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First, second, third, and fourth-generation biofuels are continuously evolving as a promising substitute to petrodiesel catalyzed by energy depletion, economic and environmental considerations. Bio-diesel can be synthesized from various biomass sources, which are commonly divided into FAME and renewable biodiesel. FAME biodiesel is generally produced by the transesterification of vegetable oils and fats while renewable diesel is produced by hydro-deoxygenation of vegetable and waste oils and fats. The different generation, processing technologies and standards for FAME and renewable biodiesel are reviewed. Finally, the life cycle analysis and production cost of conventional and renewable biodiesel are described.

Proxy models are widely used to estimate parameters such as interwell connectivity in the development and management of petroleum fields due to their low computational cost and not require prior knowledge of reservoir properties. In this work, we propose a proxy model to determine both oil and water production to maximize reservoir profitability. The approach uses production history and the Capacitance and Resistance Model based on Producer wells (CRMP), together with the combination of two fractional flow models, Koval [Cao (2014) Development of a Two-phase Flow Coupled Capacitance Resistance Model. PhD Dissertation, The University of Texas at Austin, USA] and Gentil [(2005) The use of Multilinear Regression Models in patterned waterfloods: physical meaning of the regression coefficient. Master’s Thesis, The University of Texas at Austin, USA]. The proposed combined fractional flow model is called Kogen. The combined fractional flow model can be formulated as a constrained nonlinear function fitting. The objective function to be minimized is a measure of the difference between calculated and observed Water cut (Wcut) values or Net Present Values (NPV). The constraint limits the difference in water cuts of the Koval and Gentil models at the time of transition between the two. The problem can be solved using the Sequential Quadratic Programming (SQP) algorithm. The parameters of the CRMP model are the connectivity between wells, time constant and productivity index. These parameters can be found using a Nonlinear Least Squares (NLS) algorithm. With these parameters, it is possible to predict the liquid rate of the wells. The Koval and Gentil models are used to calculate the Wcut in each producer well over the concession period which in turn allows to determine the accumulated oil and water productions. To verify the quality of Kogen model to forecast oil and water productions, we formulated an optimization problem to maximize the reservoir profitability where the objective function is the NPV. The design variables are the injector and producer well controls (liquid rate or bottom hole pressure). In this work the optimization problem is solved using a gradient-based method, SQP. Gradients are approximated using an ensemble-based method. To validate the proposed workflow, we used two realistic reservoirs models, Brush Canyon Outcrop and Brugge field. The results are shown into three stages. In the first stage, we analyze the ensemble size for the gradient computation. Second, we compare the solutions obtained with the three fractional flow models (Koval, Gentil and Kogen) with results achieved directly from the simulator. Third, we use the solutions calculated with the proxy models as starting points for a new high-fidelity optimization process, using exclusively the simulator to calculate the functions involved. This study shows that the proposed combined model, Kogen, consistently generated more accurate results. Also, CRMP/Kogen proxy model has demonstrated its applicability, especially when the available data for model construction is limited, always producing satisfactory results for production forecasting with low computational cost. In addition, it generates a good warm start for high fidelity optimization processes, decreasing the number of simulations by approximately 65%.

Matrix acidization is an important technique used to enhance oil production at the tertiary recovery stage, but its numerical simulation has never been verified. From one of the earliest models, i.e., the two-scale model (Darcy framework), the Darcy–Brinkman–Forchheimer (DBF) framework is developed by adding the Brinkman term and Forchheimer term to the momentum conservation equation. However, in the momentum conservation equation of the DBF framework, porosity is placed outside of the time derivation term, which prevents a good description of the change in porosity. Thus, this work changes the expression so that the modified momentum conservation equation can satisfy Newton’s second law. This modified framework is called the improved DBF framework. Furthermore, based on the improved DBF framework, a thermal DBF framework is given by introducing an energy balance equation to the improved DBF framework. Both of these frameworks are verified by former works through numerical experiments and chemical experiments in labs. Parallelization to the complicated framework codes is also realized, and good scalability can be achieved.

The whole process of the petrochemical industry involves flammable and explosive dangerous goods. The timely discovery of abnormalities or failures in the petrochemical process is crucial to ensure production safety. This paper sets up the approach to build the Digital Twin System (DTs) of a petrochemical process. Specifically, we decompose the petrochemical process into five levels one by one and build a digital twin plug-in for each component of the component layers, and then inversely decouple the process to assemble the DTs layer by layer. As a specific experimental example, the characteristic DTs is proposed to build modules of temperature field and pressure field and flow field, these DT modules are driven by practical industrial sampling data from cracking furnace, and three characteristic DTS modules stated above are integrated to form DTS. Based on the digital twin technology and DTs, we propose the logical structure of chemical process status monitoring and fault diagnosis in detail, which improves the safety and controllability of the petrochemical process.

Because of the significant impact of fractures on production in hydrocarbon reservoirs, identification of these phenomena is a very important issue. Image logs are one of the best tools for revealing and studying fractures in reservoir and researcher can get lots of information about geological features in wells, by studying and analyzing these logs. In this research, two approaches have been used to determine the fractures in two wells A and B located in one of the oil fields in southwest of Iran. In the first approach, using Geolog software (version-7), after processing and correction of raw image log data, the number, position, dip, extension, layering, density and expansion of fractures have been identified. In the second approach, considering that the fractures in FMI images have edges, the Canny and Sobel filters as edge detection operators in image processing have been used to detect fractures in these images.

The effects of nanocatalyst composition and calcination parameters on the performance of the Fe–Mn–Ce ternary nanocatalysts supported on alumina granules in a laboratory fixed bed microreactor have been evaluated. Nanocatalysts were synthesized by incipient wetness impregnation under vacuum method (simultaneous impregnation of metal species). The samples used for hydrogenation of carbon monoxide via Fischer-Tropsch synthesis. The optimum nanocatalyst composition for production of light olefins ( C=2 – C=4 C 2 = - C 4 = $ {\mathrm{C}}_2^{=}-{\mathrm{C}}_4^{=}$ ) from synthesis gas is 75 wt%Fe–20 wt%Mn–5 wt%Ce. The calcination parameters (temperature, time and atmosphere) were investigated and their effects on the structure and performance of the nanocatalysts were determined. The maximum ratio of olefins/(methane + paraffin) and the best activity and selectivity belonged to the nanocatalyst which was calcined in static air at 500 °C for 7 h. The nanocatalyst precursors and calcined samples (fresh and used) were characterized by XRD, N2 physisorption, FE‒SEM, EDAX, MAP, TG, DSC, and H2–TPR. The present study results confirm that the structural, morphological and physic-chemical properties of the nanocatalyst have been impressed with metal species and calcination parameters.

Synthetic plugs are available to understand oilfield properties and the behavior of oil in reservoirs where natural plugs cannot be extracted. Specifically, in cases where it is necessary to reproduce representative mineralogical and petrophysical characteristics from carbonate reservoirs, it is evident that there is a lack of publications focusing on synthetic plug construction. In this work, a methodology to construct synthetic carbonate plugs is proposed using disintegrated carbonate rock with controlled particle size, mixed in different weight fraction, uniaxial compaction with controlled load force velocity, pH, temperature, and bonding materials. Preliminary analysis of consolidation (basic consolidation and consolidation by water immersion test), wettability (contact angle measurements) and petrophysical properties (nitrogen expansion porosimetry measurements and theoretical porosity calculation) are reported in this study to determine which composition of the synthetic samples provides similar properties compared to that expected for natural rocks from carbonate reservoirs. Two compositions are recommended to construct synthetic samples: Composition 1 with a total quantity of 100 g of base material (50% w/w of

The cyclic methane hydrate production method was proposed with CO2 and N2 mixture stimulation. The cyclic production model was established based on actual hydrate reservoir parameters, accordingly, the production characteristics were analyzed, and a sensitivity analysis was conducted. The results show the following: (1) The depressurization mechanism is dominant in the cyclic production. CH4 production and CH4 hydrate dissociation can be greatly enhanced because the cyclic process can effectively reduce the partial pressure of CH4 (gas phase). However, there is a limited effect for CO2 storage. (2) Heat supply is essential for continuous hydrate dissociation. The CH4 hydrate dissociation degree is the highest in the near-wellbore area; in addition, the fluid porosity and effective permeability are significantly improved, and the reservoir temperature is obviously decreased. (3) The initial CH4 hydrate saturation, absolute permeability, intrinsic CO2 hydrate formation kinetic constant, injection time and production time can significantly influence the production performance of the natural gas hydrate reservoir.

Engineered Water Injection (EWI) has been increasingly tested and applied to enhance fluid displacement in reservoirs. The modification of ionic concentration provides interactions with the pore wall, which facilitates the oil mobility. This mechanism in carbonates alters the natural rock wettability being quite an attractive recovery method. Currently, numerical simulation with this injection method remains limited to simplified models based on experimental data. Therefore, this study uses Artificial Neural Networks (ANN) learnability to incorporate the analytical correlation between the ionic combination and the relative permeability (Kr), which depicts the wettability alteration. The ionic composition in the injection system of a Brazilian Pre-Salt benchmark is optimized to maximize the Net Present Value (NPV) of the field. The optimization results indicate the EWI to be the most profitable method for the cases tested. EWI also increased oil recovery by about 8.7% with the same injected amount and reduced the accumulated water production around 52%, compared to the common water injection.

Constructing an accurate geological model of the reservoir is a preliminary to make any reliable prediction of a reservoir’s performance. Afterward, one needs to simulate the flow to predict the reservoir’s dynamic behaviour. This process usually is associated with high computational costs. Therefore, alternative methods such as the percolation approach for rapid estimation of reservoir efficiency are quite desirable. This study tries to address the Well Testing (WT) interpretation of heterogeneous reservoirs, constructed from two extreme permeabilities, 0 and K. In particular, we simulated a drawdown test on typical site percolation mediums, occupied to fraction “p” at a constant rate Q/h, to compute the well-known pressure derivative (dP/dlnt). This derivative provides us with “apparent” permeability values, a significant property to move forward with flow prediction. It is good to mention that the hypothetical wellbore locates in the middle of the reservoir with assumed conditions. Commercial software utilized to perform flow simulations and well test analysis. Next, the pressure recorded against time at different realizations and values of p. With that information provided, the permeability of the medium is obtained. Finally, the permeability change of this reservoir is compared to the permeability alteration of a homogeneous one and following that, its dependency on the model parameters has been analysed. The result shows a power-law relation between average permeability (considering all realizations) and the occupancy probability “p”. This conclusion helps to improve the analysis of well testing for heterogeneous reservoirs with percolation structures.

Liquid biofuels for compression ignition engines are often based on vegetable oils. In order to be used in compression ignition engine the vegetable oils have to be processed because of their high viscosity or it is also possible to use vegetable oils in fuel blends. In order to decrease the viscosity of the fuel blends containing crude vegetable oil the alcohol-based fuel admixtures can be used. The paper describes the effect of rapeseed oil–diesel fuel–n-butanol blends on combustion characteristics and solid particles production of turbocharged compression ignition engine. The 10% and 20% concentrations of n-butanol in the fuel blend were measured and analysed. The engine Zetor 1204, located in tractor Zetor Forterra 8641 with the power of 60kW and direct injection was used for the measurement. The engine was loaded through power take off shaft of the tractor using mobile dynamometer MAHA ZW500. The measurement was carried out in stabilized conditions at 20%, 60% and 100% engine load. The engine speed was kept at 1950 rpm. Tested fuel blends showed lower production of solid particles than diesel fuel and lower peak cylinder pressure and with increasing concentration of n-butanol in the fuel blend the ignition delay was prolonged and premixed phase of combustion was increased.

In this paper, we study the processes of mixing when using the technology of transportation of light oil products-sequential pumping by direct contact. Modeling of mixing processes is carried out taking into account the influence of parametric and thermodynamic factors. For numerical modeling, a software package was developed that allows not only modeling and calculating the parameters of the oil pipeline operation in real time with subsequent graphical visualization, but also comparing them with real data processed by operators at production facilities.

The current practice for crude oil demulsifier selection consists of pre-screening of the best performing demulsifiers followed by field trials to determine the optimum demulsifier dosage. The method of choice for demulsifier ranking is the bottle test. As there is no standard bottle test method, there are different methodologies reported in the literature. In this work, a new approach to bottle test and field trial was described which improved significantly the selection and dosage of the demulsifier. The bottle test was optimized by measuring an accurate mass of demulsifier. This method produces repeatable results. This bottle-test methodology was benchmarked against field trial results performed in oil processing plants. The field trials were also improved to avoid the accumulation effect of demulsifier, when optimizing their dosage. The field data for the optimization of demulsifier dosage was analyzed mathematically; and a graphical method to determine the optimum range is described.

Hydrogen sulfide exists mostly as a detrimental byproduct in the gas processing units as well as refineries, and it must be eliminated from natural gas streams. In a Sulfur Recovery Unit (SRU), hydrogen sulfide is converted into the elemental sulfur during the modified Claus process. Efficiency of sulfur recovery units significantly depends on the reaction furnace temperature. In this work, the effect of oxygen and acid gas enrichment on the reaction furnace temperature and accordingly on sulfur recovery is studied, using both numerical modeling and process simulation. Then, simulation and numerical model are benchmarked against the experimental data of an SRU unit. The validated model provides spotlight on optimizing the upstream sulfur removal unit as well as the oxygen purification process. Two cases of acid gas streams with low and high H2S content, 30% and 50%, are studied to investigate the effect of operating parameters on the overall recovery. Finally, average errors of the models are presented. According to the absolute difference with experimental values, the developed numerical model shows great potential for accurately estimating overall efficiency of the recovery unit.

Reservoir simulation is a powerful technique to predict the amount of produced hydrocarbon. After a solid representation of the natural fracture geometry, an accurate simulation model and a physical reservoir model that account for different flow regimes should be developed. Many models based on dual-continuum approaches presented in the literature rely on the Pseudo-Steady-State (PSS) assumption to model the inter-porosity flow. Due to the low permeability in such reservoirs, the transient period could reach several years. Thus, the PSS assumption becomes unjustified. The numerical solution adopted by the Multiple INteracting Continua (MINC) method was able to simulate the transient effects previously overlooked by dual-continuum approaches. However, its accuracy drops with increasing fracture network complexity. A special treatment of the MINC method, i.e., the MINC Proximity Function (MINC–PF) was introduced to address the latter problem. And yet, the MINC–PF suffers a limitation that arises from the existence of several grid-blocks within a studied cell. In this work, this limitation is discussed and two possible solutions (transmissibility recalculation/adjusting the Proximity Function by accounting for nearby fractures) are put forward. Both proposed methods have demonstrated their applicability and effectiveness once compared to a reference solution.

The present study focuses on the catalytic conversion of syngas (CO + H2) through Fischer–Tropsch (FT) route using two identically prepared 0.1 wt.% palladium promoted Mesoporous Alumina (MA) and SBA–15 supported Co (15 wt.%) catalysts. The Fischer–Tropsch activity is performed in a fixed bed tubular reactor at temperature 220 °C and pressure 30 bar with H2/CO ratio ~2 having Gas Hourly Space Velocity (GHSV) of 500 h−1. Detail characterizations of the catalysts are carried out using different analytical techniques like N2 adsorption-desorption, Temperature-programmed reduction with hydrogen (H2-TPR), Temperature-programmed desorption with NH3 (NH3-TPD), X-Ray Diffraction (XRD), and Transmission Electron Microscopy (TEM). The results show that the SBA–15 supported catalyst exhibits higher C6–C12 selectivity (57.5%), and MA supported catalyst facilitates the formation of higher hydrocarbons (C13–C20) having a selectivity of 46.7%. This study attributes the use of both the support materials for the production of liquid hydrocarbons through FT synthesis.

Rigorous packed-bed absorber modeling and simulation are significant for post-combustion CO2 capture processes design. Hence, a good knowledge and judicious selection of model parameters are essential to ensure reliable predictions. In this paper, the reactive absorption of CO2 into loaded aqueous monoethanolamine solution was modeled, furthermore, the effects of five different parameters (kinetic model, enhancement factor, enthalpy of absorption, CO2 diffusivity, and vapor pressure) were investigated. Finally, this study revealed that some model parameters have a large influence on the column performance, contrary to others. In addition, methods and correlations that generally provide more accurate predictions of the empirical data relative to the other cases involved in this research were determined for each model parameter. It was also found that the model deviation was reduced by 18% and 4% for the liquid temperature and liquids CO2 loading profiles, respectively, while comparing between the worst and the best case.

The precise landing and steering of horizontal wells using conventional mudlogging and Logging While Drilling (LWD) data is a particular challenge for the Lebăda Field, offshore Romania. The use of a new technique of elemental geochemistry analysis (or chemosteering) became an option for the identification of Cenomanian, Turonian–Coniacian–Santonian, Campanian and Eocene strata. This has enabled more accurate placement of the horizontal development wells within the desired reservoir target interval. Geochemical data enabled the identification of chemostratigraphic zones C1, C2, C3 and zone R that correspond to the reservoir section. The application is a result of the geochemical zonation performed using elements and ratios that are sensitive to depositional environment, sea level change, heavy mineral concentrations and siliciclastic input namely: Sr/Ca, Zr/Th, Si/Zr and Si/K. In ascending stratigraphic order, the ratio thresholds of zone C3 are Zr/Th > 11, Sr/Ca > 1.1, Si/Zr < 22 and Si/K < 19, while zone R corresponds to 5.5 < Zr/Th < 11, Sr/Ca < 1.1, Si/Zr > 22 and Si/K > 19. C2 zone is defined by Zr/Th < 5.5, Sr/Ca > 1.1, Si/Zr < 22 and Si/K < 19 and C1 zone is characterized by Si/Zr > 22 and Si/K > 19. The selected geochemical ratios indicate a strong geochemical zonation. In the case of offset wells, 85.9% of the data confirmed the proposed classification and 89.4% for the real-time application case. The zone R shows a strong contrast with the surrounding formations facilitating critical decisions during well placement and geosteering, increasing the reservoir exposure by 28%. The quantitative approach delivered very valuable results, providing a solid foundation to define correlation and well landing intervals. Simultaneously, the cost of the method represents a fraction of the LWD cost and 0.15% of the total project cost, making it very cost effective and a standard approach for future projects.

In China, Tahe Triassic oil field block 9 reservoir was discovered in 2002 by drilling wells S95 and S100. The distribution of the reservoir sand body is not clear. Therefore, it is necessary to study and to predict oil production from this oil field. In this study, we propose an improved Random Vector Functional Link (RVFL) network to predict oil production from Tahe oil field in China. The Spherical Search Optimizer (SSO) is applied to optimize the RVFL and to enhance its performance, where SSO works as a local search method that improved the parameters of the RVFL. We used a historical dataset of this oil field from 2002 to 2014 collected by a local partner. Our proposed model, called SSO-RVFL, has been evaluated with extensive comparisons to several optimization methods. The outcomes showed that, SSO-RVFL achieved accurate predictions and the SSO outperformed several optimization methods.

A new generation improved oil recovery methods comes from combining techniques to make the overall process of oil recovery more efficient. One of the most promising methods is combined Low Salinity Surfactant (LSS) flooding. Low salinity brine injection has proven by numerous laboratory core flood experiments to give a moderate increase in oil recovery. Current research shows that this method may be further enhanced by introduction of surfactants optimized for lowsal environment by reducing the interfacial tension. Researchers have suggested different mechanisms in the literature such as pH variation, fines migration, multi-component ionic exchange, interfacial tension reduction and wettability alteration for improved oil recovery during lowsal injection. In this study, surfactant solubility in lowsal brine was examined by bottle test experiments. A series of core displacement experiments was conducted on nine crude oil aged Berea core plugs that were designed to determine the impact of brine composition, wettability alteration, Low Salinity Water (LSW) and LSS flooding on Enhancing Oil Recovery (EOR). Laboratory core flooding experiments were conducted on the samples in a heating cabinet at 60 °C using five different brine compositions with different concentrations of NaCl, CaCl2 and MgCl2. The samples were first reached to initial water saturation, Swi, by injecting connate water (high salinity water). LSW injection followed by LSS flooding performed on the samples to obtain the irreducible oil saturation. The results showed a significant potential of oil recovery with maximum additional recovery of 7% Original Oil in Place (OOIP) by injection of LS water (10% LS brine and 90% distilled water) into water-wet cores compared to high salinity waterflooding. It is also concluded that oil recovery increases as wettability changes from water-wet to neutral-wet regardless of the salinity compositions. A reduction in residual oil saturation, Sor, by 1.1–4.8% occurred for various brine compositions after LSS flooding in tertiary recovery mode. The absence of clay swelling and fine migration has been confirmed by the stable differential pressure recorded for both LSW and LSS flooding. Aging the samples at high temperature prevented the problem of fines production. Combined LSS flooding resulted in an additional oil recovery of 9.2% OOIP when applied after LSW flooding. Surfactants improved the oil recovery by reducing the oil-water interfacial tension. In addition, lowsal environment decreased the surfactant retention, thus led to successful LSS flooding. The results showed that combined LSS flooding may be one of the most promising methods in EOR. This hybrid improved oil recovery method is economically more attractive and feasible compared to separate low salinity waterflooding or surfactant flooding.

This contribution deals with about selective conversion of heavy gas oils into middle distillates fuels that meet ultra-low sulfur and aromatic compound quality standards by using a novel NiWRu/TiO2–γAl2O3 catalyst under typical hydrotreatment conditions. A diesel fuel fraction having sulfur, nitrogen and aromatics compound content of about 50 ppm, 10 ppm and 15 v%, respectively, was obtained when the reactor was operated at T = 370 °C, P = 12.4 MPa, LHSV = 0.5 h−1 and H2/hydrocarbon ratio = 800 Nm3/m3. Titanium and ruthenium additives used in the preparation of the NiWRu/TiO2–γAl2O3 catalyst, remarkably improved the catalytic activities for the hydrogenolysis, hydrogenation and hydrocracking reactions compared to the reference NiW/γAl2O3 catalyst. The coprecipitation of titanium and aluminum hydroxides produced a catalyst support having greater surface area, pore volume and surface acidity. An improvement in mechanical properties of the support extrudates was also observed. Characterization analysis by XPS, AUGER and XRD techniques of the TiO2–γAl2O3 support suggested the formation of an aluminum-titanate mixed phase (AlxTiyOz) having a non-well-defined stoichiometry. The NiW/TiO2–γAl2O3 and NiWRu/TiO2–γAl2O3 exhibited a greater surface dispersion of the supported nickel and tungsten species compared to the NiW/γAl2O3 catalyst. The promoter effect of ruthenium on the NiW bimetallic system caused a strong increase in both hydrogenolysis and hydrogenation reactions. Hydrodenitrogenation and hydrocracking reactions were also favored by the increase in the hydrogenation capacity and in the surface acidity of the catalyst. The highest conversion levels for all investigated reactions were obtained when the NiWRu/TiO2–γAl2O3 catalyst was prepared by co-impregnation of Ni and Ru in a second step. This catalyst showed sulfur tolerance properties when the reaction was conducted in the presence of different H2S partial pressures. The catalytic behavior of the NiWRu/TiO2–γAl2O3 catalyst was explained by the existence of a promoting effect between separated Ni and Ru sulfides species and the NiWS phase (dual mechanism).

Pressure response behavior of two-layered reservoir with a vertical mixed boundary is easy to be mistaken for that of the radial composite reservoir or dual-pore reservoir. It is difficult to fit the pressure response curve and easy to obtain abnormal parameter values using a misunderstood model. In this paper, we present the interpretation of three different types of pressure responses of vertical mixed boundary reservoir by our proposed models, where the diagnostic window and feature value are captured for different mixed boundary types. Results show that the mixed boundary with closed boundary and infinite-acting boundary induces the fake pressure response of a radial composite reservoir with poor permeability outer zone. The mixed boundary with the main constant-pressure and non-main closed boundary produces a fake pressure response of a dual-porosity reservoir. The diagnostic window of pressure response curves shape can easily capture the mixed boundary type, and the feature value of the feature values of pressure response value can quickly obtain the permeability ration of one layer. Aiming at different representative types of pressure response cases in the western Sichuan XC gas field, China, we innovatively analyze them from a different perspective and get a new understanding of pressure response behavior of vertical mixed boundary, which provides a guideline for the interpretation of layered oil and gas reservoir with the complex boundary in the vertical direction.

The Electrical Submersible Pumping (ESP) system is one of the most commonly used artificial lift methods in the petroleum industry and one recent breakthrough in this system is enclosed in a capsule and positioned on the seabed in a skid. As it is a recent technology, with only a small amount of equipment currently in operation, there is a clear need for a greater understanding of the flow within this geometry with the objective of perfecting the design of this promising submarine boosting system. This paper presents a numerical investigation of single-phase flow within the scaled capsule-intake of an ESP system in the Skid considering a model with geometric and dynamic similarities in relation to a real equipment in operation in the Espadarte field, located in the Campos Basin, Brazil. The tridimensional and transient simulation for a case for one mass flow rate and inclination angles are investigated. While neglecting the effects of the diffuser and impeller in the system, the flow field features, axial and radial velocity profiles in the intake region were computed. The numerical results show that the flow in the intake region is dominated by the secondary flow, leading to the formation of bathtub vortex. It is expected that the vortices influence the flow pattern in the intake region, breaking the larger bubbles into smaller bubbles, making the transition from the slug flow pattern to the dispersed bubbles or bubbly pattern in which it would be more difficult to be dragged into the intake.

Circulation loss is one of the most serious and complex hindrances for normal and safe drilling operations. Detecting the layer at which the circulation loss has occurred is important for formulating technical measures related to leakage prevention and plugging and reducing the wastage because of circulation loss as much as possible. Unfortunately, because of the lack of a general method for predicting the potential location of circulation loss during drilling, most current procedures depend on the plugging test. Therefore, the aim of this study was to use an Artificial Intelligence (AI)-based method to screen and process the historical data of 240 wells and 1029 original well loss cases in a localized area of southwestern China and to perform data mining. Using comparative analysis involving the Genetic Algorithm-Back Propagation (GA-BP) neural network and random forest optimization algorithms, we proposed an efficient real-time model for predicting leakage layer locations. For this purpose, data processing and correlation analysis were first performed using existing data to improve the effects of data mining. The well history data was then divided into training and testing sets in a 3:1 ratio. The parameter values of the BP were then corrected as per the network training error, resulting in the final output of a prediction value with a globally optimal solution. The standard random forest model is a particularly capable model that can deal with high-dimensional data without feature selection. To evaluate and confirm the generated model, the model is applied to eight oil wells in a well site in southwestern China. Empirical results demonstrate that the proposed method can satisfy the requirements of actual application to drilling and plugging operations and is able to accurately predict the locations of leakage layers.

In this paper, two methods of kernel bandwidth and wavelet transform are used for simultaneous upscaling of two features of hydrocarbon reservoir. In the bandwidth method, the criterion for upscaling is the cell variability, and by calculating the optimal bandwidth and determining the distance matrix, the upscaling process is performed in a completely non-uniform and unregularly manner. In areas with extreme variability, the bandwidth is considered small enough to maintain the fine scale characteristics of model. Conversely in homogenous areas, with the choice of large bandwidth, the maximum rate of upscaling will occur. The bandwidth upscaling algorithm is an iterative and hierarchical algorithm. The bandwidth method, unlike conventional scale-up methods, focuses on how to upgrid cells and, by determining the optimal averaging window, we will have the least loss information for the fine scale model. Upscaling is a pre-processing to building a simulator model with lower cell number, and thus, reducing volume and computational cost, while maintaining and retaining the basic information of the fine model. Due to the various variability of the reservoir features, the attribute upscaling pattern differs, and in order to show the variability of two features in the upscaling model simultaneously, it is suggested in this paper to upscale two features simultaneously. For simultaneous upscaling, we applied two different approaches; minimum and maximum bandwidth. Moreover, wavelet transformation is applied to upscaling the model. Then, as a result, the variance of the scale-up models based on wavelet is about one-third of the variance of the bandwidth method. Simulation results show that the bandwidth method is a good approach for upscaling the heterogeneous reservoirs.

The exploitation of our forests generates waste, amongst which sawdust produces approximately cubic meter per year. The objective of this work is to contribute to the improvement of the recovery process of this waste through the optimization of the pre-treatment stage of sawdust from Ayous (Triplochiton scleroxylon) by the organosolv process in order to produce bioethanol. To achieve this objective, Ayous sawdust was sampled and then characterized, followed by the pre-treatment through organosolv process. During pre-treatment, a composite experimental design centred on three factors (temperature, time, ethanol concentration) was used to study their effects on extraction of pentoses, reducing sugars and phenolic compounds. Analysis shows that Ayous sawdust contains 45.33 ± 5.5% cellulose, 30.32 ± 1.95% lignin and 20.03 ± 3.5% hemicellulose. To release the maximum of pentoses, reducing sugars and the minimum of phenolic compounds, an organosolv pre-treatment of this substrate should be carried out at 209.08 °C for 47.60 min with an ethanol–water ratio of 24.02%. Temperature is the factor having the most positive influence on the pre-treatment process whereas, ethanol concentration is not an essential factor. Organosolv pre-treatment is an effective process for delignification of the lignocellulosic structure of Ayous sawdust.

The transition from stratified to intermittent air-water two-phase flow was investigated experimentally, by flow visualization and pressure drop signals analyses, in a 30 mm ID pipe. The intermittent flow’s onset was found to be mainly dependent on the liquid superficial velocity and the pipe diameter. Plug flow, Less Aerated Slug (LAS) or Highly Aerated Slug (HAS) flows could be obtained on the gas superficial velocity grounds. The available models, compared to experiments, could not predict adequately the intermittent flow onset. The appearance of liquid slugs was revealed by peaks in the pressure drop signal. Furthermore, it was shown that the available slug frequency correlations were not valid in the zone of the onset of intermittent flow.

Crude oil is one of the most powerful types of energy and the fluctuation of its price influences the global economy. Therefore, building a scientific model to accurately predict the price of crude oil is significant for investors, governments and researchers. However, the nonlinearity and nonstationarity of crude oil prices make it a challenging task for forecasting time series accurately. To handle the issue, this paper proposed a novel forecasting approach for crude oil prices that combines Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Long Short-Term Memory (LSTM) with attention mechanism and addition, following the well-known “decomposition and ensemble” framework. In addition, a news sentiment index based on Chinese crude oil news texts was constructed and added to the prediction of crude oil prices. And we made full use of attention mechanism to better integrate price series and sentiment series according to the characteristics of each component. To validate the performance of the proposed CEEMDAN-LSTM_att-ADD, we selected the Mean Absolute Percent Error (MAPE), the Root Mean Squared Error (RMSE) and the Diebold-Mariano (DM) statistic as evaluation criterias. Abundant experiments were conducted on West Texas Intermediate (WTI) spot crude oil prices. The proposed approach outperformed several state-of-the-art methods for forecasting crude oil prices, which proved the effectiveness of the CEEMDAN-LSTM_att-ADD with the news sentiment index.

Drilling fluid loss always occurs in fracture-porosity reservoirs and it causes severe problems. To reduce and prevent lost circulation, it is important to get to know the cause and the characteristic of drilling fluid loss. According to the approach in the reservoir simulation and well test analysis, a new model for drilling fluid loss in fracture-porosity reservoir is presented. Multi fractures in the formation and drilling fluid seepage between fracture and rock matrix have been considered in the model. The governing equations are derived based on the principle of conservation of mass. The model is solved numerically using Newton-Raphson iterative method. The obtained results indicate that drilling fluid leak-off has great influence on the total leakage volume. It is necessary to consider the impact of the drilling fluid leak-off. In addition, influence of formation properties, such as fracture stiffness, rock matrix porosity, rock matrix permeability, and operation factors, such as pressure difference between wellbore and formation, are also analysed in detail in the paper which could help better understand the factors that influence the drilling fluid loss during drilling operation.

Carbon dioxide miscible flooding has become one of the important technologies for improving oil recovery. The Minimum Miscible Pressure (MMP) is the key parameter to realize miscible flooding. As the MMP in the research area is higher than the formation fracture pressure, miscible flooding cannot be formed. To address this problem, it is necessary to find a way to reduce the MMP. Citric acid isobutyl ester is chosen to reduce the MMP of carbon dioxide and crude oil in this research. The effect of citric acid isobutyl ester on reducing the MMP was measured by the method of long-slim-tube displacement experiment. The experiment results show that the MMP is 29.6 MPa and can be obviously reduced by injecting the slug of citric acid isobutyl ester. The MMP could decrease gradually with constantly adding the injected slug of citric acid isobutyl ester, but the decrease becomes smaller and smaller. The optimum injected slug size of the chemical reagent is 0.003 PV. Under the condition of the slug size, the MMP is reduced to 23.5 MPa and the reduction is 6.1 MPa.

Energy is vital to the profitable growth of every nation and to stimulate new research. Only natural resources can meet the growing energy demand in recent years, biodiesel has become very interested in the energy as well as environmental advantages that it can be combined with mineral diesel fuel in any quantity. The research focuses on the study of the replacement of diesel with a safflower methyl ester. The engine tests shall be performed using the safflower methyl ester as fuel in the DI diesel engine. The combustion, emission and performance characteristics were studied using alternative fuels and mixtures. SAfflower Methyl Ester 80% (SAME80) and SAME100 have high heat release rates. Nitrogen oxides were higher by about 50%, carbon monoxide decreased by 10%, unburnt hydrocarbon was slightly higher and the thermal efficiency was higher for the SAME than for diesel fuel.

A methodology is suggested for the explicit computation of the absolute permeability and Knudsen diffusion coefficient of tight rocks (shales) from pore structure properties. The pore space is regarded as a pore-and-throat network quantified by the statistical moments of bimodal pore and throat size distributions, pore shape factors, and pore accessibility function. With the aid of percolation theory, analytic equations are developed to express the nitrogen (N2) adsorption/desorption isotherms and mercury (Hg) intrusion curve as functions of all pertinent pore structure parameters. A multistep procedure is adopted for the successive estimation of each set of parameters by the inverse modeling of N2 adsorption–desorption isotherms, and Hg intrusion curve. With the aid of critical path analysis of percolation theory, the absolute permeability and Knudsen diffusion coefficient are computed as functions of estimated pore network properties. Application of the methodology to the datasets of several shale samples enables us to evaluate the predictability of the approach.

H2SO4-catalysed isobutane alkylation with alkenes is an important industrial process used to obtain high-octane alkylate. In this process, the concentration of H2SO4 is one of the main parameters. For alkylation, sulphuric acid containing 88%–98% monohydrate is typically used. However, only a H2SO4 concentration of 95%–96% enables alkylate with the maximum octane number to be obtained. Changes in H2SO4 concentration due to decontamination are the main cause of process variations. Therefore, it is necessary to maintain the reactor acid concentration at a constant level by regulating the supply of fresh catalyst and pumping out any spent acid. The main reasons for the decrease in the H2SO4 concentration are accumulation of high-molecular organic compounds and dilution by water. One way to improve and predict unsteady alkylation processes is to develop a mathematical model that considers catalyst deactivation. In the present work, the formation reactions of undesired substances were used in the description of the alkylation process, indicating the sensitivity of the prediction to H2SO4 activity variations. This was used for calculation the optimal technological modes ensuring the maximum selectivity and stability of the chemical–technological system under varying hydrocarbon feedstock compositions.

The article discusses effective ways to reduce the cost of operating vapor recovery units and increase the financial result of their operation. The first method is based on regulation of the power-on time of the installation. The second method is based on using the potential energy of the fluid flow of the gravity section to supply the system equipment with energy. The potential savings on VRU maintenance will reduce the risks of payback of installations. The proposed methods will have a significant impact on society, as the possibility of a wider distribution of installations that protect the environment from emissions of volatile organic compounds into the atmosphere will become available.

Carbonate reservoirs are of great importance due to having many fractures and the effectiveness of these fractures in oil production. The most effective tools for studying fractures are image logs that capture high resolution images from the well. An example of these images is the FMI tool, which provide important information on the orientation, depth, and type of fracture. Today, the detection of fractures on these logs is done manually, which in the absence of sufficient experience, will encounter errors. The purpose of this study is to identify the reservoir fractures and the dips of the fractures using Canny edge detection algorithm and Hough transform algorithm and image processing operators, so that in the first stage, fractures are identified in Geolog Software and in the second stage, using MATLAB Software, fractures and their dip are interpreted.

One of the most widely used way to improve low-temperature properties of diesel fuels is the use of additives. However, a variety of additives and the effect of susceptibility make it difficult to select additive for a particular composition of diesel fuel and operating conditions. The laws of interaction between functional groups of additives and hydrocarbons of the diesel fraction have not been investigated yet. The article discusses the influence of fractional, group and structural-group composition of straight-run diesel fuels on the effectiveness of cold flow improvers. The effect of additives concentration on the effectiveness of their action is considered. It was shown that when selecting a cold flow improver for diesel fuel and determining its optimal concentration, it is necessary to take into account the optimal content of various groups of hydrocarbons in diesel fuel, at which a cold flow improver is most effective.

Authigenic chlorite, which is frequently found in sandstone, has a controlling effect on the reservoirs in which tight oil is adsorbed during hydrocarbon filling. In this study, the content, occurrence state, timing, mechanism and influence of authigenic chlorite on the micro-occurrence states of tight oil were studied using Thin Section (TS), Fluorescent Thin Section (FTS), X-Ray Diffraction (XRD), Field Emission-Scanning Electron Microscopy (FE-SEM), Environmental Scanning Electron Microscopy (ESEM), and Energy Dispersive Spectroscopy (EDS). The results indicate: (1) a spatial coupling between chlorite development, a brackish water delta front facies depositional environment, and biotite-rich arkosic sandstone. (2) Authigenic chlorite can be divided into three types: grain-coating chlorite, pore-lining chlorite, and rosette chlorite. Chlorite forms after early compaction but before other diagenetic phases, and grows via precipitation from pore waters that contain products released during the dissolution of volcanic rock fragments and biotites. Porewater is also pressure-released from feldspars and mudstone. (3) The micro-occurrence states of tight oil can be divided into five types: emulsion form, cluster form, throat form, thin-film form, and the isolated or agglomerated particle form. (4) During hydrocarbon filling, tight oil mainly occurs on the surface of grain-coating and pore-lining chlorite in the form of a thin film, the granular or agglomerated forms are mainly enriched within the intercrystalline pores within the authigenic chlorite, and the cluster forms are mainly enriched in dissolution pores. Isolated or agglomerated particles of tight oil primarily occur in the intercrystalline pores of the rosette chlorite. (5) The specific surface area and the authigenic chlorite’s adsorption potential of authigenic chlorite control the micro-occurrence of tight oil on the surface of the chlorite and in intercrystalline pores. The adsorption capacity of chlorite lies in the following order: pore-lining chlorite intercrystalline pores > rosette chlorite > chlorite in feldspar dissolution pores > pore-lining chlorite surface > grain-coating chlorite intercrystalline pores > grain-coating chlorite surface.

This study estimates the shear friction coefficient from shear friction angles for the prediction of slip tendencies in the Tuy Hoa–Vung Tau region of Southern Vietnam. A dataset consisting of measured data of 355 fractured planes, striations, and unconformities in coastal areas as well as 239 offshore faults was analyzed based on the principles of statistical probability. As a result, 138 friction angles for the onshore and offshore faults were calculated based on shear fracture conjugate pairs. The goodness-of-fit test was used to define the probability distribution of the friction angles, which had a normal distribution. The acceptable average of friction angles for the onshore region with a reliability of more than 95% were in the range of 25.8–31.5°, which corresponds to frictional coefficients of 0.48–0.61. The acceptable average friction angles for the offshore region were relatively low at 23–31°, which corresponds to a frictional coefficient of 0.42–0.60. Owing to the heterogeneity of the fault system, the median value (19.12°) should be used as the lowest threshold value for slipping faults at all conditions. The recommended applicable average friction angles are 28.65° and 27° for the onshore and offshore regions, respectively. The estimation of the frictional coefficients is highly reliable, and it can be applied to other subsurface resource exploitation projects within the study area.

When oil fields fall during their lifetime below the bubble point gas comes out of solution. The key questions are at which saturation the gas becomes mobile (“critical gas saturation”) and what the gas mobility is, because mobile gas reduces the production of oil significantly. The traditional view is that the gas phase becomes mobile once gas bubbles grow or expand to a size where they connect and form a percolating path. For typical 3D porous media the saturation corresponding to this percolation limit is on the order of 20%. However, significant literature report on gas mobility below lower limits of percolation thresholds i.e. below 0.1%. A direct experimental insight for that is lacking because laboratory measurements are notoriously difficult since the formation of gas bubbles below the bubble point includes thermodynamic and kinetic aspects, and the pressure decline rates achievable in laboratory experiments are orders of magnitude higher than the decline rates in the field. Here we study the nucleation and transport of gas coming out of solution in-situ in 3D rock using X-ray computed micro tomography which allows direct visualization of the nucleation kinetics and connectivity of gas. We use either propane or a propane–decane mixture as model system and conduct pressure depletion in absence of flow finding that – consistent with the literature – observation of the bubble point in the porous medium is decreased and becomes pressure decline rate dependent because of the bubble nucleation kinetics. That occurs in single-component systems and in hydrocarbon mixtures. Pressure depletion in absence of flow results in critical gas saturations between 20 and 30% which is consistent with typical percolation thresholds in 3D porous structures. That does not explain experimentally observed critical gas saturations significantly below 20%. Also, the respective pore level fluid occupancy where pores are filled with either gas or liquid phase but not partially with both as in normal 2-phase immiscible systems rather diminishes connectivity of gas and liquid phases. This observation indicates that likely other mechanisms play a role in establishing gas mobility at saturations significantly below 20%. Experiments under flow conditions, where gas is injected near the bubble point suggest that diffusion may significantly contribute to the transport of gas and may even be the dominant transport mechanism at field relevant flow rates. The consequence of diffusive transport are compositional gradients where locally the composition is such gas nucleation may occur. That would lead to a disconnected but mobile gas distribution ahead of the convective front. Furthermore, diffusive exchange leads to ripening and anti-ripening effects which influences the distribution for which we see evidence in pressure depletion experiments but not so much at low rate gas injection. Respective relative permeability computed from the imaged fluid distributions using a lattice Boltzmann approach show distinctly different behavior between pressure depletion and flowing conditions. These findings suggest that capillarity in a gas–liquid hydrocarbon mixture is far more complex than in a 2-phase immiscible system. Capillarity is coupled to phase behavior thermodynamics and kinetics on a fast time scale and diffusion-dominated mechanisms such as ripening and anti-ripening effects at a slow time scale. While the consequences for the current experimental and field modelling approaches are not yet fully clear, this shows that more research is needed to fully understand these effects and their implications.

Well placement planning is one of the challenging issues in any field development plan. Reservoir engineers always confront the problem that which point of the field should be drilled to achieve the highest recovery factor and/or maximum sweep efficiency. In this paper, we use Reservoir Opportunity Index (ROI) as a spatial measure of productivity potential for greenfields, which hybridizes the reservoir static properties, and for brownfields, ROI is replaced by Dynamic Measure (DM), which takes into account the current dynamic properties in addition to static properties. The purpose of using these criteria is to diminish the search region of optimization algorithms and as a consequence, reduce the computational time and cost of optimization, which are the main challenges in well placement optimization problems. However, considering the significant subsurface uncertainty, a probabilistic definition of ROI (SROI) or DM (SDM) is needed, since there exists an infinite number of possible distribution maps of static and/or dynamic properties. To build SROI or SDM maps, the k-means clustering technique is used to extract a limited number of characteristic realizations that can reasonably span the uncertainties. In addition, to determine the optimum number of clustered realizations, Higher-Order Singular Value Decomposition (HOSVD) method is applied which can also compress the data for large models in a lower-dimensional space. Additionally, we introduce the multiscale spatial density of ROI or DM (D2ROI and D2DM), which can distinguish between regions of high SROI (or SDM) in arbitrary neighborhood windows from the local SROI (or SDM) maxima with low values in the vicinity. Generally, we develop and implement a new systematic approach for well placement optimization for both green and brownfields on a synthetic reservoir model. This approach relies on the utilization of multi-scale maps of SROI and SDM to improve the initial guess for optimization algorithm. Narrowing down the search region for optimization algorithm can substantially speed up the convergence and hence the computational cost would be reduced by a factor of 4.