Hasil untuk "Petroleum refining. Petroleum products"

Almaz Ermilov

This paper presents FormationEval, an open multiple-choice question benchmark for evaluating language models on petroleum geoscience and subsurface disciplines. The dataset contains 505 questions across seven domains including petrophysics, petroleum geology and reservoir engineering, derived from three authoritative sources using a reasoning model with detailed instructions and a concept-based approach that avoids verbatim copying of copyrighted text. Each question includes source metadata to support traceability and audit. The evaluation covers 72 models from major providers including OpenAI, Anthropic, Google, Meta and open-weight alternatives. The top performers achieve over 97% accuracy, with Gemini 3 Pro Preview reaching 99.8%, while tier and domain gaps persist. Among open-weight models, GLM-4.7 leads at 98.6%, with several DeepSeek, Llama, Qwen and Mistral models also exceeding 93%. The performance gap between open-weight and closed models is narrower than expected, with several lower-cost open-weight models exceeding 90% accuracy. Petrophysics emerges as the most challenging domain across all models, while smaller models show wider performance variance. Residual length bias in the dataset (correct answers tend to be longer) is documented along with bias mitigation strategies applied during construction. The benchmark, evaluation code and results are publicly available.

Mateus A. Fernandes, Michael M. Furlanetti, Eduardo Gildin et al.

Forecasting production reliably and anticipating changes in the behavior of rock-fluid systems are the main challenges in petroleum reservoir engineering. This project proposes to deal with this problem through a data-driven approach and using machine learning methods. The objective is to develop a methodology to forecast production parameters based on simple data as produced and injected volumes and, eventually, gauges located in wells, without depending on information from geological models, fluid properties or details of well completions and flow systems. Initially, we performed relevance analyses of the production and injection variables, as well as conditioning the data to suit the problem. As reservoir conditions change over time, concept drift is a priority concern and require special attention to those observation windows and the periodicity of retraining, which are also objects of study. For the production forecasts, we study supervised learning methods, such as those based on regressions and Neural Networks, to define the most suitable for our application in terms of performance and complexity. In a first step, we evaluate the methodology using synthetic data generated from the UNISIM III compositional simulation model. Next, we applied it to cases of real plays in the Brazilian pre-salt. The expected result is the design of a reliable predictor for reproducing reservoir dynamics, with rapid response, capability of dealing with practical difficulties such as restrictions in wells and processing units, and that can be used in actions to support reservoir management, including the anticipation of deleterious behaviors, optimization of production and injection parameters and the analysis of the effects of probabilistic events, aiming to maximize oil recovery.

Weinan Wang

This paper presents a new petroleum well logging method - electrical impedance logging for shaly sand reservoirs - through theoretical and petrophysical experimental research. Electrical impedance logging measures the electrical impedance of shaly sand reservoirs, extracts resistivity information from the real part, and uses it to determine the oil saturation of the reservoir quantitatively. The study shows that the resistivity, extracted from the real part of the electrical impedance in shaly sands, has characteristics similar to those of the pure sandstone formation resistivity and can be directly used in Archie's law for oil-bearing interpretation of reservoirs.

Caner Tanış

This study aims to introduce a new lifetime distribution, called the record-based transformed log-logistic distribution, to the literature. We obtain this distribution using a record-based transformation map based on the distributions of upper record values. We explore some mathematical properties of the suggested distribution, namely the quantile function, hazard function, moments, order statistics, and stochastic ordering. We discuss the point estimation via seven different methods such as maximum likelihood, least squares, weighted least squares, Anderson-Darling, Cramer-von Mises, maximum product spacings, and right tail Anderson Darling. Then, we perform a Monte Carlo simulation study to evaluate the performances of these estimators. Also, we present two practical data examples, reactor pump failure and petroleum rock data to compare the fits of the proposed distribution with its rivals. As a result of data analysis, we conclude that the best-fitted distribution is the record-based transmuted log-logistic distribution for reactor pump failure and petroleum rock data sets.

BI Caixia

The research and application of risk analysis and evaluation for underground gas storage facilities are critical due to their diverse equipment, complex process flows, and numerous risk factors. In particular, corrosion failure accidents in ground process pipelines at these facilities have become increasingly common in recent years. Effective and accurate analysis of the causes of these corrosion failures is essential for ensuring the safe operation of underground gas storage facilities. This article presents a risk assessment methodology that leverages data and knowledge fusion. The process begins with a statistical analysis of the corrosion failure data from ground process pipelines in underground gas storage facilities, from which a Bayesian corrosion prediction model is developed. This model serves as the foundation for analyzing the basic events that lead to corrosion failure in these pipelines. Subsequently, a knowledge model of corrosion failure is established, and a detailed analysis of corrosion causes is conducted using the fault tree specific to corrosion failure in ground process pipelines. The importance of each basic event within the fault tree is quantified through the structural importance coefficient assigned to each event. The analysis categorizes the influencing factors of corrosion failure into four main groups. A judgment matrix is then created to determine the relative weight values of these different influencing factors. This matrix is crucial for setting the weight factors in the fuzzy comprehensive evaluation, which ultimately determines the risk level of corrosion failure in ground process pipelines at underground gas storage facilities. By applying examples of corrosion risk assessments for ground process pipelines, this study provides a scientific basis for enhancing safety management and operational practices at underground gas storage facilities.

Maciej Paczuski

The chapter presents experimental data, published in numerous source materials and reviews, on the mutual solubility of water in hydrocarbons and hydrocarbons in water, relationship of water solubility in hydrocarbons depending on the structure of the organic compound molecule and the change of solubility as a function of temperature. Possibilities of water solubilization, dissolved and dispersed in hydrocarbons, their mixtures as well as fractions, and petroleum products were analyzed. With the help of turbidimetric measurements, surfactants and mixtures of surfactants with the highest water solubilization capacity in fuels were selected. Different methods of dewatering of distillate fractions, gasolines, and diesel fuels with the use of coalescing partitions were investigated. A number of barrier materials, methods of modifying the structure of the partition, and the hydrophilicity of glass fibers were tested, obtaining very good results in industrial applications.

Ruud Weijermars, Umair bin Waheed, Kanan Suleymanli

A key aim of this paper is to explore how our professional tasks as geoscientists and petroleum engineers can be completed more effectively making use of tools powered by Artificial Intelligence (AI), offered in commercial platforms now readily available to individual users. This paper intends to provide some guidance, but at the same time does not claim to be comprehensive or conclusive in any way. The paper presents a utility assessment from the research and teaching vantage points of two professors and one student, from geosciences and petroleum engineering departments. After a brief overview of the new technologies, some key questions raised include: How can one assess originality of class papers by students and research papers by their professors? How will the contribution of intelligent devices be acknowledged? Will the presentation of conference papers by author avatars be accepted by the organizing committee?

Yuanwei Qu, Baifan Zhou, Arild Waaler et al.

The petroleum industry is crucial for modern society, but the production process is complex and risky. During the production, accidents or failures, resulting from undesired production events, can cause severe environmental and economic damage. Previous studies have investigated machine learning (ML) methods for undesired event detection. However, the prediction of event probability in real-time was insufficiently addressed, which is essential since it is important to undertake early intervention when an event is expected to happen. This paper proposes two ML approaches, random forests and temporal convolutional networks, to detect undesired events in real-time. Results show that our approaches can effectively classify event types and predict the probability of their appearance, addressing the challenges uncovered in previous studies and providing a more effective solution for failure event management during the production.

Farouk I. Metwalli, Amir Ismail, M.S. Metwally et al.

The present study aims to integrate a large set of geological and geophysical data into a comprehensive model describing the depositional features of the Abu Madi/El Qar'a/Khilala gas fields. The model is based on the sequence stratigraphic framework of the Abu Madi Formation defined using cores, well logs, and time-migrated seismic data. Seismic trace attribute sections and relative acoustic impedance sections are also used. A possible depositional pattern for the main Level III is established, based on the lithological and petrophysical information derived from the seismic data analysis. The Abu Madi Formation can be regarded as a depositional sequence recording the progressive drowning of the incised valley. The sequence is bounded at the base by an erosional unconformity, created by a drop in the level of the Late Messinian Sea, and at the top by a drowning unconformity related to the Early Pliocene transgression. The bottom of Level II divides the Abu Madi sequence into two smaller sequences. In both sequences, gas-bearing traps can be found in the Lowstand Systems Tracts, represented by the fluvial Level III and fluvial-deltaic Level II, respectively.

HOU Dali, HAN Xin, TANG Hongming, GUO Jianchun, GONG Fengming, SUN Lei, QIANG Xianyu

Adsorbed gas represents a primary mode of shale gas occurrence and is a major source of shale gas production in the later stages of development. It primarily resides within the organic kerogen and clay minerals of shale formations, with organic kerogen being the dominant host. Consequently, the study of organic kerogen characteristics and its adsorption mechanisms is crucial for understanding shale gas development. In this paper, the kerogen of Longmaxi Shale in the Sichuan Basin is taken as the research object. The microstructure of kerogen is expressed by combining methods through the solid-state NMR experiment, Fourier transform infrared spectroscopy experiment, X-ray photoelectron spectroscopy experiment, and the molecular structure model of kerogen is constructed. The adsorption mechanism and characteristics of CH4 in kerogen of Longmaxi Shale are analyzed by magnetic levitation weight experiment, molecular simulation methods of the Grand Canonical Monte Carlo（GCMC）, and Molecular Dynamics（MD）. The results show that the molecular formula of the kerogen of shale experimental sample of Longmaxi Formation is C237H219O21N5S4. The excess adsorption gas volume of CH4 in kerogen increase first and then decreased with the increase of pressure. Under the same pore size and pressure, the excess adsorption gas volume and total gas volume of CH4 decrease with the increase in temperature. The C and S atoms in kerogen are the main cause of CH4 adsorption. The CH4 near the kerogen pore wall presents an adsorption state, while the CH4 far from the kerogen pore wall presents a free state. As the pore size increase, the distance between the two peaks of CH4 density gradually increases, and the peak value decreases gradually.

Deng Han, Wang Yao, Meng Zhaolan et al.

The main sand-control layer of the porous metal screen is made of metal with excellent high temperature resistance and corrosion resistance.Due to its special three-dimensional pore structure,the screen has strong permeability and flow capacity.It has good applicability in conventional cold production and development in oil and gas fields.In order to further evaluate the adaptability of the screen under the conditions of heavy oil thermal development,multi-round of steam huff and puff simulation experiments were carried out to simulate the change of sand control effect of the screen in the process of multi-round of steam huff and puff stimulation,and analyze the pressure,temperature,sand production and sand particle size of the screen during the injection and production process.The experimental results show that after 16 rounds of steam huff and puff experiments(the maximum steam temperature is 350 ℃,and the maximum injection pressure is 17 MPa),the sand concentration of the screen ranges from 1.86×10^-7% to 6.63×10^-6%,the median particle size of the sand is slightly smaller than the sand control accuracy of the screen,and the permeability retention capacity is about 85.7%.The overall flow capacity and anti-plugging performance retention rate of the screen is good.The experimental conclusion fully proves that the screen has an excellent adaptability in the development of heavy oil thermal recovery reservoirs.

Kiplang'at Weldon, John Ngechu, Ngatho Everlyne et al.

Over the past 20 years, Kenya's demand for petroleum products has proliferated. This is mainly because this particular commodity is used in many sectors of the country's economy. Exchange rates are impacted by constantly shifting prices, which also impact Kenya's industrial output of commodities. The cost of other items produced and even the expansion of the economy is significantly impacted by any change in the price of petroleum products. Therefore, accurate petroleum price forecasting is critical for devising policies that are suitable to curb fuel-related shocks. Data mining techniques are the tools used to find valuable patterns in data. Data mining techniques used in petroleum price prediction, including artificial neural networks (ANNs), support vector machines (SVMs), and intelligent optimization techniques like the genetic algorithm (GA), have grown increasingly popular. This study provides a comprehensive review of the existing data mining techniques for making predictions on petroleum prices. The data mining techniques are classified into regression models, deep neural network models, fuzzy sets and logic, and hybrid models. A detailed discussion of how these models are developed and the accuracy of the models is provided.

Yan Dongzhi, Lei Yu, Liao Ruiquan et al.

In order to determine the multiphase fluid flow parameters of wellbore in the process of recovering heavy oil by gas injection, the flow pattern of gas-liquid flow in wellbore in the process of lifting heavy oil were studied. In this paper, by means of conducting gas-liquid flow experiment of high viscosity fluid in vertical pipe, with the help of high-speed camera, the annular flow transition pheNmenon in the pipe under different oil viscosities(60, 100, 290 cp)and different liquid apparent flow rates(0.2, 0.5, 0.8 m/s)were observed; then, based on the gas-liquid flow theory and fluid dyNmics, a method for discriminating the formation of gas-liquid annular flow in wellbore that has considered liquid viscosity was proposed, i.e., when the slip velocity between gas and liquid phases is equal to the velocity loss caused by liquid viscosity and gravity, the annular flow begins to form; and finally, the annular flow transition boundary model was established. Under the working conditions covered by the experiment, the new model can accurately predict the formation of annular flow, but as the liquid flow rate increases, the annular flow gradually approaches the discriminant boundary. The study results lay a foundation for further studying the law of high viscosity gas-liquid flow.

Onaiwu Oduwa David, Usiosefe Ikponmwosa, Okon Samuel

Generating pressure transient response for an interpretation model to describe essential features of a reservoir system accurately is often difficult. It is generally due to the inaccessibility of standard pressure transient analysis tools due to the cost, and even when accessible, they are constrained to its workflow and limitations. This study presents an alternative to standard industry tools to determine transient pressure response for a given rate history. A reservoir model for a single well with constant skin and wellbore storage producing a varying step rate in a semi-infinite acting reservoir with a sealing fault was used as a case study. The well is also assumed to be producing above saturation pressure from a reservoir saturated with slightly compressible fluid hence having constant fluid properties. The method discussed in this study can be applied to well-test interpretation models with an analytical constant terminal rate solution producing at variable step rates from a reservoir having constant rock and fluid properties. The results show conformance with that of standard industry software, and diagnostic plots of the simulated data set can help engineers plan well-test jobs and study the behavior of different reservoir models. Moreover, the program can be modified and used to regress observed pressure response with a selected model. The approach suggested by this study is a perfect alternative where time and cost are constraints.

Liang Zhang, Rong Feng, Songhe Geng et al.

Seepage-type gas hydrate accumulation in subsea shallow formations involves complicated thermo-hydro-solid coupling processes and matching problem between various accumulation elements. The formation physical properties control local natural gas migration pathway and thus the final reservoir characteristics of hydrates. In this paper, a novel mixed-flux model for gas hydrate accumulation is established and then used to simulate the process of methane gas migration into the shallow stratum to form a hydrate reservoir. The effects of reservoir heterogeneity and gas source conditions on the distribution of pore fluid and hydrate accumulation are examined. The simulation results show that reservoir heterogeneity is conducive to the retention and lateral migration of CH4 in a hydrate stability zone. CH4 can contact more pore water to form a large hydrate reserve, but the formed hydrate is often dispersed. Low-permeability layers enhance the trapping of CH4 and form a uniform and large hydrate saturation. Besides, gas source conditions have an important impact on the hydrate accumulation in reservoirs. Large gas flux, small pore water flux, continuous gas supply, high content of heavy components in natural gas, and numerous gas source points contribute to large amounts of hydrates generation in a certain time period. The presented work will deepen our understanding of the controls of natural gas hydrate systems in subea shallow formations.

Qian Deru, Zheng Junhua, Gao Runfeng et al.

The MWD tool for formation pressure is composed of mechanical, electronic and hydraulic components. The internal installation space is small, the structure is complex, and the integration is difficult. In order to reduce the research and development risk of the tool, the formation pressure simulation gauging nipple was developed firstly. The 3D visualization technology was used to establish the virtual digital prototype of the simulation gauging nipple. The hydraulic valve insertion technology was used to study the key modules such as the micro hydraulic system with an output pressure of 20 MPa. Meanwhile, a formation pressure simulation test apparatus was developed as a platform for indoor high-temperature and high-pressure test and test principle verification of simulation gauging nipple. Actual measurement shows that the simulation gauging nipple runs stably at 120 ℃ and 60 MPa. Cores with permeability of 1×10^-3 μm² and 320×10^-3 μm² were selected to investigate the gauging nipple test principle, obtaining the formation pressure test curve, with measurement accuracy reaching 96%. The laboratory test verified the correctness of the measurement principle of the simulation gauging nipple and the accuracy of the measurement data. The research results lay a solid foundation for the development of formation pressure MWD engineering prototype.

Eric Johnson, Carl Vadenbo

Energy-related greenhouse gas emissions dominate the carbon footprints of most product systems, and petroleum is one of the main types of energy sources. This is consumed as a variety of refined products – most notably diesel, petrol (gasoline) and jet fuel (kerosene). Refined product carbon footprints are of great importance to regulators, policymakers and environmental decision-makers. For instance, they are at the heart of legislation such as the European Union’s Renewable Energy Directive or the United States’ Renewable Fuels Standard. This study identified 14 datasets that report footprints for the same system, European petroleum refining. For the main refined products – diesel, petrol and jet fuel – footprints vary by at least a factor of three. For minor products, the variation is even greater. Five different organs of the European Commission have estimated refining footprints: for main products these are relatively harmonic; for minor products much less so. The footprint variation is due mainly to differing approaches to refinery modelling, especially regarding the rationale and methods applied to assign shares of the total burden from the petroleum refinery operation to the individual products. Given the economic/social importance of refined products, a better harmony of their footprints would be valuable to their users.

Elena Khlebnikova, Kaarthik Sundar, Anatoly Zlotnik et al.

The majority of overland transport needs for crude petroleum and refined petroleum products are met using pipelines. Numerous studies have developed optimization methods for design of these systems in order to minimize construction costs while meeting capacity requirements. Here, we formulate problems to optimize the operations of existing single liquid commodity pipeline systems subject to physical flow and pump engineering constraints. The objectives are to maximize the economic value created for users of the system and to minimize operating costs. We present a general computational method for this class of continuous, non-convex nonlinear programs, and examine the use of pump operating settings and flow allocations as decision variables. The approach is applied to compute optimal operating regimes and perform engineering economic sensitivity analyses for a case study of a crude oil pipeline developed using publicly available data.

F. Cataldo, D. A. Garcia-Hernandez, A. Manchado

The petroleum and coal models of the unidentified infrared emissions (UIE), sometimes referred also as unidentified infrared bands (UIBs) has been reviewed mainly based on the work of the authors with the inclusion of unpublished results. It is shown that the petroleum and coal model of the UIE converges and merges quite well with the MAON (Mixed Aromatic Aliphatic Organic Nanoparticles) model of the UIE. It is shown that the thermal treatment of various substrates like PAHs, alkylated PAHs but also mixed aliphatic/olefinic substrates leads invariable to carbonaceous materials matching the infrared spectrum of anthracite coal or certain petroleum fractions. Thus, the experimental thermal processing (which under space conditions could be equivalent to the expected processing by shock waves or high energy radiation) of mixed aromatic/aliphatic organic matter can be used to match also the UIE evolution. Another way to simulate the thermal/radiation processing of organic matter in space, can be achieved through the carbon arc. Simple substrates processed in this way produce carbon soot and a plethora of organic molecules. Fullerenes are found in space both through mid-infrared and optical spectroscopy and it is very likely that other complex related species such as endohedral fullerenes (i.e. fullerenes with a metal, heteroatom or molecules inside the cage) may be formed in space. After all, their formation requires the same conditions as those needed for fullerene formation provided that also a metal vapour (e.g. interstellar/circumstellar gas) is available. The last part of this review is thus dedicated to the recent results on the study and characterization of an endohedral C60 derivative containing lithium inside the cage.

Nazanin Moradinasab, Hassan Jafarzadeh, M. R. Amin-Naseri et al.

Petroleum industry is the world's biggest energy source, and its associated industries such as production, distribution, refining and retail are considered as the largest ones in the world. Having the increasing price and governments job creation and international environmental policies, the petroleum companies try to maximize the number of created job, and their profit and minimize the air pollution simultaneously. To meet these objectives, an effective detailed and precise planning is needed. On the other hand, the dynamic environment and the presence of various stakeholders add to the complexity of planning and design of petroleum supply chain. Therefore, the multi-period, multi-objective, multi-level and multi-product dynamic sustainable competitive petroleum supply chain (DSCPSC) model taking into consideration the various stakeholders have been proposed in this paper. The proposed model is an MILP model and GAMS 24.1.2 software has been used to run it for a part of real petroleum supply chain data. Sensitivity analysis was then performed to determine the sensitivity of the results to the variation of the coefficients in objective function. Sensitivity analysis reveals that the highest variations of the objective function were observed with respect to the variable costs, facility installation costs and pipeline transportation costs.