Compositional Characterization of Nitrogen Compounds in Changqing Crude Oil and Its Heavy Distillates

The nitrogen-containing compounds in Changqing crude oil, its atmospheric residue(AR), and vacuum reside(VR) were characterized by negative and positive ion electrospray ionization(ESI) Fourier transform ion cyclotron resonance mass spectrometry(FT-ICR MS). The heteroatom compounds(N_1, N_2, N_1O_1, O_1, and O_2 class species) could be identified by the negative ESI analysis, while the positive mode could only detect the N_1, N_2, and N_1O_1 class species. Among them, the N_1 class species were found to be predominant in crude oil, as confirmed by either negative or positive ESI analyses,which were similar in composition to AR and VR. These compounds with higher abundance were characterized by double bond equivalent(DBE) values and carbon numbers. The composition of these compounds in crude oil and its AR as well as VR was correlated with their different boiling range, DBE values and carbon numbers. The negative ESI analysis showed that the abundant N_1 class species in crude oil and AR were centered at a DBE value of 12, and these species were likely benzocarbazoles, while the N_1 class species with the DBE value ranging from 13 to 16 having more complicated molecular structures were dominant in VR. And the positive ESI analysis gave the information of the abundant N_1 class species in crude oil, AR, and VR having the DBE values in the range of 10, 9―11, and 10―16, respectively, which were likely the compounds with the core of quinoline and benzoquinoline. The analysis confirmed that the distillation process in refinery preferentially removed the low DBE value and low molecular N-class species and brought them into the light and medium distillates, while those N-class species having a high molecular condensation in the molecules with large carbon number remained in the residual oil and could continually affect the downstream oil refining process.

Relative Performance Evaluation of Competing Crude Oil Prices’ Volatility Forecasting Models: A Slacks-Based Super-Efficiency DEA Model

With the increasing number of quantitative models available to forecast the volatility of crude oil prices, the assessment of the relative performance of competing models becomes a critical task. Our survey of the literature revealed that most studies tend to use several performance criteria to evaluate the performance of competing forecasting models;however, models are compared to each other using a single criterion at a time, which often leads to different rankings for different criteria—A situation where one cannot make an informed decision as to which model performs best when taking all criteria into account. In order to overcome this methodological problem, Xu and Ouenniche [1] proposed a multidimensional framework based on an input-oriented radial super-efficiency Data Envelopment Analysis (DEA) model to rank order competing forecasting models of crude oil prices’ volatility. However, their approach suffers from a number of issues. In this paper, we overcome such issues by proposing an alternative framework.

Crude oil mobility and its controlling factors in tight sand reservoirs in northern Songliao Basin, East China

Taking tight oil in Gaotaizi and Fuyu oil layers of the Upper Cretaceous Qingshankou Formation in northern Songliao Basin as an example, based on analyses of nuclear magnetic resonance and high pressure mercury injection, experiment methods of supercritical carbon dioxide displacement and extraction are firstly employed to quantify crude oil mobility in tight sand reservoirs with different lithologies and oil contents. The results show that, under the conditions of simulating the Cretaceous Qingshankou Formation in the northern Songliao Basin at a temperature of 76-89 °C and a pressure of 35-42 MPa, the lower limit of the porosity of the movable oil is4.4%, and the lower limit of the permeability is 0.015′10-3 mm2. The lower limit of the average pore throat radius is 21 nm. On this basis,a classification standard for three types of tight sand reservoirs is proposed. Type I reservoirs are characterized by the movable fluid saturation larger than 40%, the movable oil ratio(ratio of movable oil to total oil) greater than 30% and the starting pressure gradient in the range of 0.3-0.6 MPa/m; Type II reservoirs are characterized by the movable fluid saturation in the range of 10%–40%, the movable oil ratio in the range of 5%–30% and the starting pressure gradient in the range of 0.6–1.0 MPa/m; Type III reservoirs are characterized by the movable fluid saturation less than 10% in general, the movable oil ratio less than 5%, and the starting pressure gradient greater than1.0 MPa/m. The fluid mobility in tight sand reservoirs is mainly affected by diagenesis and sedimentary environment. Reservoirs with depth lower than 2000 m are dominated by type I reservoir, whereas those with greater depth are dominated by type I and II reservoirs.Reservoirs in inner delta-front facies are dominated by type I reservoir, whereas those in outer delta-front facies and shore-shallow lacustrine facies are dominated by type II and III reservoirs.

The impacts of gas impurities on the minimum miscibility pressure of injected CO_2-rich gas–crude oil systems and enhanced oil recovery potential

An effective parameter in the miscible-CO_2 enhanced oil recovery procedure is the minimum miscibility pressure(MMP)defined as the lowest pressure that the oil in place and the injected gas into reservoir achieve miscibility at a given temperature. Flue gases released from power plants can provide an available source of CO_2,which would otherwise be emitted to the atmosphere, for injection into a reservoir. However, the costs related to gas extraction from flue gases is potentially high. Hence, greater understanding the role of impurities in miscibility characteristics between CO_2 and reservoir fluids helps to establish which impurities are tolerable and which are not. In this study, we simulate the effects of the impurities nitrogen(N_2), methane(C_1), ethane(C_2) and propane(C_3) on CO_2 MMP. The simulation results reveal that,as an impurity, nitrogen increases CO_2–oil MMP more so than methane. On the other hand, increasing the propane(C_3)content can lead to a significant decrease in CO_2 MMP, whereas varying the concentrations of ethane(C_2) does not have a significant effect on the minimum miscibility pressure of reservoir crude oil and CO_2 gas. The novel relationships established are particularly valuable in circumstances where MMP experimental data are not available.

Application of Artificial Neural Networks Based Monte Carlo Simulation in the Expert System Design and Control of Crude Oil Distillation Column of a Nigerian Refinery

This research work investigated comparative studies of expert system design and control of crude oil distillation column (CODC) using artificial neural networks based Monte Carlo (ANNBMC) simulation of random processes and artificial neural networks (ANN) model which were validated using experimental data obtained from functioning crude oil distillation column of Port-Harcourt Refinery, Nigeria by MATLAB computer program. Ninety percent (90%) of the experimental data sets were used for training while ten percent (10%) were used for testing the networks. The maximum relative errors between the experimental and calculated data obtained from the output variables of the neural network for CODC design were 1.98 error % and 0.57 error % when ANN only and ANNBMC were used respectively while their respective values for the maximum relative error were 0.346 error % and 0.124 error % when they were used for the controller prediction. Larger number of iteration steps of below 2500 and 5000 were required to achieve convergence of less than 10-7?for the training error using ANNBMC for both the design of the CODC and controller respectively while less than 400 and 700 iteration steps were needed to achieve convergence of 10-4?using ANN only. The linear regression analysis performed revealed the minimum and maximum prediction accuracies to be 80.65% and 98.79%;and 98.38% and 99.98% when ANN and ANNBMC were used for the CODC design respectively. Also, the minimum and maximum prediction accuracies were 92.83% and 99.34%;and 98.89% and 99.71% when ANN and ANNBMC were used for the CODC controller respectively as both methodologies have excellent predictions. Hence, artificial neural networks based Monte Carlo simulation is an effective and better tool for the design and control of crude oil distillation column.

A Review of an Expert System Design for Crude Oil Distillation Column Using the Neural Networks Model and Process Optimization and Control Using Genetic Algorithm Framework

This paper presents a comprehensive review of various traditional systems of crude oil distillation column design, modeling, simulation, optimization and control methods. Artificial neural network (ANN), fuzzy logic (FL) and genetic algorithm (GA) framework were chosen as the best methodologies for design, optimization and control of crude oil distillation column. It was discovered that many past researchers used rigorous simulations which led to convergence problems that were time consuming. The use of dynamic mathematical models was also challenging as these models were also time dependent. The proposed methodologies use back-propagation algorithm to replace the convergence problem using error minimal method.

Improving Supply Chain Strategies towards Mitigating the Effect of Crude Oil Theft and Pipeline Vandalism in the Nigerian Oil and Gas Industry: A Case Study of the Nigerian National Petroleum Corporation (NNPC)

Generically, SCM may be said to include all activities carried out to ensure proper functioning of the supply chain. The activities included in proper management of a supply chain broadly include logistics activities, planning and control of the flow of information and materials in a firm, management of relationships with other organizations and government intervention, However, crude oil theft and pipeline vandalism are established products supply chain disruptors in Nigeria which are rendering the task of running an efficient petroleum supply chain onerous. This paper aims to establish the importance of effective supply chain strategies for companies in the oil and gas industry with special focus on the Nigerian oil and gas sector and the strategies by which the state oil and gas corporation in this sector may mitigate disruptions to its supply chain. This study investigates the enhancement of supply chain strategies towards meeting the challenge of crude oil theft and pipeline vandalism, using the Nigerian National Corporation (NNPC) as a case study. Based on this study, data were collected from two sources: A summary of incident reports obtained from NNPC and an interview with personnel in the PPMC Department. Incident report refers to a report produced when accidents such as equipment failure, injury, loss of life, or fire occur at the work site. Content analysis is utilized to evaluate data obtained from interview responses, CBN financial stability reports, NDIC annual reports, circulars, banking supervision reports and implementation guidelines. The study found out that NNPC should endeavor to sustain its value chain and ward of pipeline vandals and crude oil thieves by engaging in community partnership, detailing security outfits to ensure its pipelines’ right of way and bridging. Concluded that the oil supply chain of the Nigerian National Petroleum Corporation has been plagued by disruptions in the form of crude oil theft and pipeline vandalism which has had debilitating effects on its value.

The interactions between Chinese local corn and WTI crude oil prices:an empirical analysis

This paper investigates the relationship between China’s fuel ethanol promotion plan and food security based on the interactions between the crude oil market, the fuel ethanol market and the grain market. Based on the US West Texas Intermediate(WTI) crude oil spot price and Chinese corn prices from January 2008 to May 2018, this paper applies Granger causality testing and a generalized impulse response function to explore the relationship between world crude oil prices and Chinese corn prices. The results show that crude oil prices are not the Granger cause of China’s corn prices, but changes in world crude oil prices will have a long-term positive impact on Chinese corn prices. Therefore, the Chinese government should pay attention to changes in crude oil prices when promoting fuel ethanol. Considering the conduction e ect between fuel ethanol and the food market, the government should also take some measures to ensure food security.

Optimization of Diesel and Crude Oil Degradation in a Ghanaian Soil Using Organic Wastes as Amendment

Soil contamination by hydrocarbons poses numerous environmental, health and agricultural problems. The degradation of these pollutants can occur naturally but very slowly. It is therefore generally necessary to stimulate this degradation by different means. Thus, this study aimed to improve the bio-degradation of diesel and crude oil in a Ghanaian soil by biostimulation. For this, the sampled soil was characterized by standard methods and contaminated with diesel and crude oil at a proportion of 1% (w/w). Then, contaminated soil samples were supplemented with biochar-compost, poultry manure or cow dung at the proportion of 10% (w/w). Periodically, fractions of these samples were taken to evaluate the density of hydrocarbon utilizing bacteria (HUB) and the residual quantities of diesel or crude oil. The characteristics of the soil used show the need for supplementation for better degradation of hydrocarbons. The results of the study show that supplementing the soil with organic substrates increases HUB loads in soils contaminated by diesel and crude oil. They also show that the residual quantities of diesel and crude oil are generally significantly lower in supplemented soils (p = 0.048 and p < 0.0001 respectively). In addition, the study shows that degradation was generally greater in soils contaminated by diesel compared to those contaminated by crude oil, especially at the end of the study.

Data-driven Wasserstein distributionally robust chance-constrained optimization for crude oil scheduling under uncertainty

Crude oil scheduling optimization is an effective method to enhance the economic benefits of oil refining.But uncertainties,including uncertain demands of crude distillation units(CDUs),might make the production plans made by the traditional deterministic optimization models infeasible.A data-driven Wasserstein distributionally robust chance-constrained(WDRCC)optimization approach is proposed in this paper to deal with demand uncertainty in crude oil scheduling.First,a new deterministic crude oil scheduling optimization model is developed as the basis of this approach.The Wasserstein distance is then used to build ambiguity sets from historical data to describe the possible realizations of probability distributions of uncertain demands.A cross-validation method is advanced to choose suitable radii for these ambiguity sets.The deterministic model is reformulated as a WDRCC optimization model for crude oil scheduling to guarantee the demand constraints hold with a desired high probability even in the worst situation in ambiguity sets.The proposed WDRCC model is transferred into an equivalent conditional value-at-risk representation and further derived as a mixed-integer nonlinear programming counterpart.Industrial case studies from a real-world refinery are conducted to show the effectiveness of the proposed method.Out-of-sample tests demonstrate that the solution of the WDRCC model is more robust than those of the deterministic model and the chance-constrained model.

Effects of biodegradation on diamondoid distribution in crude oils from the Bongor Basin,Chad

The sensitivity of biodegradation on diamondoids was investigated using a series of biodegraded oil samples from the Ronier tectonic unit of Bongor Basin,Chad.The results suggest that diamondoids,including adamantanes(As)and diamantanes(Ds),are relatively resistant to biodegradation and obvious biodegradation was observed in oils with a Peters-Moldowan(PM)biodegradation rank of 6 or more.Overall,the sensibility of biodegradation on diamondoids is generally similar to hopanes and regular steranes.As biodegradation evolves,the changes in concentration and components of diamondoids show that the biodegradation process is selective and stepwise.The significant increase of MD/MA and DMD/DMA for oils with a PM ranking 6^(+) indicates that diamantanes are generally more resistant to biodegradation than adamantanes.The similar trends of DMA/MA,EA/MA,MD/D,DMD/MD and other relevant indexes,show that higher alkylation homologs are more resistant to biodegradation.The commonly used diamondoid ratios,such as MAI,EAI,MDI and DMID-1,are obviously affected by biodegradation at the stage of high-level biodegradation,which may indicate that these ratios should be used with caution in case of severely degraded oils.

Prediction Model of Wax Deposition Rate in Waxy Crude Oil Pipelines by Elman Neural Network Based on Improved Reptile Search Algorithm

A hard problem that hinders the movement of waxy crude oil is wax deposition in oil pipelines.To ensure the safe operation of crude oil pipelines,an accurate model must be developed to predict the rate of wax deposition in crude oil pipelines.Aiming at the shortcomings of the ENN prediction model,which easily falls into the local minimum value and weak generalization ability in the implementation process,an optimized ENN prediction model based on the IRSA is proposed.The validity of the new model was confirmed by the accurate prediction of two sets of experimental data on wax deposition in crude oil pipelines.The two groups of crude oil wax deposition rate case prediction results showed that the average absolute percentage errors of IRSA-ENN prediction models is 0.5476% and 0.7831%,respectively.Additionally,it shows a higher prediction accuracy compared to the ENN prediction model.In fact,the new model established by using the IRSA to optimize ENN can optimize the initial weights and thresholds in the prediction process,which can overcome the shortcomings of the ENN prediction model,such as weak generalization ability and tendency to fall into the local minimum value,so that it has the advantages of strong implementation and high prediction accuracy.

A Method for Crude Oil Selection and Blending Optimization Based on Improved Cuckoo Search Algorithm

Refineries often need to find similar crude oil to replace the scarce crude oil for stabilizing the feedstock property. We introduced the method for calculation of crude blended properties firstly, and then created a crude oil selection and blending optimization model based on the data of crude oil property. The model is a mixed-integer nonlinear programming(MINLP) with constraints, and the target is to maximize the similarity between the blended crude oil and the objective crude oil. Furthermore, the model takes into account the selection of crude oils and their blending ratios simultaneously, and transforms the problem of looking for similar crude oil into the crude oil selection and blending optimization problem. We applied the Improved Cuckoo Search(ICS) algorithm to solving the model. Through the simulations, ICS was compared with the genetic algorithm, the particle swarm optimization algorithm and the CPLEX solver. The results show that ICS has very good optimization efficiency. The blending solution can provide a reference for refineries to find the similar crude oil. And the method proposed can also give some references to selection and blending optimization of other materials.

Molecular Organic Geochemistry of Crude Oils from the Albertine Graben, Uganda： Possible Implications on the Expulsion of the Oils from the Source Rocks

Twelve representative crude oil samples recovered from six oil fields in the Albertine Graben, Uganda were chosen for this study. The study aimed to understand the genetic relationships between the oils, the inferred depositional environment of the source rocks, maturity of the crude oils, and to gain some insight on the expulsion of the oils from source rocks. The work involved geochemical bulk analysis （asphaltene and liquid chromatographic separations）, GC-FID （gas chromatography with a flame ionization detector）, and GC-MS （gas chromatography-mass spectrometry） of saturate and aromatic fractions. Bulk analysis shows that the oils are dominated by saturate hydrocarbon fractions （48.7%-62.0%） and are highly waxy （35-56.2 wt%） with low sulfur content （〈 0.1 wt%）. The high saturate hydrocarbon and high wax contents are probably due to organic matter input from land plants and/or long-chain alkanes from fresh water algae in lacustrine systems. The low sulfur contents alongside the high wax abundances are consistent with elastic-dominated source rock facies deposited in a non-stratified lacustrine environment. Data from GC-FID and GC-MS analyses such as n-alkane distributions, pristane/phytane ratios, biomarker terpane and sterane, dibenzothiophene and phenanthrene parameters show that the oils belong to a single family and were derived from a elastic predominantly algal source rock deposited under suboxic conditions in a non-stratified freshwater to brackish water lacustrine environment. The data further show that the oils have a very narrow range of maturities and are generated in the peak oil window. The observed narrow range of maturities and inferred lacustrine depositional setting for the source rocks suggest that the kerogen responsible for the generation of the oils is likely to be predominantly type-1 known to display narrow activation energies. This in turn implies that the expulsion of the oil from the source rock occurred as a quick single event hence, the filling of reservoirs in the Albertine Graben probably did not involve late stage expulsion and multiple charges of oil.

Investigations into Optimization Models of Crude Oil Distillation Column in the Context of Feed Stock and Market Value

This paper proposes optimization models of crude oil distillation column for both limited and unlimited feed stock and market value of known products prices. The feed to the crude distillation column was assumed to be crude oil containing naphtha gas, kerosene, petrol and diesel as the light-light key, light key, heavy key and heavy-heavy key respectively. The models determined maximum concentrations of heavy key in the distillate and light key in the bottom for limited feed stock and market condition. Both were impurities in their respective positions of the column. The limiting constraints were sales specification concentration of light key in the distillate [ ], heavy key in the bottom [ ] and an operating loading constraint of flooding above the feed tray. For unlimited feed stock and market condition, the optimization models determined the optimum separation [ and ] and feed flow rate that would give maximum profit with minimum purity sales specification constraints of light key in the distillate and heavy key in the bottom as stated above. The feed loading was limited by the reboiler capacity. However, there is need to simulate the optimization models for an existing crude oil distillation column of a refinery in order to validate the models.

Experimental research on characteristic of start-up pressure wave propagation in gelled crude oil by large-scale flow loop

In order to research start-up pressure wave propagation mechanism and determine pressure wave speed in gelled crude oil pipelines accurately,experiment of Large-scale flow loop was carried out.In the experiment,start-up pressure wave speeds under various operation conditions were measured,and effects of correlative factors on pressure wave were analyzed.The experimental and theoretical analysis shows that thermal shrinkage and structural properties of gelled crude oils are key factors influencing on start-up pressure wave propagation.The quantitative analysis for these effects can be done by using volume expansion coefficient and structural property parameter of gelled crude oil.A new calculation model of pressure wave speed was developed on the basis of Large-scale flow loop experiment and theoretical analysis.

Research on a TOPSIS energy efficiency evaluation system for crude oil gathering and transportation systems based on a GA-BP neural network

As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crude oil gathering and transportation systems and identify the energy efficiency gaps.In this paper,the energy efficiency evaluation system of the crude oil gathering and transportation system in an oilfield in western China is established.Combined with the big data analysis method,the GA-BP neural network is used to establish the energy efficiency index prediction model for crude oil gathering and transportation systems.The comprehensive energy consumption,gas consumption,power consumption,energy utilization rate,heat utilization rate,and power utilization rate of crude oil gathering and transportation systems are predicted.Considering the efficiency and unit consumption index of the crude oil gathering and transportation system,the energy efficiency evaluation system of the crude oil gathering and transportation system is established based on a game theory combined weighting method and TOPSIS evaluation method,and the subjective weight is determined by the triangular fuzzy analytic hierarchy process.The entropy weight method determines the objective weight,and the combined weight of game theory combines subjectivity with objectivity to comprehensively evaluate the comprehensive energy efficiency of crude oil gathering and transportation systems and their subsystems.Finally,the weak links in energy utilization are identified,and energy conservation and consumption reduction are improved.The above research provides technical support for the green,efficient and intelligent development of crude oil gathering and transportation systems.

The Effects of Carbon Dioxide Laser Irradiation on Drilling of Limestone Included Crude Oil

Laser rock spallation is a rock removal process that utilizes laser induced thermal stress to fracture and cause a break through the rock by creating small fragments before melting of the rock. In this paper we investigated the effects of CO2 laser irradiation on limestone of Iran Sarvak formation. Since the limestone included heavy and light oil, we studied the amount of laser beam absorption by this oils for determining thermal fractured during the laser drilling laboratory process. In order to characterize this limestone spectrophotometry (from UV to NIR), scanning electron microscopy (SEM) have been used.

Permafrost warming along the Mo'he-Jiagedaqi section of the China-Russia crude oil pipeline

The permafrost along the China-Russia Crude Oil Pipeline(CRCOP) is degrading since the pipeline operation in 2011. Heat dissipated from the pipeline, climate warming and anthropogenic activities leads to permafrost warming. The processes of permafrost warming along the CRCOP were studied based on the monitoring of air and soil temperatures, and electrical resistivity tomography(ERT) surveys. Results show that:(1) the mean annual air temperature(MAAT) in permafrost regions along the CRCOP increased with a rate of 0.21°C/10a–0.40°C/10 a during the past five decades;(2) the mean annual ground temperature(MAGT, at-15 m depth) of undisturbed permafrost increased by 0.2°C and the natural permafrost table remained unchanged due to the zero-curtain effect;(3) permafrost surrounding the uninsulated pipeline right-of-way warmed significantly compared with that in a natural site. During 2012–2017, the MAGT and the artificial permafrost table, 2 m away from the pipeline centerline, increased at rates of 0.063°C/a and 1.0 m/a. The thaw bulb developed around the pipe and exhibits a faster lateral expansion;(4) 80-mm-thick insulation could reduce the heat exchange between the pipeline and underlying permafrost and then keep the permafrost and pipe stable. The MAGT and the artificial permafrost table, 4.8 m away from the center line of the pipeline, increased by 0.3°C/a and 0.43 m/a, respectively. Due to the heat disturbance caused by warm oil, the degradation of wetland, controlled burn each autumn and climate warming, the permafrost extent reduced and warmed significantly along the CRCOP route. Field observations provide basic data to clarify the interactions between CRCOP and permafrost degradation and environmental effects in the context of climate change.

The Relationship between Nigerian Bonnylight Crude Oil-Induced Hypoglycaemia and Endogenous Serum Insulin Concentration in Male Wistar Rats: The Role of Antioxidant Vitamins C and E

The relationship between Nigerian Bonny Light crude oil (NBLCO) induced hypoglycaemia and endogenous serum insulin concentration;the role of antioxidant vitamin C or E supplementation was the focus of this study. Forty adult male Wistar rats were randomly divided into group I, which served as the control, group II, which was oral gavaged 6 ml/kg of NBLCO, groups III and IV, which were in addition to 6 ml/kg of NBLCO supplemented with 9 ml/kg and 1 mg/kg of vitamin E or C, respectively for 28 days. Results showed that NBLCO significantly (p < 0.05) lower body weight and food intake compared with control. These effects exerted by NBLCO were however significantly (p < 0.05) reversed by vitamin E or C supplementation. The NBLCO significantly (p < 0.05) reduced fasting blood glucose (FBG) when compared with control, the antioxidant vitamins supplementation significantly (p < 0.05) reversed the crude oil effect. The mean serum insulin level in NBLCO, vitamin E or C supplemented groups is not significantly different from the control. There was no significant correlation between FBG and fasting serum insulin concentrations in all the groups on day 28. It has been demonstrated in this study that direct oral ingestion of crude oil (NBLCO) could reduce food intake, body weight and cause hypoglycemia;the hypoglycemia may not be a function of serum insulin concentration. Interestingly, the hazardous effects of NBLCO could be ameliorated with antioxidant vitamin C or E supplementation.