Hasil untuk "Oils, fats, and waxes"

Li Fengfeng, Feng Zhou, Wu Hongliang et al.

We propose a mud-standoff effect correction method and a set of approximate apparent resistivity inversion methods suitable for oil-based mud micro-resistivity imaging logging. To calibrate the influence of the mud layer on electrode measurement signals, this study integrates the Open-Short calibration(OSC) method with the three-layer impedance model of the oil-based mud resistivity imager. By treating the electrode and the mud layer as an integrated whole and simulating the open/short-circuit states via the finite element method, the independent extraction of the mud layer impedance signal is achieved, and the formation impedance signal is separated from the total impedance. For fast inversion of formation resistivity, standoff thickness (mud layer thickness), and relative permittivity of formation, a resistivity consistency-constrained iterative inversion method is further proposed. In this method, the formation impedance is first converted into resistivity, and then the consistency residual of the resistivity at different frequencies is used as the objective function to invert the approximate apparent resistivity of the formation through an iterative optimization algorithm. The effectiveness of the finite element-simulated OSC method, the objective function construction scheme, and the consistency inversion method is verified through both numerical models and an example of field data.

WANG Zhouhua, ZHANG Hongyu, ZHANG Juan et al.

Gas-water relative permeability measurement is a common method to describe the flow process in gas reservoirs with water. However， the results of relative permeability measurements vary significantly between different test methods and types of cores. To deepen the understanding of the microscopic distribution characteristics of fluid and flow mechanism during the gas-water flow process， this paper took YB Gas Field in Sichuan Basin as the research object and used nuclear magnetic resonance （NMR） technology to quantitatively describe the microscopic distribution of the two phases before and after relative permeability test. The distribution results were explained based on the gas-water two-phase flow mechanism obtained by the previous researchers with the visualization model. The results showed that the displacement efficiencies of micron-scale （>1 μm） pores during the water displacing gas and gas displacing water are basically the same with the two test methods， but the displacement efficiency in submicron-scale （0.1–1 μm） and nanoscale （<0.1 μm） pores during water displacing gas is relatively higher. Moreover， the water in the submicron-scale and nanoscale pores is not mainly produced during the gas displacing water. For fractured and porous cores， the displacement efficiencies in micron-scale pores of fractured cores are relatively low， while the displacement efficiencies in submicron-scale and nanoscale pores are relatively high. The difference in the microscopic distribution of fluids with the two test methods is mainly caused by the different capillary forces inside the pores， while the difference between the two types of cores is primarily due to the difference in their main flow channels.

Luis Fernando Lozano, Furtado Frederico, De Souza Aparecido et al.

This work presents the Riemann solution for three-phase flow in porous media under the condition that oil viscosity exceeds that of water and gas. We classify all Riemann solution problems for scenarios where the left states $L$ lie along the edge $G$-$W$, and the right states $R$ span nearly the entire saturation triangle, excluding small regions near the boundaries $G$-$O$ and $W$-$O$. We use the wave curve method to determine the Riemann solution for initial and injection data within the above-mentioned class. This study extends previous analytical solutions, which were limited to right states near the corner $O$ or within the quadrilateral $O$-$E$-$\mathcal{U}$-$D$. Notably, this classification remains valid for all viscosity variations satisfying the inequalities \eqref{eq:classical}, corresponding to viscosity regimes where the umbilic point is close to the vertex $O$. We verify the $L^1_{loc}$-stability of the Riemann solution with respect to variations in the data. While we do not establish the uniqueness of the Riemann solution, extensive numerical experiments confirm its validity. Our findings provide a comprehensive framework for understanding three-phase flow dynamics in porous media under a wide range of conditions.

Luca Vincenzo Ballestra, Christian Tezza

We present a new model for commodity pricing that enhances accuracy by integrating four distinct risk factors: spot price, stochastic volatility, convenience yield, and stochastic interest rates. While the influence of these four variables on commodity futures prices is well recognized, their combined effect has not been addressed in the existing literature. We fill this gap by proposing a model that effectively captures key stylized facts including a dynamic correlation structure and time-varying risk premiums. Using a Kalman filter-based framework, we achieve simultaneous estimation of parameters while filtering state variables through the joint term structure of futures prices and bond yields. We perform an empirical analysis focusing on crude oil futures, where we benchmark our model against established approaches. The results demonstrate that the proposed four-factor model effectively captures the complexities of futures term structures and outperforms existing models.

Eghbal Motaei, Tarek Ganat, Khairul Azhar et al.

This paper provides a comprehensive overview of Deep Transient Testing (DTT), a cutting-edge technique for reservoir characterization that has revolutionized the oil and gas industry. The main aim of DTT is to characterize the reservoir with a deeper radius of investigation. The optimization of the radius of investigation with the DTT approach is studied in detail. Reveal is a commercial numerical simulation application used to simulate the DTT process and evaluate the pressure wave analysis in the porous media. The main aim of the simulation is to understand the impact of the reservoir quality on the pressure response and use it to address the noise-to-pule ratio, which is a determinantal parameter in testing duration. The tested wells with the DTT tool show that measured well productivity can deliver the minimum commercial rate. The has been delivered within 2 days compared to the potential test time of 21 days which saved the 19 rig days and contributed to CO2 emission reduction of (gas flaring 1340 + rig emission 600) 1940 Metric tons equivalent to 421 cars emission in a year. However, DTT also presents certain limitations, such as the requirement for specialized equipment and expertise, as well as the potential for formation damage during testing. This study provides a detailed description of the DTT technique, encompassing its history, theory, and practical applications. Furthermore, it discusses the benefits and limitations of DTT and presents case studies to illustrate its effectiveness across various reservoir types. Overall, this study serves as a valuable resource for reservoir engineers, geologists, and other professionals involved in the exploration and production of oil and gas.

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.

Mudiaga Chukunedum Onojake, Nsikan Edet Nkanta, Joseph Onyekwelu Osakwe et al.

Abstract Geochemical and biomarker characteristics of representative crude oil samples from selected fields in southern Nigeria were evaluated to determine the organic matter input, origin of biological material, depositional environment, thermal maturity, and genetic relationship between the oils. Four crude oil samples were obtained from various oil producing fields from Delta, Bayelsa and Abia state in southern Nigeria and labeled Kwale (KW), Kolo creek (KLC), Owaza (OWA1 and OWA2). The crude oil samples were fractionated into saturates, aromatic hydrocarbons and polar compounds using column chromatography on silica gel thereafter, analyzed using Gas chromatography-mass spectrometry (GC–MS). The calculated ratios of normal alkanes, acyclic isoprenoids, carbon preference index (CPI), hopanes, and steranes showed the following results: Pr/Ph (0.34 to 0.89); C29/C27 (0.78 to 1.25); 20S/(20S + 20R)C29sterane (0.28 to 0.66); 22S/(22S + 22R)C32 homohopane (0.17 to 0.23); CPI (0.96 to 0.98); Ts/Ts + Tm (0.46 to 0.50); and sterane/hopane (0.16 to 0.87). The results obtained were used to correlate the crude oils with respect to depositional environment, thermal maturity, and organic matter source. The Pr/Ph ratios of KW and KLC were less than one, and the cross-plot of Pr/nC17 versus Ph/nC18 of KW and KLC suggested that the oils were deposited under anoxic environments, whereas OWA1 and OWA2 indicated oxic conditions with no biodegradation. From the calculated ratios of 22S (22S + 22R)C32 homohopane and CPI, the oils were mature and had entered the generating window. Sample OWA1 is the most mature, while KLC is the least mature. The calculated ratios also showed that the four oil samples were from a shale source rock with both terrestrial and marine inputs.

A. Sen, S. Mandal, S. Chatterjee et al.

Resistive Plate Chamber (RPC) is one of the most commonly used detectors in high energy physics experiments for triggering and tracking because of its good efficiency ($\textgreater$~90\%) and time resolution ($\sim$~1-2~ns). Generally, bakelite which is one of the most commonly used materials as electrode plates in RPC, sometimes suffers from surface roughness issues. If the surface is not smooth, the probability of micro discharges and spurious pulses increase, which leads to the deterioration in the performance of the detector. We have developed a new method of linseed oil coating for the bakelite based detectors to avoid the surface roughness issue. The detector is characterised with Tetrafluoroethane (R134a) based gas mixture. The detector is also tested with a high rate of gamma radiation environment in the laboratory for the radiation hardness test. The detailed measurement procedure and test results are presented in this article.

Somasekhara Goud Sontti, Xuehua Zhang

Pipeline transportation is a vital method for conveying crushed oil sand ores and tailings in the oil sands industry. This study focuses on enhancing economic benefits by exploring the separation of valuable bitumen residues from coarse sand tailings within hydrotransport pipelines. Employing three-dimensional transient Eulerian-Eulerian computational fluid dynamics (CFD) simulations coupled with a population balance model (PBM), we examine the aggregation and breakage of bitumen droplets under various flow conditions. The CFD-PBM model's accuracy is validated against field measurements of velocity profiles and pressure drops. Our findings reveal that higher slurry velocities lead to intensified particle-bitumen interactions, resulting in reduced aggregated bitumen droplet sizes at the pipeline's core. Additionally, variations in bitumen fraction cause shifts in the distribution of coarse particles along the pipe's vertical axis, with increased aggregation and larger droplets in the upper region. Notably, we demonstrate that smaller bubbles promote a more uniform distribution of bitumen compared to larger bubbles. These insights provide valuable knowledge for optimizing bitumen recovery processes, facilitating the integration of pipeline dynamics with downstream separation and extraction units.

Muhammad Salman Ali, Maryam Qamar, Sung-Ho Bae et al.

In recent times, the utilization of 3D models has gained traction, owing to the capacity for end-to-end training initially offered by Neural Radiance Fields and more recently by 3D Gaussian Splatting (3DGS) models. The latter holds a significant advantage by inherently easing rapid convergence during training and offering extensive editability. However, despite rapid advancements, the literature still lives in its infancy regarding the scalability of these models. In this study, we take some initial steps in addressing this gap, showing an approach that enables both the memory and computational scalability of such models. Specifically, we propose "Trimming the fat", a post-hoc gradient-informed iterative pruning technique to eliminate redundant information encoded in the model. Our experimental findings on widely acknowledged benchmarks attest to the effectiveness of our approach, revealing that up to 75% of the Gaussians can be removed while maintaining or even improving upon baseline performance. Our approach achieves around 50$\times$ compression while preserving performance similar to the baseline model, and is able to speed-up computation up to 600 FPS.

S. Leardini, A. Sáa-Hernández, M. Kuźniak et al.

The idea of implementing electroluminescence-based amplification through transparent multi-hole structures (FAT-GEMs) has been entertained for some time. Arguably, for such a technology to be attractive it should perform at least at a level comparable to conventional alternatives based on wires or meshes. We present now a detailed calorimetric study carried out for 5.9~keV X-rays in xenon, for pressures ranging from 2 to 10~bar, resorting to different geometries, production and post-processing techniques. At a reference voltage 5~times above the electroluminescence threshold ($E_{EL,th}\sim0.7$~kV/cm/bar), the number of photoelectrons measured for the best structure was found to be just 18\%~below that obtained for a double-mesh with the same thickness and at the same distance. The energy resolution stayed within 10\% (relative) of the double-mesh value. An innovative characteristic of the structure is that vacuum ultraviolet (VUV) transparency of the polymethyl methacrylate (PMMA) substrate was achieved, effectively, through tetraphenylbutadiene (TPB) coating of the electroluminescence channels combined with indium tin oxide (ITO) coating of the electrodes. This resulted in a $\times 2.25$-increased optical yield (compared to the bare structure), that was found to be in good agreement with simulations if assuming a TPB wavelength-shifting-efficiency at the level of WLSE=0.74-1.28, compatible with expected values. This result, combined with the stability demonstrated for the TPB coating under electric field (over 20~h of continuous operation), shows great potential to revolutionize electroluminescence-based instrumentation.

Eamon Duede, William Dolan, André Bauer et al.

This study empirically investigates claims of the increasing ubiquity of artificial intelligence (AI) within roughly 80 million research publications across 20 diverse scientific fields, by examining the change in scholarly engagement with AI from 1985 through 2022. We observe exponential growth, with AI-engaged publications increasing approximately thirteenfold (13x) across all fields, suggesting a dramatic shift from niche to mainstream. Moreover, we provide the first empirical examination of the distribution of AI-engaged publications across publication venues within individual fields, with results that reveal a broadening of AI engagement within disciplines. While this broadening engagement suggests a move toward greater disciplinary integration in every field, increased ubiquity is associated with a semantic tension between AI-engaged research and more traditional disciplinary research. Through an analysis of tens of millions of document embeddings, we observe a complex interplay between AI-engaged and non-AI-engaged research within and across fields, suggesting that increasing ubiquity is something of an oil-and-water phenomenon -- AI-engaged work is spreading out over fields, but not mixing well with non-AI-engaged work.

WEN Rou, LI Dong, HUANG Ke et al.

The wave field data which is monitored the fracturing crack by micro seismic in the well is complex, especially when the shear wave (S-wave) encounters the fracture. The shear wave will split into the fast or slow wave. The polarization directions of the two kinds waves are perpendicular to each other. The identification of the shear wave field, the longitudinal wave (P-wave) field and fast or slow wave field, will directly affect the accuracy of the interpretation results. In order to improve the accuracy of interpretation results of microseismic data in wells, the wave field characteristics of waves in three-component geophone are analyzed according to the relationship between different incidence angles and the three components of the geophone, and it is concluded that the inversion results of the S-wave splitting event will cause fracture interpretation errors. Taking the micro-seismic fracture monitoring data of the Xinping XX well as an example, collect the micro-seismic records data of the P-wave, S-wave and fast/slow shear waves separately. Using the travel time inversion positioning algorithm of the first break collecting of the P/S waves, complete the micro-seismic positioning inversion of the P-wave+S-wave, fast S-wave +slow S-wave, P-wave+fast S-wave+slow S-wave fields. Through comparison, it is found that the orientation and distance of microseismic event localization results using only P-wave and S-wave are more reliable, and the fracture morphology is more consistent with the fracture growth law. At the same time, the influence of fast and slow S-wave on microseismic localization inversion results is fully explained.

毛逸霖1，周俊1，陈凯2，汪勇1，张震1 MAO Yilin1，ZHOU Jun1，CHEN Kai2，WANG Yong1，ZHANG Zhen1

油脂是人体主要的三大营养素之一，合理膳食油脂对人体供能、提升免疫功能、维持神经和生理活性提供了保障。甘油三酯（TAG）作为食用油脂主要成分，在消化代谢后容易转化为储能脂肪，使机体负担较大。甘油二酯（DAG）是一种天然TAG替代脂，被证明具有多种营养功能。旨在为DAG作为新型健康油脂的应用提供理论基础，综述了DAG的代谢机制以及DAG主要的营养功能。DAG具有和TAG相似的理化性质，由于代谢途径与TAG的差异以及可以调控与脂肪氧化相关基因的表达，使DAG具有促进脂肪氧化、抑制体质量增加、降低内脏脂肪含量、改善血清胆固醇、调节血糖、降低血脂等多种功能。DAG的摄入可有效降低代谢综合征和心血管疾病发生的风险。Oils and fats are one of the three main nutrients in the human body. A balanced diet of oils and fats provide energy to the body, enhance immune function, and maintain neurological and physiological activities. Triacylglycerol (TAG), the main component of edible oils and fats, is easily converted into stored fat after digestion and metabolism, which can burden the body. Diacylglycerol (DAG) is a natural substitute for TAG in edible oil and has been proven to have various nutritional functions. To provide a theoretical basis for the application of DAG as a new type of healthy fat, the metabolic mechanism and main nutritional functions of DAG were reviewed. DAG has similar physicochemical properties to TAG, but due to differences in metabolic pathways and the ability to regulate the expression of genes related to oil oxidation, DAG has multiple functions such as promoting fat oxidation, inhibiting body weight gain, reducing visceral fat content, improving serum cholesterol, regulating blood sugar, and lowering blood lipids. The intake of DAG can effectively reduce the risk of metabolic syndrome and cardiovascular disease.

Xiuli Zhu, Seshu Kumar Damarla, Biao Huang

Minimum miscibility pressure (MMP) prediction plays an important role in design and operation of nitrogen based enhanced oil recovery processes. In this work, a comparative study of statistical and machine learning methods used for MMP estimation is carried out. Most of the predictive models developed in this study exhibited superior performance over correlation and predictive models reported in literature.

Satish Kumar, Rui Kou, Henry Hill et al.

From agriculture to mining, to energy, surface water quality monitoring is an essential task. As oil and gas operators work to reduce the consumption of freshwater, it is increasingly important to actively manage fresh and non-fresh water resources over the long term. For large-scale monitoring, manual sampling at many sites has become too time-consuming and unsustainable, given the sheer number of dispersed ponds, small lakes, playas, and wetlands over a large area. Therefore, satellite-based environmental monitoring presents great potential. Many existing satellite-based monitoring studies utilize index-based methods to monitor large water bodies such as rivers and oceans. However, these existing methods fail when monitoring small ponds-the reflectance signal received from small water bodies is too weak to detect. To address this challenge, we propose a new Water Quality Enhanced Index (WQEI) Model, which is designed to enable users to determine contamination levels in water bodies with weak reflectance patterns. Our results show that 1) WQEI is a good indicator of water turbidity validated with 1200 water samples measured in the laboratory, and 2) by applying our method to commonly available satellite data (e.g. LandSat8), one can achieve high accuracy water quality monitoring efficiently in large regions. This provides a tool for operators to optimize the quality of water stored within surface storage ponds and increasing the readiness and availability of non-fresh water.

Wei Liu, Jing Li, Zixiang Chen et al.

We explore the potential to use machine learning methods to search for heavy neutrinos, from their hadronic final states including a fat-jet signal, via the processes $pp \rightarrow W^{\pm *}\rightarrow μ^{\pm} N \rightarrow μ^{\pm} μ^{\mp} W^{\pm} \rightarrow μ^{\pm} μ^{\mp} J$ at hadron colliders. We use either the Gradient Boosted Decision Tree or Multi-Layer Perceptron methods to analyse the observables incorporating the jet substructure information, which is performed at hadron colliders with $\sqrt{s}=$ 13, 27, 100 TeV. It is found that, among the observables, the invariant masses of variable system and the observables from the leptons are the most powerful ones to distinguish the signal from the background. With the help of machine learning techniques, the limits on the active-sterile mixing have been improved by about one magnitude comparing to the cut-based analyses, with $V_{μN}^2 \lesssim 10^{-4}$ for the heavy neutrinos with masses, 100 GeV$~<m_N<~$1 TeV.

Meisin Lee, Lay-Ki Soon, Eu-Gene Siew et al.

In this paper, we present CrudeOilNews, a corpus of English Crude Oil news for event extraction. It is the first of its kind for Commodity News and serve to contribute towards resource building for economic and financial text mining. This paper describes the data collection process, the annotation methodology and the event typology used in producing the corpus. Firstly, a seed set of 175 news articles were manually annotated, of which a subset of 25 news were used as the adjudicated reference test set for inter-annotator and system evaluation. Agreement was generally substantial and annotator performance was adequate, indicating that the annotation scheme produces consistent event annotations of high quality. Subsequently the dataset is expanded through (1) data augmentation and (2) Human-in-the-loop active learning. The resulting corpus has 425 news articles with approximately 11k events annotated. As part of active learning process, the corpus was used to train basic event extraction models for machine labeling, the resulting models also serve as a validation or as a pilot study demonstrating the use of the corpus in machine learning purposes. The annotated corpus is made available for academic research purpose at https://github.com/meisin/CrudeOilNews-Corpus.

Luo Yi, Huang Zhongwei, Shi Huaizhong et al.

Conventional hydraulic fracturing technology faces problems such as high fracture initiation pressure and difficult packer setting in the stimulation of hot dry rock reservoirs. Supercritical nitrogen jet fracturing technology uses fluid pressure energy to coact with cold shock and is expected to achieve effective fracturing of hot dry rock reservoirs. In order to study the distribution law of supercritical nitrogen jet flow field, with the help of computational fluid mechanics method, after having considered the physical property variation of supercritical nitrogen, this paper figured out the velocity and pressure and temperature distribution of supercritical nitrogen jet flow field, conducted comparative analysis with liquid nitrogen jet, supercritical CO₂ jet and water jet flow fields, and simultaneously studied the flow field characteristics of supercritical nitrogen jet at different drawdowns, confining pressures and inlet temperatures. The study results show that compared with the other three jets, the supercritical nitrogen jet has the largest nozzle exit velocity and the longest potential core of jet; as the nozzle pressure drawdown increases and the supercritical nitrogen inlet temperature rises, the outlet velocity of fluid increases rapidly and the length of potential core increases; and the confining pressure has little effect on nozzle exit velocity, but the increase of confining pressure would lead to the decrease of potential core length. The study results provide theoretical guidance for the design of supercritical nitrogen jet fracturing stimulation parameters.

Sabine Krist