Hasil untuk "Petroleum refining. Petroleum products"

Du Anqi, Wen Ming, Dong Zonghao et al.

Downhole throttling technology is an efficient means of hydrate prevention and control. How to establish an effective throttling pressure difference in a reasonable time to ensure that the wellhead pressure and temperature are quickly reduced to a safe range has become the key to the successful implementation of downhole throttling technology. To address this issue， the OLGA transient multiphase flow simulator was used to conduct dynamic simulation on the pressure， temperature and production during flowing of gas wells. Then， the flow and heat transfer characteristics in the wellbore under different choke diameters and flowing production conditions were analyzed， and the risk of hydrate formation was predicted. The research results show that the choke diameter significantly affects the time required for the wellhead pressure to decline to the delivery pressure and the stable production rate. Smaller choke diameter （e.g. 4.3 mm） increases the downhole flow resistance， accelerates the decline of wellhead pressure， but limits the stable production rate. Larger choke diameters （e.g. 5.4 mm and 6.0 mm） prolong the pressure decline time， but can achieve higher stable production rates in long-term production. Under the conditions of downhole throttle valve with small choke diameter and high flowing production rate， the post-valve temperature recovers fast， and the risk of freezing blockage is low. However， under the conditions of downhole throttle valve with large choke diameter and low flowing production rate， the post-valve temperature remains below the hydrate formation temperature for a long time， and the risk of freezing blockage increases significantly. In actual production， it is recommended to comprehensively consider surface processing capacity， gas reservoir development requirements and safe production demands to formulate the optimal downhole throttling scheme. The research results provide a scientific basis for the design and optimization of downhole throttling technology in high-pressure gas wells.

C. Ananna, F. B. Armani, G. Cataldi et al.

The SABRE North experiment is developing ultra-high radiopurity NaI(Tl) detectors to investigate dark matter. To achieve this, SABRE North utilizes the technique called zone refining for NaI powder purification. This work details the mathematical model developed to describe the purification process. By comparing this model to the results of the commissioning and production runs conducted prior to crystal growth, the distribution coefficients were determined for various impurities, contained in the powder at the parts-per-billion (ppb) level. Furthermore, the synthesis of data from both zone refining and normal freezing is discussed. These findings can be used to predict the SABRE North detectors background level in the energy region-of-interest for dark matter search and to optimize the production of ultra-high purity crystals through multiple purification strategies.

Eldar Hacohen, Yuval Moskovitch, Amit Somech

Numerous studies have explored the SQL query refinement problem, where the objective is to minimally modify an input query so that it satisfies a specified set of constraints. However, these works typically target restricted classes of queries or constraints. We present OmniTune, a general framework for refining arbitrary SQL queries using LLM-based optimization by prompting (OPRO). OmniTune employs a two-step OPRO scheme that explores promising refinement subspaces and samples candidates within them, supported by concise history and skyline summaries for effective feedback. Experiments on a comprehensive benchmark demonstrate that OmniTune handles both previously studied refinement tasks and more complex scenarios beyond the scope of existing solutions.

Tianxin Tao, Han Liu, Hung Yu Ling

High-quality motion data underpins games, film, XR, and robotics. Vision-based motion capture tools have made significant progress, offering accessible and visually convincing results, yet often fall short in the final stretch -- the last mile -- when it comes to physical realism and production readiness, due to various artifacts introduced during capture. In this paper, we summarize key issues through case studies and feedback from professional animators to set a stepping stone for future research in motion cleanup. We then present a physics-based motion refinement framework to bridge the gap, with the goal of reducing labor-intensive manual cleanup and enhancing visual quality and physical realism. Our framework supports both single- and multi-character sequences and can be integrated into animator workflows for further refinement, such as stylizing motions via keyframe editing.

Wang Yufeng

To reduce uncertainties in bit design and improvement effectiveness， while also lowering workload of designer and enhancing design efficiency of bit， a bit force balance verification software was developed using NXOPEN and UFun mixed programming techniques. Using the area， arc length and volume measurement functions built in UG to replace complex trajectory equation calculations， and integrating the special-shaped cutter replacement function， this software significantly reduced the computational complexity in the process of bit force balance verification， and effectively solved the problem of slow drawing speed in the design of special-shaped cutter bit. Two bits with different core lifespans were designed for different thicknesses of glutenite， and both they demonstrated excellent performance under applicable conditions. Through numerical comparison and analysis of cutting force and cutting volume at core location during bit design， the reasons for the difference in bit life were well explained. The application effect of the two bits verified the design process determinacy of the software and the necessity of the software development. The research results provide reference for the design of bit.

Zehua Chen, Wenjian Yue, Chengwen Wang

The incorporation of fibers represents a crucial technique for improving the mechanical properties and other relevant characteristics of cement-based composites (CBC), including concrete, cement mortar, and oil-well cement. Especially, carbon fiber (CF) has a great potential for reinforcing oil-well cement due to its high strength, modulus, stiffness, high temperature, corrosion and fatigue resistance as well as chemical stability. There is a huge amount of waste CFs all over the world which show better performance in cement industry, while their reuse will realize waste recovery (good environment impact) and greatly reduce cost. This review paper presents the recent progress of using CF in enhancing mechanical properties of CBC. We put high emphasis on the CF surface modification for reinforcing bond strength at the cement/CF interface. Comprehensive discussion with respect to effects of CF and modified CF on CBC properties is performed. The key properties of CBC examined in this study encompass mechanical characteristics (compressive strength, flexural strength, and tensile strength), dimensional stability (shrinkage behavior), durability indicators (water absorption and permeability), and fracture-related properties (toughness, crack resistance, and impact performance). Thus, suggestions are given for the future study and application of CF in oil-well cement.

Kentaro Kasai, Masahiro Kawasaki, Kai Murai

The existence of a large primordial neutrino asymmetry is an intriguing possibility, both observationally and theoretically. Such an asymmetry can lead to the resonant production of $\mathrm{keV}$-scale sterile neutrinos, which are a fascinating candidate for dark matter. In this paper, we comprehensively revisit the resonant production processes with a refined numerical analysis, adopting a dynamical discretization of momentum modes to take care of the sharpness of the resonance. We find parameter regions consistent with X-ray and Lyman-$α$ constraints for lepton-to-entropy ratio $\gtrsim \mathcal{O}(10^{-3})$ and $m_{ν_s}\gtrsim 20\,$keV. We also explore the Affleck-Dine mechanism as a possible origin for such asymmetries. While previous studies considered resonant production after lepton number generation, we numerically investigate cases where a fraction of sterile neutrinos is produced during lepton number injection. In this regime, some parameter sets can shorten the free-streaming length and reduce the required mixing angle to match the observed dark matter abundance, thereby mitigating the observational constraints.

Soyeong Jeong, Aparna Elangovan, Emine Yilmaz et al.

Large Language Models (LLMs) have demonstrated remarkable success in conversational systems by generating human-like responses. However, they can fall short, especially when required to account for personalization or specific knowledge. In real-life settings, it is impractical to rely on users to detect these errors and request a new response. One way to address this problem is to refine the response before returning it to the user. While existing approaches focus on refining responses within a single LLM, this method struggles to consider diverse aspects needed for effective conversations. In this work, we propose refining responses through a multi-agent framework, where each agent is assigned a specific role for each aspect. We focus on three key aspects crucial to conversational quality: factuality, personalization, and coherence. Each agent is responsible for reviewing and refining one of these aspects, and their feedback is then merged to improve the overall response. To enhance collaboration among them, we introduce a dynamic communication strategy. Instead of following a fixed sequence of agents, our approach adaptively selects and coordinates the most relevant agents based on the specific requirements of each query. We validate our framework on challenging conversational datasets, demonstrating that ours significantly outperforms relevant baselines, particularly in tasks involving knowledge or user's persona, or both.

WU Turong, CHEN Jinding, ZHANG Qun et al.

Nuclear magnetic resonance (NMR) imaging is an advanced technology for core-scale heterogeneity analysis. Affected by rock complexity and encoding technology, existing methods are not really effective. 2D/3D nuclear magnetic resonance technology based on gradient fields is easy to image but has a low signal-to-noise ratio. The traditional T2 method (frequency coding/phase coding) without gradient field is in low efficiency. This study proposes a tomography method based on constant gradient coded 1D T2 spectrum, which can achieve small imaging data volume, high signal-to-noise ratio and more complete signal. Tomographic T2 spectrum images and their heat distribution can effectively characterize the effects of capillary force and diagenesis on the non-uniform distribution of fluids. In the oil-saturated state, the difference between T2 spectrum layers reflects the influence of diagenesis. The heat change of the image in the high saturation stage mainly reflects the displace pattern of low capillary force controlled free oil. After complete displacement, the capillary force enters a stable state, and the axial heat reflects the difference of micro-pore content that filled with adsorbed oil. The new technology has achieved good results in gas displacement experiments of cemented sandstone, and is expected to play an important role in the analysis of seepage laws of strong heterogeneous rocks.

Manya Wadhwa, Xinyu Zhao, Junyi Jessy Li et al.

Recent work has explored the capability of large language models (LLMs) to identify and correct errors in LLM-generated responses. These refinement approaches frequently evaluate what sizes of models are able to do refinement for what problems, but less attention is paid to what effective feedback for refinement looks like. In this work, we propose looking at refinement with feedback as a composition of three distinct LLM competencies: (1) detection of bad generations; (2) fine-grained natural language critique generation; (3) refining with fine-grained feedback. The first step can be implemented with a high-performing discriminative model and steps 2 and 3 can be implemented either via prompted or fine-tuned LLMs. A key property of the proposed Detect, Critique, Refine ("DCR") method is that the step 2 critique model can give fine-grained feedback about errors, made possible by offloading the discrimination to a separate model in step 1. We show that models of different capabilities benefit from refining with DCR on the task of improving factual consistency of document grounded summaries. Overall, DCR consistently outperforms existing end-to-end refinement approaches and current trained models not fine-tuned for factuality critiquing.

Guoqiang LIU, Renbin GONG, Yujiang SHI et al.

Based on the well logging knowledge graph of hydrocarbon-bearing formation (HBF), a Knowledge-Powered Neural Network Formation Evaluation model (KPNFE) has been proposed. It has the following functions: (1) extracting characteristic parameters describing HBF in multiple dimensions and multiple scales; (2) showing the characteristic parameter-related entities, relationships, and attributes as vectors via graph embedding technique; (3) intelligently identifying HBF; (4) seamlessly integrating expertise into the intelligent computing to establish the assessment system and ranking algorithm for potential pay recommendation. Taking 547 wells encountered the low porosity and low permeability Chang 6 Member of Triassic in the Jiyuan Block of Ordos Basin, NW China as objects, 80% of the wells were randomly selected as the training dataset and the remainder as the validation dataset. The KPNFE prediction results on the validation dataset had a coincidence rate of 94.43% with the expert interpretation results and a coincidence rate of 84.38% for all the oil testing layers, which is 13 percentage points higher in accuracy and over 100 times faster than the primary conventional interpretation. In addition, a number of potential pays likely to produce industrial oil were recommended. The KPNFE model effectively inherits, carries forward and improves the expert knowledge, nicely solving the robustness problem in HBF identification. The KPNFE, with good interpretability and high accuracy of computation results, is a powerful technical means for efficient and high-quality well logging re-evaluation of old wells in mature oilfields.

Jianbin TENG, Longwei QIU, Shoupeng ZHANG et al.

The origin of dolomite in Shahejie Formation shale of Jiyang Depression in eastern China were studied by means of petrologic identification, compositional analysis by X-ray diffraction, stable carbon and oxygen isotopic composition, and trace element and rare earth element analyses. The results show that the development of dolomite is limited in the lacustrine organic rich shale of Shahejie Formation in the study area. Three kinds of dolomite minerals can be identified: primary dolomite (D1), penecontemporaneous dolomite (D2), and ankerite (Ak). D1 has the structure of primary spherical dolomite, high magnesium and high calcium, with order degree of 0.3-0.5, and is characterized by the intracrystalline corrosion and coexistence of secondary enlargement along the outer edge. D2 has the characteristics of secondary enlargement, order degree of 0.5-0.7, high magnesium, high calcium and containing a little iron and manganese elements. Ak is characterized by high order degree of 0.7-0.9, rhombic crystal, high magnesium, high calcium and high iron. The micritic calcite belongs to primary origin on the basis of the carbon and oxygen isotopic compositions and the fractionation characteristics of rare earth elements. According to the oxygen isotopic fractionation equation between paragenetic dolomite and calcite, it is calculated that the formation temperature of dolomite in the shale is between 36.76-45.83 °C, belonging to lacustrine low-temperature dolomite. Based on the maturation and growth mechanism of primary and penecontemporaneous dolomite crystals, a dolomite diagenetic sequence and the dolomitization process are proposed, which is corresponding to the diagenetic environment of Shahejie Formation shale in the study area.

Anders T. Sandnes, Bjarne Grimstad, Odd Kolbjørnsen

Virtual flow metering (VFM) is a cost-effective and non-intrusive technology for inferring multiphase flow rates in petroleum assets. Inferences about flow rates are fundamental to decision support systems that operators extensively rely on. Data-driven VFM, where mechanistic models are replaced with machine learning models, has recently gained attention due to its promise of lower maintenance costs. While excellent performances in small sample studies have been reported in the literature, there is still considerable doubt about the robustness of data-driven VFM. In this paper, we propose a new multi-task learning (MTL) architecture for data-driven VFM. Our method differs from previous methods in that it enables learning across oil and gas wells. We study the method by modeling 55 wells from four petroleum assets and compare the results with two single-task baseline models. Our findings show that MTL improves robustness over single-task methods, without sacrificing performance. MTL yields a 25-50% error reduction on average for the assets where single-task architectures are struggling.

Gerardo Berbeglia, Alvaro Flores, Guillermo Gallego

We introduce the refined assortment optimization problem where a firm may decide to make some of its products harder to get instead of making them unavailable as in the traditional assortment optimization problem. Airlines, for example, offer fares with severe restrictions rather than making them unavailable. This is a more subtle way of handling the trade-off between demand induction and demand cannibalization. For the latent class MNL model, a firm that engages in refined assortment optimization can make up to $\min(n,m)$ times more than one that insists on traditional assortment optimization, where $n$ is the number of products and $m$ the number of customer types. Surprisingly, the revenue-ordered assortment heuristic has the same performance guarantees relative to {\em personalized} refined assortment optimization as it does to traditional assortment optimization. Based on this finding, we construct refinements of the revenue-order heuristic and measure their improved performance relative to the revenue-ordered assortment and the optimal traditional assortment optimization problem. We also provide tight bounds on the ratio of the expected revenues for the refined versus the traditional assortment optimization for some well known discrete choice models.

E. Saifullin, K. Sadikov, M. Varfolomeev et al.

Petroleum coke is one of the waste products generated in the oil refining industry that can be used as fuel in energetics. However, the low volatile matter content and graphite-like structure of petroleum coke are the reasons for its high ignition temperature and combustion complexity. In this research, petroleum coke combustion and oxidation kinetics in the presence of metal catalysts were investigated. To evaluate the effect of the catalyst on the ignition temperature and the apparent activation energy, a new approach of a “fixed fluidized bed” was proposed. In this mode, petroleum coke particles spaced from each other by inert quartz powder kind of “freeze” in the porous layer. This regime allows us to determine the ignition temperature of petroleum coke particles in the static mode by differential thermography and calculate the activation energy by gas analysis. Organic and inorganic salts of copper, iron, and cerium are used as catalysts for petroleum coke combustion. A series of experiments were carried out in the porous media thermo-effect cell (PMTEC) and on a thermogravimetric (TG) analyzer. The kinetics of the combustion processes was calculated by Kissinger–Akahira–Sunose and Ozawa–Flynn–Wall methods. The results obtained in the “fixed bed” mode showed that the ignition temperature and the average apparent activation energy significantly decreased in the presence of CuCl2 and FeCl3. The results obtained by the new approach were compared with the results of the thermogravimetric analysis.

V. Chelyadyn, Mykola Bogoslavets, L. Chelyadyn et al.

The article presents the quantitative characteristics of multi-tonnage technogenic wastes in Ukraine and the IvanoFrankivsk region, which cause environmental pollution. The water silts containing petroleum products are particularly dangerous wastes. It is proposed to recycle them using the method of preparation of the raw mixture in composition with the following technogenic wastes: oil sludge, ash, zeolite material, calcium-containing compounds, and organic mineral binders. They are granulated and subjected to the thermal treatment at low temperatures. The granular materials made using the oil-containing silt of the model object reduce the negative impact onto the environment of the region and increase its level of environmental safety.

N. Norouzi, Saeed Talebi, M. Giulia Fabi et al.

In this study, heat oil conversion experiments using steam and formic acid as a hydrogen carrier be carried out in a batch reactor at T = 380 degrees of Celsius and P = 165 bar. Material balance and product distribution were calculated after the process. Properties of crude oil before and after thermal conversion, including viscosity, API gravity, SARA measurement, and elemental analysis, were analyzed. It has been presented that the use of formic acid as a hydrogen carrier solvent reduces the formation of coke and gaseous products and enhances the performance of liquid products. Also, the viscosity of the refined oil decreased by 23.2% due to the addition of formic acid compared to the thermal conversion without hydrogen solvent. And also, a synthesis process is being implemented to provide the formic acid demand of the refining process sustainably. This process uses the carbon capture to contain CO2 for the direct green formic acid synthesis in the plant. Thus the oil produced by this process can be called green petroleum.

N. Koronatov, I. V. Il’in, S. Kalyazina

Aim . The presented study aims to develop a reference model of a system of processes for controlling the parameters of technological processes of installations involved in the production of commercial petroleum products. Tasks . The authors use specially designed mathematical models to select optimally configured parameters of technological processes based on the criterion of minimizing production costs; consider the need to supply final petroleum products in quantities determined by a system of contracts with customers; formulate the process landscape of an oil refinery and identify the main business processes. Methods . The methodological basis of this study includes the process approach, process management, decision-making theory, and optimization theory. The study uses information about the business processes of an oil refinery and the results of research on the development of specialized mathematical models for the predictive analytics of petroleum production. Results . The result of the study is a model of the system of basic business processes of an oil refinery, with a focus on the subsequent automation of processes based on the developed models. Conclusions . By constructing the process landscape and identifying the main business processes of an oil refinery, it is possible to build a reference model for the system of processes for controlling the parameters of technological processes involved in oil refining. Further research will focus on optimizing and automating this system of business processes.

N. Ngobiri

Kangxu Ren, Junfeng Zhao, Qian Liu et al.

Igneous rocks are widely developed in many hydrocarbon-bearing sedimentary basins in Brazil, and some igneous rocks play positive roles in the oil and gas accumulation process. But so far, no industrial oil or gas flow is discovered in igneous rocks in Brazilian onshore basins. At present, in some literatures published by some researchers, cases of igneous reservoirs in Brazil are inaccurate. The lithology of reservoirs in the Igarape Cuia oil and gas field, the oil and gas field of Urucu and the Barra Bonita gasfield, were previously thought to be volcanic rocks, but now are clastic rocks according to studies, and the igneous rocks in these three oil and gas field can only be acted as indirect and direct cap rocks. Furthermore, igneous rock reservoirs in the Campos Basin and Santos Basin in the Brazilian offshore are briefly analyzed. The representative Badejo oilfield in the Campos Basin has igneous rock reservoirs dominated by basalts which are intercalated with thin layers of volcaniclastic and sedimentary rocks, the storage space are vesicules, fractures and vugular pores, and the porosity of hydrocarbon bearing interval basalt reservoirs ranges from 10% to 15%. In addition, for the Santos Basin, igneous rocks in this basin are dominated by basic rocks, some alkaline intrusive rocks develop good micro spaces, mainly crystal moldic pores, inter- and intra-crystal dissolution pores and fractures, better reservoir intervals are often concentrated such as at sections near to unconformity surfaces and can have porosity of 6%–9% or higher; local pre-salt igneous rock reservoirs in the Santos Basin have the necessary conditions for hydrocarbon accumulation and it will be a new target layer for hydrocarbon exploration.