Nuhu Ayuba Chemical EngineeringLuciano Silva da Silva Computer EngineeringToni Jefferson Lopes Food Engineering
8页
查看更多>>摘要：In water lubricated transportation of heavy crude oil, fouling monitoring on the walls of the pipe is fundamental, since it reflects in the cost of transportation. Although such phenomenon has been discussed by many researchers, more of experimental and theoretical evaluations have been carried out than numerical ones. For this reason, this work was aimed at using laminar Level-set (numerical method) to identify oil fouling (through oil density magnitude identification) on the upper and lower walls of a round horizontal pipe during water lubricated transportation. In order to achieve such objective, fluid constants (found in literature) and operational conditions established experimentally were applied to simulate and observe the density flow profiles along the upper and lower walls of a 2D pipe. Prior to the simulation process, a grid convergence test was carried out in order to establish a mesh which was capable of representing the flow characteristics, and at the same time reducing computational cost. Additionally, laminar Level-set was validated through comparing Reynolds numbers obtained from its application to analytical values calculated at the same conditions. Two main volumetric flow profiles (plug and core-annular flow-CAF) with their respective density profiles were obtained. In both cases, oil fouling was identified at specific regions of the pipe's upper and lower walls, presenting densities closer to 918.8 kg/m3.
查看更多>>摘要：We study thermal stimulation and huff and puffin a homogeneous model with a single heterogeneous layer using numerical simulation. This included investigating the response of the dissociation front and the volume of dissociated methane to variations in the depth of the injector well and the permeability of the heterogeneity during thermal stimulation. The sensitivity analysis around the permeability of the heterogeneity demonstrated that the vertical extent of the dissociation front was maximum when the permeability of the heterogeneity matched the permeability of the background medium. Reducing the permeability of the heterogeneity below the background permeability compromised overall fluid flow whereas increasing the permeability, redirected the fluid flow radially into the lateral heterogeneity. The sensitivity analysis for well depth was conducted for a permeable heterogeneity as well as a relatively impermeable heterogeneity. For the permeable case, it was found that maximum radial extent of the dissociated front was observed when the injector well was placed within the heterogeneous layer. For the impermeable case, a significant reduction in radial extent was observed at well depths close to the heterogeneity, and the highest dissociated volumes were recorded for well depths away from the heterogeneity. Subsequently, production was simulated within the reservoir using huff and puff to study the performance of the reservoir during production. Interestingly, it was observed that the case with a permeable heterogeneity underperformed the other cases with respect to the production of gas.
查看更多>>摘要：Steam-assisted gravity drainage (SAGD) has become a widely used thermal method for developing heavy oil reservoirs. The accurate estimation of steam chamber expansion over the entire life of the SAGD process is very important to forecast its performance correctly. In this study, the concave parabola steam chamber geometry analytical model is expanded to include the rise and confinement stage of SAGD. Based on Darcy's law and material balance, analytical models in the rise and confinement stage of the steam chamber were established to estimate the oil production rate with time respectively. The energy balance is then used to estimate the SOR for different stages. The developed analytical models for different stages of SAGD are combined to obtain a comprehensive multi-stage model. The model is then validated against the experimental data obtained by Cheng and Butler and a numerical simulation with CMG-STARS. The comparison proves that the newly proposed model is more accurate than the previous model. After verifying the accuracy of the proposed model, some important production indicators of the SAGD process in different stages, such as oil production rate, cumulative production and effective height, and energy analysis during different stages of the SAGD process are discussed respectively. The influence of different parameters on the whole process of SAGD is discussed finally. The model proposed in this paper is significant for guiding the actual development of SAGD process in oil fields.
查看更多>>摘要：pEDFM is a newly developed numerical simulation framework for mass transfer in fractured reservoirs, and this paper aims to study the application of the pEDFM framework to numerical simulation of two-phase heat and mass transfer in fractured reservoirs. Firstly, the finite volume method is used to discretize the mass and energy conservative equations. Then, all the connections between control volumes including two types of fracture-matrix (f-m), three types of fracture-fracture (f-f) and one type of matrix-matrix (m-m) connections are constructed, and corresponding transmissibility formulas of mass and heat transfer in finite-volume discrete schemes for these connections are given, and Newton iteration method is used to solve the fully implicit coupled discrete equations to obtain cell temperature, pressure and water saturation. Finally, two numerical examples including multiphase flow across high-conductivity fractures and flow barriers are implemented to show that pEDFM can eliminate the errors in EDFM for the calculated temperature profiles. An application case that applies waterflooding to a fractured reservoir model with a fractured horizontal well, four water injection wells, natural fractures and a fault is considered to show that, compared with EDFM, pEDFM can more accurately and effectively handle the numerical simulation of mass and heat transfer in realistic fractured reservoirs with complex geological conditions.
查看更多>>摘要：Electrical conductivity/resistivity is one of the key petrophysical parameters for well-log interpretation. However, in the shale formations, the fluid saturation determined from the well-known Archie-related equations is inaccurate. The commonly accepted reason is that clays within shale formations provide Cation Exchange Capacity (CEC) and additional surficial conduction pathways that are not properly accounted for in water saturation equations leading to the so-called "non-Archie" phenomenon. To investigate this, the Archie parameters were determined for 5 shale samples with CEC controlled by folly saturating different levels of pore water salinity. The electrical conductivity measurement underwent 2800 psi confining pressure to simulate reservoir conditions. The effective porosity was determined by comparing the sample weight in both dry and fully saturated states. Nuclear Magnetic Resonance (NMR) was used for the pore size distribution investigation. Only a small change in Archie's cementation exponent m was observed for different porewater salinities (0.1-0.15) indicating a minor contribution from CEC for shale samples, however, the change in pore water conductivity leads to altered electrical conduction pathways consistent with a volume averaging approach. In contradiction with commonly held belief, it is shown that the rock bulk conductivity and likewise Archie's cementation exponent, m, is not monotonically increasing with the pore water conductivity and therefore CEC has a minor effect on Archie's cementation exponent. This implies that confining pressure and therefore depth, is the main cause of the non-Archie phenomenon.
Renan Vieira BelaSinesio PescoAbelardo Borges Barreto Jr
14页
查看更多>>摘要：One of the main purposes for conducting well tests is to obtain information about reservoir parameters, such as its permeability and the existence of skin effects. Determining individual layer properties from pressure transient data in multilayer reservoirs is challenging, since pressure behavior is influenced by the properties of all layers. This work presents three methods for estimating layer properties from well testing data in multilayer reservoirs with multilateral wells. First, we extend two existing graphical straight-line methods for estimating individual layer properties in multilayer systems with vertical wells to stratified reservoirs with multilateral horizontal wells. These techniques are the rate-normalized pressure analysis and the delta transient method. Both methods require a clear identification of radial flow regimes, which may not occur in a practical case. Additionally, we show that a computer-assisted history matching method based on the Nelder-Mead optimization algorithm can also be used to evaluate layer permeabilities and skin. This optimization method does not rely on the identification of any specific flow regime. Estimates obtained from the graphical methods were used as initial guess for the assisted history matching. The proposed techniques are applied on a set of synthetic well-test cases, where pressure and layer flow-rate profiles are computed from an existing analytical model. Results show that all three methods are able to yield good estimates for layer properties if both early-and late-time radial flow are observed. In cases where only one of the radial flow regimes is identified, then the NM algorithm provides the best results, showing that the assisted history matching improved the estimates provided by the graphical method.
查看更多>>摘要：Identifying reservoir fractures has been a challenge due to its significant influence in drilling and production, especially in highly complex carbonate reservoirs. In this paper, one of the well-known carbonate reservoirs, Asmari reservoir located in the Middle East, was considered and its fracture zones were classified as a machine learning nonlinear problem. First, a dataset was created which included conventional logs and fracture points from oil-based micro imager (OBMI) and oil mud reservoir imager (OMRI) with two circumferential and ultrasonic borehole imagers data from four wells. Next, the initial data were considered and the outliers were eliminated. The feature selection was carried out among conventional logs through pattern recognition artificial neural network (ANN) with the second version of the non-dominated sorting Genetic algorithm (NSGA-II). As a result of ANN-NSGA-II, six factors were selected and fed for classification methods. The targets of methods were three classes including no fracture, low fracture, and high fracture zones based on the user-defined thresholds. According to classification accuracies and confusion matrices, the support vector machine (SVM) with cubic kernel function outperformed the fine decision trees, quadratic discriminant analysis, and K-nearest neighbor (KNN) classifier methods. After determining the highest rank by SVM, five other kernel functions were tried as SVM functions. The radial basis function (RBF) with SVM showed a more reliable classification in comparison with the others. Regarding the objective of the present study, means introduced the most effective fracture classification. SVM was run with three neutral-inspired optimization producers including particle swarm optimization (PSO) and two newly presented grasshopper optimization algorithm (GOA) and grey wolf optimizer (GWO) methods. The final results indicated that (1) the hybrid SVM (RBF)-GWO offered superior accuracies in different population of algorithms, (2) classification zones with no fracture and low fracture (classes 1 and 2) had minimum misclassification through SVM-GWO while the high fracture points (class 3) revealed the highest accuracies with SVM-PSO. Also, SVM-GOA offered the best solution in several iterations and higher time, while, SVM-GWO and SVM-PSO seek SVM classification response faster and are thus recommended for fracture detection.
查看更多>>摘要：Increase in global natural gas production over the last 15 years has led to the use of new and untapped reservoirs including high pressure-high temperature ones in order to meet the consumer demands. As flow characteristics of gas in various environments such as porous media, wells, and pipelines are influenced by its viscosity, it is an important parameter for petroleum engineers. In this work, an immense gas viscosity dataset consisting of 3017 laboratory data points was used for properly implementing two smart techniques;; radial basis function neural network with two training algorithms as well as multilayer perceptron neural network with four training algorithms. By using these techniques, various models with high accuracies were developed for viscosities estimation of gas mixture, pure methane, and pure nitrogen at high pressures (5000~(-2)5000 psia) and high temperatures (100~(-1)880 °F). The radial basis function (RBF) neural network with ant colony optimization (ACO) (namely RBF-ACO model) is considered as the best model. Average absolute relative errors of the aforementioned model for estimating pure methane, pure nitrogen and gas mixture viscosities are 0.36 %, 0.49 %, and 1.76 %, respectively. RBF-ACO model provides better results comparing with other presented empirical models. Also, RBF neural network optimized by particle swarm optimization (PSO) shows a high error for estimating the viscosities of methane and gas mixture and RBF neural network optimized by genetic algorithm (GA) yields a high error for estimating the viscosity of gas mixture. Afterwards, effects of input parameters on the viscosity value obtained by RBF-ACO model, were investigated using the relevancy factor. Finally, based on numerical simulation, a sensitivity analysis was conducted for measuring the uncertainty of cumulative gas production resulted from gas viscosity estimation for a high pressure-high temperature gas reservoir. This process indicates that accurate estimation of gas viscosity plays an important role in reliable estimation of cumulative gas production.
Sergey O. IlyinViktoria Y. IgnatenkoAnna V. Kostyuk
13页
查看更多>>摘要：The use of hexamethyldisiloxane (HMDSO) for deasphalting heavy crude oil allows precipitating several times more compounds from crude oil compared to aliphatic hydrocarbons such as pentane or heptane. The asphaltenic products were obtained by varying the HMDSO/crude oil ratio in the range from 1/1 to 40/1. The structure, composition, and properties of the resulting products were then analyzed by elemental analysis, infrared spectroscopy, matrix-assisted laser desorption/ionization, gradient chromatography, X-ray diffraction, differential scanning calorimetry, and rotational rheometry. It turned out that HMDSO precipitates not only heptane-insoluble asphaltenes from heavy crude oil but also other polyaromatic compounds as well as resins and paraffin waxes. The product yield rises with increasing the HMDSO/crude oil ratio and reaches a maximum at the ratio of 15/1 (the yield is 5 times higher than when using heptane);; then, the yield decreases due to an increase in the content of saturated compounds in the precipitate and the transition of a part of the polyaromatic compounds and asphaltenes into the solution ofmaltenes. The molecular weight, heteroatom content, resin concentration, and other characteristics of the asphaltenic product also pass through a maximum when the HMDSO/crude oil ratio changes. Despite the variability of structure and composition, all the asphaltenic products when heated above 60 °C pass from the glass state to the liquid state characterized by viscoelasticity and non-Newtonian behavior. Temperature variation allows changing the viscosity of the asphaltenic product over a wide range, which makes it possible for its processing by different methods.
查看更多>>摘要：Due to the uniqueness of deep-water shallow formations, there is no fracture system around the wellbore when borehole breathing is observed in this part of the formation. Therefore, the inducing mechanism of the opening/closing of the fracture network cannot reasonably explain this type of borehole breathing. In this study, a new mechanism of permeability-induced is proposed to explain borehole breathing, based on the fact that there is no fracture system around the well and the formation has the characteristics of high permeability and porosity. By using the stress and seepage coupling method in the porous elastic medium, a new model is established to simulate and describe permeability-induced borehole breathing. Through comparison with actual cases, this model can effectively simulate the typical characteristics of fluid loss-flow back in borehole breathing. This study also analyzed the influence of factors such as formation parameters and mud rheological parameters on the borehole breathing caused by permeability. According to the results of the study, the use of a smaller diameter wellbore and agents that can adjust related parameters (such as loss-reducing circulating material) can effectively inhibit wellbore breathing while drilling.
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