showed that A3C achieved evacuations 43.86% faster on average and converged in fewer episodes (100 vs. 250 for DQN). In dynamic environments with moving threats, A3C also outperformed DQN in maintaining agent safety and adapting routes in real time. As the number of agents increased, A3C maintained high levels of efficiency and robustness. These findings demonstrate A3C’s strong potential to enhance evacuation planning through improved speed, adaptability, and scalability. The study concludes by highlighting the practical benefits of applying such models in real-world emergency response systems, including significantly faster evacuation times, real-time adaptability to evolving threats, and enhanced scalability for managing large crowds in high-density environments including airport terminals. The A3C-based model offers a cost-effective alternative to full-scale evacuation drills by enabling virtual scenario testing, supports proactive safety planning through predictive modeling, and contributes to the development of intelligent decision-support tools that improve coordination and reduce response time during emergencies. Full article

The optimization and control of the wellbore trajectory is one of the important technologies to improve drilling efficiency, reduce drilling cost, and ensure drilling safety in the process of modern oil and gas exploration and development. In this paper, a multi-objective wellbore trajectory optimization mathematical model is established, which takes into account the five factors of wellbore trajectory length, friction, torque, trajectory complexity, and target accuracy. A DR-NSGA-III-MGA algorithm (dynamic reference NSGA-III with multi-granularity adaptation) is proposed. By introducing multi-granularity reference vector generation and an information entropy-guided search direction adaptation mechanism, the performance of the algorithm in the complex target space is improved, and the three-stage wellbore trajectory is optimized. Simulation experiments show that the DR-NSGA-III-MGA algorithm is stable in a variety of complex problems, while maintaining good convergence, and has good generalization ability and practical application value. Full article

In recent years, the exploration and utilization of geothermal energy have received growing attention as a sustainable alternative to conventional energy sources. Reliable, data-driven identification of geothermal reservoirs, particularly in crystalline basement terrains, is crucial for reducing exploration uncertainties and costs. In such geological settings, magnetic susceptibility, radioactive heat production, and seismic wave characteristics play a vital role in evaluating geothermal energy potential. Building on this foundation, our study integrates in situ and laboratory measurements, collected using advanced sensors from spatially diverse locations, with statistical and unsupervised artificial intelligence (AI) clustering models. This integrated framework improves the effectiveness and reliability of identifying clusters of potential geothermal sites. We applied this methodology to the migmatitic gneisses within the Simav Basin in western Türkiye. Among the statistical and AI-based models evaluated, Density-Based Spatial Clustering of Applications with Noise and Autoencoder-Based Deep Clustering identified the most promising and spatially confined subregions with high geothermal production potential. The potential geothermal sites identified by the AI models align closely with those identified by statistical models and show strong agreement with independent datasets, including existing drilling locations, thermal springs, and the distribution of major earthquake epicenters in the region. Full article

This paper presents the development and analysis of a planar microfluidic microwave sensor featuring three circular complementary split-ring resonators (CSRRs) fabricated on an RO3035 substrate. The sensor demonstrates enhanced sensitivity in characterizing liquids contained in a fine glass capillary tube by leveraging a novel configuration: a central 5-split-ring CSRR with a drilled hole to suspend the capillary, flanked by two 2-split-ring CSRRs to improve the band-stop filtering effect. The sensor’s performance is benchmarked against another CSRR-based microwave sensor with a similar configuration. High linearity is observed (R² > 0.99), confirming its capability for precise ethanol concentration prediction. Compared to the replicated square CSRR design from the literature, the proposed sensor achieves a 35.22% improvement in sensitivity, with a frequency shift sensitivity of 567.41 kHz/% ethanol concentration versus 419.62 kHz/% for the reference sensor. The enhanced sensitivity is attributed to several key design strategies: increasing the intrinsic capacitance by enlarging the effective area and radial slot width to amplify edge capacitive effects, adding more split rings to intensify the resonance dip, placing additional CSRRs to improve energy extraction at resonance, and adopting circular CSRRs for superior electric field confinement. Additionally, the proposed design operates at a lower resonant frequency (2.234 GHz), which not only reduces dielectric and radiation losses but also enables the use of more cost-effective and power-efficient RF components. This advantage makes the sensor highly suitable for integration into portable and standalone sensing platforms. Full article

Multilateral wells can effectively develop complex reservoirs at a lower cost, which, in turn, enhances the overall efficiency of oilfield exploitation. However, drilling branch wells from the main wellbore can disrupt the surrounding formation stresses, leading to secondary stress concentration at the junctions, which, in turn, causes wellbore instability. This study established a coupled analysis model for wellbore stability in branch wells by integrating seepage, stress, and damage. The model explained the instability mechanisms of branch wellbores under multi-physics coupling conditions. The results showed that during drilling, the thin, interwall section of branch wells had weak resistance to external loads, with significant stress concentration and a maximum damage factor of 0.267, making it prone to instability. As drilling time progressed, fractures in the surrounding rock mass of the wellbore continuously formed, propagated, and interconnected, causing a sharp increase in the permeability of the damaged area. The seepage direction of drilling fluid in the wellbore tended towards the severely damaged interwall section, leading to a rapid increase in pore pressure there. With increasing distance from the interwall tip, the resistance to external loads strengthened, and the formation damage factor, permeability, pore pressure, and equivalent plastic strain all gradually decreased. When the drilling fluid density increased from 1.0 g/cm³ to 1.5 g/cm³, the maximum equivalent plastic strain around the wellbore decreased from 0.041 to 0.014, a reduction of 65.8%, indicating that appropriately increasing the drilling fluid density can effectively reduce the risk of wellbore instability. Full article

Geothermal heat pump systems (GHPSs) offer a sustainable and energy-efficient solution for heating and cooling buildings. Ground heat exchanger (GHE) design and configuration significantly impact on the overall performance and installation expenses of geothermal heat pump systems. This paper presents a comprehensive analysis of GHPSs, focusing on their advantages, disadvantages, key components, types, and particularly the various closed-loop GHE configurations. Detailed comparisons highlight how different designs affect thermal performance and installation costs. The findings reveal that helical GHEs offer superior thermal efficiency with reduced drilling requirements and cost savings, while coaxial GHEs, especially those using steel tubes, enhance heat transfer and enable shorter boreholes. Cost-effective options like W-type GHEs provide performance comparable to more complex systems. Additionally, triple U-tube and spiral configurations balance high efficiency with economic feasibility. The single and double U-tube remain the most common borehole geometry, though coaxial designs present distinct advantages in targeted scenarios. These insights support the optimization of vertical GHEs, advancing system performance, cost-effectiveness, and long-term sustainability in GHPS applications. Full article

Rock bursts usually happen during the hours or days after tunnel excavation, even in an unsupported opening where no collapses occur. To investigate the mechanism of those delayed failures in brittle rock tunnels, this paper showcases the performed scale-model test based upon the Jinping II headrace tunnelling project. The model test was conducted in a particularly designed loading apparatus; the scale-model is composed of a similar material for the deep brittle rock. The tunnel in the scale-model is excavated by a specially made drilling tool. The failure mode of the deep circle tunnel under isotropic and anisotropic geostress were obtained; the delay failure time was recorded, and the accompanying stresses and strains changing were monitored. Under isotropic geostress the failure shape has a smooth circle boundary, failure process totally costs 56 h. While under anisotropic geostress a dog-eared breakdown was found, the failure process amounted to 72 h. The time-to-failure was evaluated by delay failure theory, and the evaluation equation was implemented into in FEM code. Numerical simulations have been performed to simulate the failure time and failure mode. The numerical results of failure time and failure mode mainly match the scale-model testing results. Full article

Sensorineural hearing loss occurs when cochlear hair cells fail to convert mechanical sound waves into electrical signals transmitted via the auditory nerve. Cochlear implants (CIs) restore hearing by directly stimulating the auditory nerve with electrical impulses, often while preserving residual hearing. Over the past two decades, robotic-assisted techniques in otologic surgery have gained prominence for improving precision and safety. Robotic systems support critical procedures such as mastoidectomy, cochleostomy drilling, and electrode array (EA) insertion. These technologies aim to minimize trauma and enhance hearing preservation. Despite the outpatient nature of most CI surgeries, surgeons still face challenges, including anatomical complexity, imaging demands, and rising costs. Robotic systems help address these issues by streamlining workflows, reducing variability, and improving electrode placement accuracy. This review evaluates robotic systems developed for cochlear implantation, focusing on their design, surgical integration, and clinical outcomes. This review concludes that robotic systems offer low insertion speed, which leads to reduced insertion forces and lower intracochlear pressure. However, their impact on trauma, long-term hearing preservation, and speech outcome remains uncertain. Further research is needed to assess clinical durability, cost-effectiveness, and patient-reported outcomes. Full article

In modern oil and gas exploration and development, wellbore trajectory optimization and control is the key technology to improve drilling efficiency, reduce costs, and ensure safety. In the drilling operation of non-vertical wells in complex formations, the traditional static trajectory function, combined with the classical optimization algorithm, has difficulty adapting to the parameter fluctuation caused by formation changes and lacks real-time performance. Therefore, this paper proposes a wellbore trajectory optimization model based on deep reinforcement learning to realize non-vertical well trajectory design and control while drilling. Aiming at the real-time optimization requirements of complex drilling scenarios, the TD3 algorithm is adopted to solve the problem of high-dimensional continuous decision-making through delay strategy update, double Q network, and target strategy smoothing. After reinforcement learning training, the trajectory offset is significantly reduced, and the accuracy is greatly improved. This research shows that the TD3 algorithm is superior to the multi-objective optimization algorithm in optimizing key parameters, such as well deviation, kickoff point (KOP), and trajectory length, especially in well deviation and KOP optimization. This study provides a new idea for wellbore trajectory optimization and design while drilling, promotes the progress and development of intelligent drilling technology, and provides a theoretical basis and technical support for more accurate, efficient, concise, and effective wellbore trajectory optimization and design while drilling in the future. Full article

The drilling core sampling and chemical analysis method for the quantitative determination of solid mineral deposits has several drawbacks, including a low core drilling efficiency, a high core sampling cost, and a long chemical analysis cycle. In current uranium quantification practices, advanced techniques have been developed to preliminarily determine the formation of uranium content based on the interpretation results of natural $\gamma$-ray total logging. However, such methods still require supplementary core chemical analysis to derive the uranium–radium–radon balance coefficient, which is then used for equilibrium correction to obtain the true uranium content within the uranium-bearing layer. Furthermore, conventional prompt neutron time spectrum logging is constrained by low count rates, resulting in slow logging speeds that fail to meet the demands of practical engineering applications. To address this, this study proposes a uranium quantification method that corrects the natural $\gamma$-ray total logging using prompt neutron time spectrum logging. Additionally, a calibration parameter determination method necessary for quantitative interpretation is constructed. Experimental results from standardized model wells indicate that, in sandstone-type uranium deposits, the absolute error of uranium content is within $\pm 0.002\%\mathrm{eU}$, and the relative error is within $\pm 2.5\%$. These findings validate the feasibility of deriving the uranium–radium–radon balance coefficient without relying on core chemical analysis. Compared with the prompt neutron time spectrum logging method, the proposed approach significantly improves the logging speed while producing results that are essentially consistent with those of natural $\gamma$-ray total logging. It provides an efficient and accurate solution for uranium quantitative interpretation. Full article

This study presents a comprehensive treatment system for addressing leakage challenges in underground structure construction within complex karst terrains, demonstrated through the case of Baiyun Station in Guangzhou. Integrating advanced geological investigation, dynamic grouting techniques, and adaptive structural remediation strategies, this methodology effectively mitigates water inflow risks in structurally heterogeneous karst environments. Key innovations include the “one-trench two-drilling” exploration-grouting system for karst cave detection and filling, a multi-stage emergency water-gushing control protocol combining cofferdam sealing and dual-fluid grouting, and a zoned epoxy resin injection scheme for structural fissure remediation. Implementation at Baiyun Station achieved quantifiable outcomes: karst cave filling rates increased from 35.98% to 82.6%, foundation pit horizontal displacements reduced by 67–68%, and structural seepage repair rates reached 96.4%. The treatment system reduced construction costs by CNY 12 million and shortened schedules by 45 days through optimized pile formation efficiency (98% qualification rate) and minimized rework. While demonstrating superior performance in sealing > 0.2 mm fissures, limitations persist in addressing sub-micron fractures and ensuring long-term epoxy resin durability. This research establishes a replicable framework for underground engineering in karst regions, emphasizing real-time monitoring, multi-technology synergy, and environmental sustainability. Full article