Hasil untuk "Petroleum refining. Petroleum products"

JIANG ZHIGAO, MA XIAODONG, DING ANXU et al.

Given the difficulty in accurately determining the total amount of retained hydrocarbons in shale with current experimental techniques, this study aims to achieve a precise evaluation of shale oil content. Using sealed core samples from well H in the Subei Basin as the subjects, this study employed multiple experimental methods, including freeze pyrolysis, multi-temperature step pyrolysis, sealed thermal release, and two-dimensional nuclear magnetic resonance (2D-NMR) to systematically evaluate the oil content and mobility. Through comparative pyrolysis experiments at different storage times and sealed thermal release experiments, the light hydrocarbon recovery coefficient for shale oil in the second member of the Funing Formation was determined to be 1.99. Combined with the difference in pyrolysis <italic>S</italic>₂ peak areas before and after extraction, a heavy hydrocarbon correction formula was established (0.452 6×<italic>S</italic>₂-0.307 9), enabling accurate calculation of the total retained hydrocarbons. Furthermore, 2D-NMR technology was used to calibrate crude oil of different qualities, and a standard curve between hydrogen nucleus signal intensity and oil mass was established, enabling non-destructive and rapid determination of oil content. By comparing NMR spectra before and after oil washing, the <italic>T</italic>₂ cutoff values for movable and adsorbed oil were identified, facilitating the calculation of free oil content and its proportion. The experimental results showed that the oil content measured by the 2D-NMR method was highly consistent with the recovered oil content, and the proportion of free oil showed a good correlation with results from multi-temperature step pyrolysis. The technical framework of “light hydrocarbon recovery-heavy hydrocarbon correction-NMR calibration-movable oil identification” established in this study offers advantages such as relative operational simplicity, a broad detection range, and non-destructiveness to samples. Overall, it significantly improves the accuracy and efficiency of shale oil content and mobility evaluation, providing crucial experimental support for shale oil sweet spot identification, reserve calculation, and development potential assessment.

Yuchen Ren, Zhengyu Zhao, Chenhao Lin et al.

Vision Transformers (ViTs) have been widely applied in various computer vision and vision-language tasks. To gain insights into their robustness in practical scenarios, transferable adversarial examples on ViTs have been extensively studied. A typical approach to improving adversarial transferability is by refining the surrogate model. However, existing work on ViTs has restricted their surrogate refinement to backward propagation. In this work, we instead focus on Forward Propagation Refinement (FPR) and specifically refine two key modules of ViTs: attention maps and token embeddings. For attention maps, we propose Attention Map Diversification (AMD), which diversifies certain attention maps and also implicitly imposes beneficial gradient vanishing during backward propagation. For token embeddings, we propose Momentum Token Embedding (MTE), which accumulates historical token embeddings to stabilize the forward updates in both the Attention and MLP blocks. We conduct extensive experiments with adversarial examples transferred from ViTs to various CNNs and ViTs, demonstrating that our FPR outperforms the current best (backward) surrogate refinement by up to 7.0\% on average. We also validate its superiority against popular defenses and its compatibility with other transfer methods. Codes and appendix are available at https://github.com/RYC-98/FPR.

Aakriti Agrawal, Gouthaman KV, Rohith Aralikatti et al.

In this work, we identify an inherent bias in prevailing LVLM architectures toward the language modality, largely resulting from the common practice of simply appending visual embeddings to the input text sequence. To address this, we propose a simple yet effective method that refines textual embeddings by integrating average-pooled visual features. Our approach demonstrably improves visual grounding and significantly reduces hallucinations on established benchmarks. While average pooling offers a straightforward, robust, and efficient means of incorporating visual information, we believe that more sophisticated fusion methods could further enhance visual grounding and cross-modal alignment. Given that the primary focus of this work is to highlight the modality imbalance and its impact on hallucinations -- and to show that refining textual embeddings with visual information mitigates this issue -- we leave exploration of advanced fusion strategies for future work.

Anthony Genevois

In this paper, we introduce and initiate the study of quandle products of groups, a family of groups that includes graph products of groups, cactus groups, wreath products, and the recently introduced trickle groups. Our approach is geometric: we show that quandle products admit quasi-median Cayley graphs; and, then, we exploit this geometry to deduce various valuable information about quandle products.

Avigail Cohen Rimon, Mirela Ben-Chen, Or Litany

We propose a novel approach for refining a given correspondence map between two shapes. A correspondence map represented as a functional map, namely a change of basis matrix, can be additionally treated as a 2D image. With this perspective, we train an image diffusion model directly in the space of functional maps, enabling it to generate accurate maps conditioned on an inaccurate initial map. The training is done purely in the functional space, and thus is highly efficient. At inference time, we use the pointwise map corresponding to the current functional map as guidance during the diffusion process. The guidance can additionally encourage different functional map objectives, such as orthogonality and commutativity with the Laplace-Beltrami operator. We show that our approach is competitive with state-of-the-art methods of map refinement and that guided diffusion models provide a promising pathway to functional map processing.

Peng Lu, Ivan Kobyzev, Mehdi Rezagholizadeh et al.

Recent advancements in Large Language Models (LLMs) have set themselves apart with their exceptional performance in complex language modelling tasks. However, these models are also known for their significant computational and storage requirements, primarily due to the quadratic computation complexity of softmax attention. To mitigate this issue, linear attention has been designed to reduce the quadratic space-time complexity that is inherent in standard transformers. In this work, we embarked on a comprehensive exploration of three key components that substantially impact the performance of the Gated Linear Attention module: feature maps, normalization, and the gating mechanism. We developed a feature mapping function to address some crucial issues that previous suggestions overlooked. Then we offered further rationale for the integration of normalization layers to stabilize the training process. Moreover, we explored the saturation phenomenon of the gating mechanism and augmented it with a refining module. We conducted extensive experiments and showed our architecture outperforms previous Gated Linear Attention mechanisms in extensive tasks including training from scratch and post-linearization with continual pre-training.

Jiaxin Zhang, Wendi Cui, Yiran Huang et al.

Large language models (LLMs) are proficient in capturing factual knowledge across various domains. However, refining their capabilities on previously seen knowledge or integrating new knowledge from external sources remains a significant challenge. In this work, we propose a novel synthetic knowledge ingestion method called Ski, which leverages fine-grained synthesis, interleaved generation, and assemble augmentation strategies to construct high-quality data representations from raw knowledge sources. We then integrate Ski and its variations with three knowledge injection techniques: Retrieval Augmented Generation (RAG), Supervised Fine-tuning (SFT), and Continual Pre-training (CPT) to inject and refine knowledge in language models. Extensive empirical experiments are conducted on various question-answering tasks spanning finance, biomedicine, and open-generation domains to demonstrate that Ski significantly outperforms baseline methods by facilitating effective knowledge injection. We believe that our work is an important step towards enhancing the factual accuracy of LLM outputs by refining knowledge representation and injection capabilities.

Seok Ki Moon, Milan Stanko

In this work we propose and demonstrate a method to estimate the flowing gas-oil ratio and composition of a hydrocarbon well stream using measurements of pressure and temperature across a production choke. The method consists of using a numerical solver on a thermodynamic simulator to recombine a seed oil and gas until the simulated temperature drop across the choke is equal to the measured value. This method is meant for cases where it is not possible to measure periodically individual well composition. A study case and reference solution were generated using the reservoir model presented in the SPE (Society of Petroleum Engineers) comparative case Nr. 5 linked with a process simulator. Time profiles of well producing gas-oil ratio, wellstream compositions, compositions of surface conditions oil and gas, and temperature drop across the choke were generated with the models. The method proposed was then employed to estimate the flowing gas-oil ratio of the reference solution. Results show that the proposed method predicts with reasonable accuracy (maximum 12% percent error) the well gas-oil ratio and compositions during the life of the field when using compositions of surface oil and gas from initial time. When using compositions of surface oil and gas from later times, the prediction accuracy of the gas-oil ratio improves at those times but worsens for times before and after. A measurement error for the temperature drop across the choke of at least 0.01 °C is required to achieve convergence of the method. The mean percent error between the predicted and real mole fractions has an upper bound in time of 21% when using initial surface oil and gas as seed compositions.

Manasa Bhat, Santanu Manna

This research explores refined boundary conditions for a traction-free surface in a non-local micropolar half-space, combining non-local and micropolar elasticity effects to study Rayleigh wave propagation in an isotropic, homogeneous medium. This study revisits the solution for Rayleigh waves obtained within the framework of Eringen's non-local differential model. It highlights that the equivalence between the non-local differential and integral formulations breaks down for a micropolar half-space and can only be restored under specific additional boundary conditions. For mathematical tractability, equivalence is assumed for a defined subset of stresses. Asymptotic analysis is further employed to capture the effects of the boundary layer within the non-local micropolar half-space. This technique finally derives the refined boundary conditions for micropolar media.

William Hornslien

We introduce polyhedral products in an $\infty$-categorical setting. We generalize a splitting result by Bahri, Bendersky, Cohen, and Gitler that determines the stable homotopy type of the a polyhedral product. We also introduce a motivic refinement of moment-angle complexes and use the splitting result to compute cellular $\mathbb{A}^1$-homology, and $\mathbb{A}^1$-Euler characteristics.

TANG Jiandong, WANG Zhilin, GE Zhengjun

CCUS（Carbon capture, Utilization and Storage） technology is of great significance to the green and low-carbon transformation and the realization of the “dual carbon” goal, It includes important strategies like CO2 enhanced oil recovery（EOR） and sequestration. Jiangsu Oilfield has been focusing on CO2 EOR to improve recovery rates in the challenging fault block reservoirs of the Subei Basin. The company has developed four unique CO2 EOR models suitable for these complex reservoirs, featuring techniques like gravity-stable displacement. A notable achievement is the successful pilot of the methods such as “simulated horizontal well” GAGD technology in Hua-26 fault block, which led to the one hundred thousand CCUS project tailored for such reservoirs. According to statistics, Jiangsu Oilfield has injected a total of 30.34×104 t of liquid CO2, with a cumulative oil increase of 9.83×104 t, realizing a better production increase and economic benefits. These technical researches and tests can provide valuable insights for applying CO2 EOR in similar complex reservoirs.

ZHAO Zhongxin, LI Hongda, YAN Yican, REN Lu

The Nanpu Sag in the Huanghua Depression of the Bohai Bay Basin is rich in geothermal resources, with multiple geothermal fields identified, including Gaoshangpu-Liuzan, Nanpu, and Matouying. The thermal reservoirs, primarily composed of fluvial sandstone from the Guantao Formation, exhibit advantages such as high temperatures（70-90 ℃）, significant water amounts (100 m3/h), large-scale reservoirs, and thick caprocks. However, their development faces several challenges, including optimal target area selection, sustainability evaluation, efficient drilling and production processes, reinjection into sandstone reservoirs, long-distance centralized thermal water transportation, and intelligent monitoring. To address these challenges, practical exploration in the Gaoshangpu-Liuzan geothermal field has led to the development of five core technologies: 1） optimization and detailed resource evaluation technology for exploration areas; 2） well placement and thermal field simulation technology; 3） geothermal well drilling, completion, and pressure-free reinjection for sandstone thermal reservoirs; 4） multi-well collection and long-distance thermal water transportation technology; 5） intelligent management and control technology for geothermal development. These advancements provide technical support for geothermal heating projects in the Gaoshangpu-Liuzan geothermal field and the geothermal development efforts of Jidong Oilfield.

Guoyong LIU, Songtao WU, Kunyu WU et al.

Based on the oil and gas exploration in western depression of the Qaidam Basin, NW China, combined with the geochemical, seismic, logging and drilling data, the basic geological conditions, oil and gas distribution characteristics, reservoir-forming dynamics, and hydrocarbon accumulation model of the Paleogene whole petroleum system (WPS) in the western depression of the Qaidam Basin are systematically studied. A globally unique ultra-thick mountain-style WPS is found in the western depression of the Qaidam Basin. Around the source rocks of the upper member of the Paleogene Lower Ganchaigou Formation, the structural reservoir, lithological reservoir, shale oil and shale gas are laterally distributed in an orderly manner and vertically overlapped from the edge to the central part of the lake basin. The Paleogene WPS in the western depression of the Qaidam Basin is believed unique in three aspects. First, the source rocks with low organic matter abundance are characterized by low carbon and rich hydrogen, showing a strong hydrocarbon generating capacity per unit mass of organic carbon. Second, the saline lake basinal deposits are ultra-thick, with mixed deposits dominating the center of the depression, and strong vertical and lateral heterogeneity of lithofacies and storage spaces. Third, the strong transformation induced by strike-slip compression during the Himalayan resulted in the heterogeneous enrichment of oil and gas in the mountain-style WPS. As a result of the coordinated evolution of source-reservoir-caprock assemblage and conducting system, the Paleogene WPS has the characteristics of “whole process” hydrocarbon generation of source rocks which are low-carbon and hydrogen-rich, “whole depression” ultra-thick reservoir sedimentation, “all direction” hydrocarbon adjustment by strike-slip compressional fault, and “whole succession” distribution of conventional and unconventional oil and gas. Due to the severe Himalayan tectonic movement, the western depression of the Qaidam Basin evolved from depression to uplift. Shale oil is widely distributed in the central lacustrine basin. In the sedimentary system deeper than 2 000 m, oil and gas are continuous in the laminated limy-dolomites within the source rocks and the alga limestones neighboring the source kitchen, with intercrystalline pores, lamina fractures in dolomites and fault-dissolution bodies serving as the effective storage space. All these findings are helpful to supplement and expand the WPS theory in the continental lake basins in China, and provide theoretical guidance and technical support for oil and gas exploration in the Qaidam Basin.

Mehdi Fadaei, Mohammad Javad Ameri, Yousef Rafiei et al.

Abstract During oil production, the reservoir pressure declines, causing changes in the hydrocarbon components. To ensure better separation of produced phases, separator dimensions should also be adjusted. It is not possible to change the dimensions of the separator during production. Therefore, to improve the separation of the phases, the level of the separator needs to be adjusted. An intelligent system is required to ensure that the liquid level is maintained at the desired level for optimal phase separation during changes in reservoir pressure. In this study, a novel correlation is presented to measure the desired liquid level using new separator pressures. For this purpose, an intelligent system was built in the laboratory and tested in different operational conditions. The intelligent system effectively maintained the desired liquid level of the separator through a new correlation technique. The system accomplished this by acquiring new separator pressure readings collected by installed sensors. This approach helped mitigate the negative effects of the slug flow regime and minimized issues such as foam formation and over-flushing of the separator. It could achieve a 99.1% separation efficiency between gas and liquid phases. This was possible during liquid and gas flow rates ranging from 0 to 2.35 and 8–17 m3/h, respectively. The system could operate under bubble, stratified, plug, and slug flow regimes. Then the intelligent model obtained from lab experiments was integrated into the production model for the southern Iranian oil field. The smart model increased oil production by 13% and prevented the separator from over-flushing in 840 days.

Daniela Inclezan

This paper introduces a framework for assisting policy authors in refining and improving their policies. In particular, we focus on authorization and obligation policies that can be encoded in Gelfond and Lobo's AOPL language for policy specification. We propose a framework that detects the statements that make a policy inconsistent, underspecified, or ambiguous with respect to an action being executed in a given state. We also give attention to issues that arise at the intersection of authorization and obligation policies, for instance when the policy requires an unauthorized action to be executed. The framework is encoded in Answer Set Programming. Under consideration for acceptance in TPLP.

Antoine Gaulin, Brigitte Pientka

We develop an extension of the proof environment Beluga with datasort refinement types and study its impact on mechanized proofs. In particular, we introduce refinement schemas, which provide fine-grained classification for the structures of contexts and binders. Refinement schemas are helpful in concisely representing certain proofs that rely on relations between contexts. Our formulation of refinements combines the type checking and sort checking phases into one by viewing typing derivations as outputs of sorting derivations. This allows us to cleanly state and prove the conservativity of our extension.

Daniele Massaro, Valerio Lupi, Adam Peplinski et al.

In this work, we introduce the novel application of the adaptive mesh refinement (AMR) technique in the global stability analysis of incompressible flows. The design of an accurate mesh for transitional flows is crucial. Indeed, an inadequate resolution might introduce numerical noise that triggers premature transition. With AMR, we enable the design of three different and independent meshes for the non-linear base flow, the linear direct and adjoint solutions. Each of those is designed to reduce the truncation and quadrature errors for its respective solution, which are measured via the spectral error indicator. We provide details about the workflow and the refining procedure. The numerical framework is validated for the two-dimensional flow past a circular cylinder, computing a portion of the spectrum for the linearised direct and adjoint Navier-Stokes operators.

MENG Wenhui, ZHANG Wen, WANG Boyang et al.

The issue of coal fine production is increasingly prominent in the development of coal-bed methane. Implementing appropriate measures to control the migration and production of coal fines is crucial for achieving stable and high production of coal-bed methane wells. However, the characteristics of coal migration and production in the coal seams of Baode block remain unclear, which hinders the efficient development of coal-bed methane in some wells in this area. To address the problem of coal fine production in coal-bed methane development, core flooding experiments were conducted to investigate the migration and production characteristics of coal fines concerning influencing factors such as formation water velocity, salinity, gas-water ratio, effective stress, etc. The experimental results revealed that during the drainage stage, the amount of coal fines produced at low formation water flow is minimal, with coal fines moving within fractures and accumulating at the outlet, forming a coal powder filter cake. However, when formation water flow surpasses the critical flow, a significant amount of coal fines is produced. A substantial pressure fluctuation can flush out the coal fines obstructing the outlet. Furthermore, the salinity of the formation water plays a role in carrying coal powder, with higher salinity increasing its transport capacity. While single gas phase flow is not effective in displacing the coal fine migration and production, two-phase flow with a gas-water ratio of 50∶50 exhibits a stronger ability to carry coal powder. The concentration of coal fine in the produced liquid continued to decline with the increase of the effective stress loaded on the coal, Similarly, the holding pressure at the outlet follows a downward trend, but the displacement pressure difference increases. The research findings provide essential data and a theoretical basis for implementing on-site prevention and control of coal fine production.

Hanyuan Wang, Majid Mirmehdi, Dima Damen et al.

Current one-stage action detection methods, which simultaneously predict action boundaries and the corresponding class, do not estimate or use a measure of confidence in their boundary predictions, which can lead to inaccurate boundaries. We incorporate the estimation of boundary confidence into one-stage anchor-free detection, through an additional prediction head that predicts the refined boundaries with higher confidence. We obtain state-of-the-art performance on the challenging EPIC-KITCHENS-100 action detection as well as the standard THUMOS14 action detection benchmarks, and achieve improvement on the ActivityNet-1.3 benchmark.