The influence of wettability and carbon dioxide injection on hydrocarbon recovery

This study can be divided into two sections. First, a detailed study of petrophysical properties and the impact of wettability is performed on cores from a producing heterogeneous carbonate reservoir from the Middle East. Second, a comparison between different injection schemes (waterflooding, gas injection, WAG and CO2 injection) for enhanced oil recovery is made for another giant carbonate reservoir in the Middle East. Knowledge of the wettability of a reservoir rock and its influence on petrophysical properties is a key factor for determining oil recovery mechanisms and making estimates of recovery efficiency. A full suite of experiments on well-characterised systems, including sandpacks, sandstones and carbonate cores, was performed to measure capillary pressure, relative permeability, NMR response and resistivity index. Cores aged in crude oil, with different wettability were studied. As a preliminary step to investigate the effect of wettability on heterogeneous carbonates from the Middle East, sandpack and sandstone samples were first tested because: 1) these samples are known to be quite homogeneous and of a wettability that can be controlled; 2) To test our experimental methods; and 3) to serve as a dataset for modelling studies. First, the static (porosity and permeability) and dynamic (initial water saturation and residual oil saturation) properties of Leavenseat (LV60) and Ottawa (F-42) sandpacks were measured. The formation factor and NMR response for these sandpacks were also determined. These experimental measurements have served as a benchmark for pore-modelling studies that have reproduced the experimental data. Fontainebleau sandstones have also been used as a benchmark in the industry because of its relatively simple pore structure. Mercury injection capillary pressure (MICP) measurements were performed on this sandstone. The MICP experimental measurements showed very low pore volume values, indicating very tight (consolidated) samples. These samples had a diameter of less than 0.02 m which made the experiments quite difficult. Once we had confidence in the experimental methodology, five carbonate samples from a typical Middle East reservoir were imaged and cleaned in order to render them more water wet. Conventional and special core analyses were performed on all the samples. The pore throat distribution from capillary pressure was successfully compared with the pore size distribution inferred from the NMR T2 relaxation curve. Formation resistivity factor and the formation resistivity index were also measured. Capillary pressure and relative permeability curves were measured using refined oil and synthetic formation brine. Then the samples were aged in crude oil from the same field at elevated temperature (120oC) and underwent the same experiments to evaluate the influence of wettability changes on these properties. The experimental data show that there is a significant difference in the relative permeability and capillary pressure of the cleaned and aged samples; the results are explained in terms of the pore-scale configurations of fluids. In contrast, electrical resistivity did not encounter significant changes for different wettability, suggesting that electrical properties in these carbonates are mainly affected by the porosity that remains water-wet, or is only neutrally-wet. This conclusion is supported by the significant displacement that is observed in the aged sample at capillary pressures close to zero. We show that wettability, imbibition capillary pressure and relative permeability have major impact on the waterflood sweep efficiency and hence on the distribution of remaining oil saturation. An incorrect understanding of the distribution of remaining oil saturation may lead to ineffective reservoir management and IOR/EOR decisions. The second part of this thesis is to assess the efficacy of CO2 injection into carbonate oil fields. The reservoir under study is a layered system. The reservoir consists of two main units, i.e. a lower zone of generally low permeability layers and an upper zone of high permeability layers inter-bedded with low permeability layers; the average permeability of the upper zone is some 10-100 times higher than that of the Lower zone. Under waterflooding, the injected water tends to flow through the upper zone along the high permeability layers and no or very slow cross flow of water into the lower zone occurs, resulting in very poor sweep of the lower zone. There is significant scope for improving oil recovery from such type of heterogeneous mixedwet carbonate reservoirs. The apparent impediment to water invading the bottom strata prompts suggests that a miscible fluid could be Injected into the lower zone. We conducted a series of core-flood experiments to compare the performance of different displacement process: waterflooding, hydrocarbon gas flooding and wateralternate gas (WAG) and compared them with CO2 injection. We show that the local displacement efficiency for CO2 flooding is approximately 97% - much higher than that obtained from waterflooding or hydrocarbon gas injection, due to the development of miscibility between CO2 and the oil. We use the results to discuss the potential of CO2 injection for storage and enhanced oil recovery in the Middle East carbonate reservoir discussed above, and proposes further research to develop a fuller understanding of the subsurface behavior of CO2

Analytical approximate solutions for two-dimensional incompressible Navier-Stokes equations

Analytical approximate solutions of the two-dimensional incompressible Navier-Stokes equations by means of Adomian decomposition method are presented. The power of this manageable method is confirmed by applying it for two selected  flow problems: The first is the Taylor decaying vortices, and the second is the flow behind a grid, comparison with High-order upwind compact finite-difference method is made. The numerical results that are obtained for two incompressible flow problems  showed that the proposed method is less time consuming, quite accurate and easily implemented. In addition, we prove the convergence of this method when it is applied to the flow problems, which are describing them by  unsteady two-dimensional incompressible Navier-Stokes equations.   Keywords: Navier-Stokes equations, Adomian decomposition, upwind compact difference, Accuracy, Convergence analysis,Taylor's decay vortices, flow behind a grid

Enhanced CNN with Global Features for Fault Diagnosis of Complex Chemical Processes

Convolutional neural network (CNN) models have been widely used for fault diagnosis of complex systems. However, traditional CNN models rely on small kernel filters to obtain local features from images. Thus, an excessively deep CNN is required to capture global features, which are critical for fault diagnosis of dynamical systems. In this work, we present an improved CNN that embeds global features (GF-CNN). Our method uses a multi-layer perceptron (MLP) for dimension reduction to directly extract global features and integrate them into the CNN. The advantage of this method is that both local and global patterns in images can be captured by a simple model architecture instead of establishing deep CNN models. The proposed method is applied to the fault diagnosis of the Tennessee Eastman process. Simulation results show that the GF-CNN can significantly improve the fault diagnosis performance compared to traditional CNN. The proposed method can also be applied to other areas such as computer vision and image processing.Comment: 6 pages, 5 figure

New analytical approximate solutions of Fifth-order KdV equation

In this paper, we have exposed a process of how to implement a new splitting Adomian decomposition homotopy perturbation method to solve fifth-order KdV equations. The new methodology is applied on two kinds of fifth-order KdV equations with initial data: The first is Sawada-Kotera equation and the second its Lax equation. The numerical results we  obtained  from solutions of two kinds of fifth-order KdV equations, have good convergent  and high  accuracy  comparison with other methods in literature. The graphs and tables of the new analytical approximate solutions show the validity, usefulness, and necessity of the process. Keywords: Splitting scheme, Adomian decomposition, homotopy perturbation method,  fifth-order KdV equation, convergence analysis. Mathematics Subject Classifications 2010 [MSC]: 76S05, 65N99, 35Q3

Splitting Decomposition Homotopy Perturbation Method To Solve One -Dimensional Navier -Stokes Equation

We have proposed in this  research a new scheme to find analytical  approximating solutions for Navier-Stokes equation  of  one  dimension. The  new  methodology depends on combining  Adomian  decomposition  and Homotopy perturbation methods  with the splitting time scheme for differential operators . The new methodology is applied on two problems of  the test: The first has an exact solution  while  the other one has no  exact solution. The numerical results we  obtained  from solutions of two problems, have good convergent  and high  accuracy   in comparison with the two traditional Adomian  decomposition  and Homotopy  perturbationmethods .&nbsp

Numerical Solution of Mixed Volterra – Fredholm Integral Equation Using the Collocation Method

         معادلات فولتيرا- فريدهولم التكاملية المختلط ((MVFIEs لديها اهتمام كبير من قبل الباحثين مؤخرا . الطريقة العددية الي اقترحت لحل هذا النوع من المعادلات تستعمل نقاط التجميع وتقريب الحل بواسطة الدالة  اساس الشعاعي (radial basis function)  و متعددة حدود من الدرجة الثانية واندراج النقطة من دون استخدام الشبكة, ولسهولة  الحل تم استخدام اصفار متعددة حدود ليجندر كنقاط تجمع. الغرض الرئيسي من استخدام دالة أساس الشعاعي ومتعدد الحدود هو التغلب على التفرد الذي قد يرتبط بأساليب التجميع. علاوة على ذلك، فإن وظيفة الاستيفاء التي تم الحصول عليها تمر عبر كل النقاط المنتشرة في مجال ما ، وبالتالي فإن وظائف الشكل هي من خصائص خاصية دلتا. تمت مقارنة الحل الدقيق للحلول الانتقائية بالنتائج التي تم الحصول عليها من التجارب العددية من أجل التحقق من دقة وكفاءة طريقتنا.Volterra – Fredholm integral equations (VFIEs) have a massive interest from researchers recently. The current study suggests a collocation method for the mixed Volterra - Fredholm integral equations (MVFIEs)."A point interpolation collocation method is considered by combining the radial and polynomial basis functions using collocation points". The main purpose of the radial and polynomial basis functions is to overcome the singularity that could associate with the collocation methods. The obtained interpolation function passes through all Scattered Point in a domain and therefore, the Delta function property is the shape of the functions. The exact solution of selective solutions was compared with the results obtained from the numerical experiments in order to investigate the accuracy and the efficiency of scheme

Soft computing models for assessing bond performance of reinforcing bars in concrete at high temperatures

The bond between steel and concrete in reinforced concrete structures is a multifaceted and intricate phenomenon that plays a vital role in the design and overall performance of such structures. It refers to the adhesion and mechanical interlock between the steel reinforcement bars and the surrounding concrete matrix. Under elevated temperatures, the bond is more complex under higher temperatures, yet having an accurate estimate is an important factor in design. Therefore, this paper focuses on using data-driven models to explore the performance of the concrete-steel bond under high temperatures using a Gene Expression Programming (GEP) soft computing model. The GEP models are developed to simulate the bond performance in order to understand the effect of high temperatures on the concrete-steel bond. The results were compared to the multi-objective evolutionary polynomial regression analysis (MOGA-EPR) models for different input variables. The new model would help the designers with strength predictions of the bond in fire. The dataset used for the model was obtained from experiments conducted in a laboratory setting that gathered a 316-point database to investigate concrete bond strength at a range of temperatures and with different fibre contents. This study also investigates the impact of the different variables on the equation using sensitivity analysis. the results show that the GEP models are able to predict bond performance with different input variables accurately. This study provides a useful tool for engineers to better understand the concrete-steel bond behaviour under high temperatures and predict concrete-steel bond performance under high temperatures

An optimized prediction of FRP bars in concrete bond strength employing soft computing techniques

The precise estimation of the bonding strength between concrete and fiber-reinforced polymer (FRP) bars holds significant importance for reinforced concrete structures. This study introduces a new methodology that utilizes soft computing methods to enhance the prediction of FRP bars’ bonding strength. A significant compilation of experimental bond strength tests is assembled, covering various variables. Significant variables that affect bonding strength are found in the study of this database. The prediction process is optimized using soft computing methods, particularly Gene Expression Programming (GEP) and the Multi-Objective Genetic Algorithm Evolutionary Polynomial Regression (MOGA-EPR).The proposed soft computing approaches accommodate complex relationships and optimize prediction accuracy depending on the input variables. Results demonstrate its effectiveness in predicting bond strength and comparing it with existing codes and other models from the literature. The results have shown that the MOGA-EPR and the GEP models have high R2 values between 0.91 and 0.94. The proposed new models enhance the reliability and efficiency of designing and assessing FRP-reinforced concrete

Shear strength assessment of reinforced recycled aggregate concrete beams without stirrups using soft computing techniques

This paper presents a study to predict the shear strength of reinforced recycled aggregate concrete beams without stirrups using soft computing techniques. The methodology involves the development of a Multi-Objective Genetic Algorithm Evolutionary Polynomial Regression (MOGA-EPR) and Gene Expression Programming (GEP) models. The input variables considered are the longitudinal reinforcement ratio, recycled coarse aggregate ratio, beam cross-section dimensions, and concrete compressive strength. Data collected from the literature were used to train and validate the models. The results showed that the MOGA-EPR and GEP models can accurately predict the shear strength of beams without stirrups. The models also performed better than equations from the codes and literature. This study provides an alternative approach to accurately predict the shear strength of reinforced recycled aggregate concrete beams without stirrups

A New Technique for Simulation the Zakharov–Kuznetsov Equation

In this article, a new technique is proposed to simulated two-dimensional Zakharov–Kuznetsov equation with the initial condition. The idea of this technique is based on Taylors' series in its derivation. Two test problems are presented to illustrate the performance of the new scheme. Analytical approximate solutions that we obtain are compared with variational iteration method (VIM) and homotopy analysis method (HAM). The results show that the new scheme is efficient and better than the other methods in accuracy and convergence