贝克休斯

Valves and their internal components operate under continuous friction, wear, and tribological loading during service. These effects become more complex and potentially more severe when valves operate in high-pressure hydrogen environments. This paper presents an analytical review and conceptual framework that integrates tribological behavior with hydrogen embrittlement mechanisms in valve internal components. The study examines contact conditions in valve internals, including seat–disc interfaces and other sliding surfaces. Particular attention is given to contact stress estimation, asperity-level interactions, and realistic friction and wear modeling. Tribological models such as contact mechanics and wear relationships are discussed alongside hydrogen transport and embrittlement mechanisms. The interaction between these processes is analyzed to highlight how hydrogen exposure may modify tribological parameters such as friction coefficient, effective hardness, and crack propagation resistance. The paper further discusses mitigation strategies including material selection, hardfacing alloys, advanced coatings, and surface finishing techniques that improve resistance to hydrogen-assisted tribological degradation. Design considerations aimed at reducing excessive contact stress, minimizing sharp geometric stress concentrators, and optimizing valve seating forces are also addressed. Additionally, lubrication strategies suitable for hydrogen service are briefly examined. Finally, a conceptual quantitative framework is proposed to estimate the relative severity of tribological degradation in valve internals operating under high-pressure hydrogen conditions.

An increasing number of sensors and actuators are being used in today’s high-tech drilling tools to further optimize the drilling process. Each sensor and actuator either generates data that needs to be processed or requires real-time input control signals. RISC-V processors are being developed to meet the computational demands of today’s applications. A known bottleneck for processors is the data flow and instruction input to the processor, especially as memory response times are particularly high for the state-of-the-art harsh environment silicon-on-insulator (SOI) technology. This paper presents a high-performance instruction fetch architecture that achieves a high clock frequency while preserving high instructions per cycle. We evaluate different approaches implementing and propose a design that is able to reach up to 0.8 instruction per cycle (IPC) with a clock frequency of 181 MHz, which is more than twice as high as previous designs in this technology. This design is first tested in isolation an then combined with our current RISC-V processor specially designed to be used in such a harsh environment. This architecture achieves 146.5 million instructions per second (MIPS), which is four times higher than other off the shelf solution synthesized for the same harsh environment technology.

Meta-learning algorithms face a fundamental challenge: while they train on episodes from one distribution and test on episodes from different distributions, current approaches do not capture unlabeled representations in episodes. We present MetaRep, a novel meta-representation learning framework that learns unsupervised latent representations within episodes to address this gap. Our approach employs weakly augmented samples for the support set and strongly augmented variants for the query set, utilizing a temperature-scaled cross-entropy loss to prevent overfitting during representation learning. The learned parameters are then fine-tuned through supervised meta-learning, making MetaRep model-agnostic and capable of improving any meta-learning architecture. Through extensive experiments on standard few-shot learning benchmarks, we demonstrate that MetaRep significantly improves accuracy across multiple architectures including MAML (+3.8 https://github.com/atik666/representationTransfer .

Abstract This paper addresses the growing need to expand geothermal energy production beyond conventional hydrothermal resources by exploring next-generation geothermal systems. It provides a comprehensive overview of next-generation geothermal systems, focusing on the technological readiness, economic viability, environmental impacts, opportunities, and challenges associated with enhanced geothermal systems (EGS), advanced geothermal systems (AGS), and supercritical geothermal resources, as well as the potential for geothermal to contribute to green hydrogen production and lithium extraction. The review evaluates prominent geothermal initiatives, including Iceland's IDDP-2 project, Japan's Beyond Brittle project, and the Kakkonda Drilling Studies. The methodology includes a comprehensive systematic literature review of academic articles, scientific publications, and industry reports, supplemented by data from government and academic sources. Studies are categorized thematically according to geological environments, exploration and drilling methodologies, energy conversion technologies, and economic and environmental impacts. The analysis examines cutting-edge technologies and conducts comparative assessments between supercritical and conventional geothermal systems to evaluate energy conversion performance and sustainability. Conventional geothermal resources are limited by specific geological requirements, while next-generation geothermal systems offer broader applicability. EGS can enhance energy production by creating permeability in hot, dry rock, but poses risks of induced seismicity and requires careful water management. AGS, especially closed-loop systems, offer environmental benefits and flexibility in different geologic settings through the use of borehole heat exchangers and different working fluids, but require technological innovation and significant investment. Supercritical geothermal resources, found at temperatures above 374°C, have the potential for high energy output, but present extreme technological and engineering challenges due to high temperature and pressure conditions that affect equipment selection and drilling environments. Geothermal energy can contribute significantly to green hydrogen production through electrolysis and high-temperature steam separation. In addition, geothermal brines are a promising source for lithium extraction, although further research is needed to optimize extraction processes and minimize environmental impacts. This paper provides a comparative analysis of conventional and unconventional geothermal development. It provides an overview of the methods available and clarifies the confusion and arbitrary use of common terms that combine characteristics of both approaches. By synthesizing information on technological advances, risk mitigation strategies, and economic/environmental considerations, this review provides a valuable resource for energy professionals and policy makers involved in establishing geothermal projects and scientific collaborations.

Abstract Retrieving a 1.5-in OD, 17-ft-long fish weighing approximately 150 lb from a horizontal well with 3.92-in casing posed significant operational challenges. The fish had remained in an H2S environment for over a year, creating uncertainties about its condition, corrosion risk, and mechanical integrity. Additional complications included unknown depth, possible debris and wire remnants above the fish, and an 87° deviation, all of which increased the likelihood of multiple fishing attempts and extended intervention time. To overcome these challenges, a 360° downhole camera was deployed via coiled tubing (CT) to visually confirm the fish's location and assess the surrounding environment. This imaging step provided critical insight into debris and wire remnants, enabling accurate planning and reducing uncertainty. Based on these findings, a customized fishing bottomhole assembly (BHA) was designed and equipped with a casing collar locator (CCL) and tension/compression tool (TCT) sensors. Real-time telemetry from these sensors ensured precise depth correlation and continuous monitoring during tagging and latching attempts, allowing immediate feedback for decision-making. The fish was identified and located at the depth of 8,072 ft in a highly deviated section and successfully retrieved in a single run. Imaging confirmed minimal obstruction and no significant deformation, while TCT readings validated engagement and indicated an approximately 150-lb weight change upon retrieval. Post-job analysis confirmed minimal wear on the fishing assembly, and the flawless completion of operation. This case demonstrates the effectiveness of integrating visual diagnostics with sensor-based feedback in CT fishing operations under sour and high-deviation conditions. The approach minimized operational risk, reduced intervention time, and avoided multiple fishing runs, which could have escalated cost and complexity. Lessons learned from this operation are broadly applicable to similar retrieval challenges, highlighting how advanced imaging and real-time telemetry enhance situational awareness, improve efficiency, and deliver significant value to the industry.