Computer Implementation of the Dykstra-Parsons Method of Waterflood Calculation

2021 ◽  
Author(s):  
Prosper Kiisi Lekia
Keyword(s):  
Petroleum Industry ◽  
Injection Pressure ◽  
Injection Rate ◽  
Process Time ◽  
Computer Implementation ◽  
Natural Energy ◽  
Recovery Techniques ◽  
Secondary Recovery ◽  
Time Required ◽  
User Friendly

Abstract One of the challenges of the petroleum industry is achieving maximum recovery from oil reservoirs. The natural energy of the reservoir, primary recoveries in most cases do not exceed 20%. To improve recovery, secondary recovery techniques are employed. With secondary recovery techniques such as waterflooding, an incremental recovery ranging from 15 to 25% can be achieved. Several theories and methods have been developed for predicting waterflood performance. The Dykstra-Parson technique stands as the most widely used of these methods. The authors developed a discrete, analytical solution from which the vertical coverage, water-oil ratio, cumulative oil produced, cumulative water produced and injected, and the time required for injection was determined. Reznik et al extended the work of Dykstra and Parson to include exact, analytical, continuous solutions, with explicit solutions for time, constant injection pressure, and constant overall injection rate conditions, property time, real or process time, with the assumption of piston-like displacement. This work presents a computer implementation to compare the results of the Dykstra and Parson method, and the Reznik et al extension. A user-friendly graphical user interface executable application has been developed for both methods using Python 3. The application provides an interactive GUI output for graphs and tables with the python matplotlib module, and Pandastable. The GUI was built with Tkinter and converted to an executable desktop application using Pyinstaller and the Nullsoft Scriptable Install System, to serve as a hands-on tool for petroleum engineers and the industry. The results of the program for both methods gave a close match with that obtained from the simulation performed with Flow (Open Porous Media). The results provided more insight into the underlying principles and applications of the methods.

Reinforcement Learning From Pixels: Waterflooding Optimization

2020 ◽  
Author(s):  
Ruslan Miftakhov ◽  
Igor Efremov ◽  
Abdulaziz S. Al-Qasim
Keyword(s):  
Reinforcement Learning ◽  
Net Present Value ◽  
Vertical Section ◽  
Water Injection ◽  
Petroleum Industry ◽  
Injection Pressure ◽  
Injection Rate ◽  
Simulation Engine ◽  
First Case ◽  
The Impact

Abstract The application of Artificial Intelligence (AI) methods in the petroleum industry gain traction in recent years. In this paper, Deep Reinforcement Learning (RL) is used to maximize the Net Present Value (NPV) of waterflooding by changing the water injection rate. This research is the first step towards showing that the use of pixel information for reinforcement learning provides many advantages, such as a fundamental understanding of reservoir physics by controlling changes in pressure and saturation without directly accounting for the reservoir petrophysical properties and wells. The optimization routine based on RL by pixel data is tested on the 2D model, which is a vertical section of the SPE 10 model. It has been shown that RL can optimize waterflooding in a 2D compressible reservoir with the 2-phase flow (oil-water). The proposed optimization method is an iterative process. In the first few thousands of updates, NPV remains in the baseline since it takes more time to converge from raw pixel data than to use classical well production/injection rate information. RL optimization resulted in improving the NPV by 15 percent, where the optimum scenario shows less watercut values and more stable production in contrast to baseline optimization. Additionally, we evaluated the impact of selecting the different action set for optimization and examined two cases where water injection well can change injection pressure with a step of 200 psi and 600 psi. The results show that in the second case, RL optimization is exploiting the limitation of the reservoir simulation engine and tries to imitate a cycled injection regime, which results in a 7% higher NPV than the first case.

scholarly journals Study Rheological Behavior of Polymer Solution in Different-Medium-Injection-Tools

Polymers ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 319 ◽  
Author(s):  
Bin Huang ◽  
Xiaohui Li ◽  
Cheng Fu ◽  
Ying Wang ◽  
Haoran Cheng
Keyword(s):  
Molecular Weight ◽  
Polymer Solution ◽  
Oil Recovery ◽  
Injection Pressure ◽  
Injection Rate ◽  
Injection Velocity ◽  
Structural Parameter ◽  
Local Perturbation ◽  
Polymer Injection ◽  
Single Pipe

Previous studies showed the difficulty during polymer flooding and the low producing degree for the low permeability layer. To solve the problem, Daqing, the first oil company, puts forward the polymer-separate-layer-injection-technology which separates mass and pressure in a single pipe. This technology mainly increases the control range of injection pressure of fluid by using the annular de-pressure tool, and reasonably distributes the molecular weight of the polymer injected into the thin and poor layers through the shearing of the different-medium-injection-tools. This occurs, in order to take advantage of the shearing thinning property of polymer solution and avoid the energy loss caused by the turbulent flow of polymer solution due to excessive injection rate in different injection tools. Combining rheological property of polymer and local perturbation theory, a rheological model of polymer solution in different-medium-injection-tools is derived and the maximum injection velocity is determined. The ranges of polymer viscosity in different injection tools are mainly determined by the structures of the different injection tools. However, the value of polymer viscosity is mainly determined by the concentration of polymer solution. So, the relation between the molecular weight of polymer and the permeability of layers should be firstly determined, and then the structural parameter combination of the different-medium-injection-tool should be optimized. The results of the study are important for regulating polymer injection parameters in the oilfield which enhances the oil recovery with reduced the cost.

The Research and Evaluation of Finely Layered Water Injection Standard in Low-Permeability Reservoirs - A Case from Block A in one Low-Permeability Reservoir

2014 ◽  
Vol 1073-1076 ◽  
pp. 2310-2315 ◽  
Author(s):  
Ming Xian Wang ◽  
Wan Jing Luo ◽  
Jie Ding
Keyword(s):  
Oil Recovery ◽  
Water Injection ◽  
Injection Pressure ◽  
Injection Rate ◽  
Low Permeability ◽  
Reservoir Permeability ◽  
Engineering Parameters ◽  
The Common ◽  
Common Problems ◽  
Low Permeability Reservoirs

Due to the common problems of waterflood in low-permeability reservoirs, the reasearch of finely layered water injection is carried out. This paper established the finely layered water injection standard in low-permeability reservoirs and analysed the sensitivity of engineering parameters as well as evaluated the effect of the finely layered water injection standard in Block A with the semi-quantitative to quantitative method. The results show that: according to the finely layered water injection standard, it can be divided into three types: layered water injection between the layers, layered water injection in inner layer, layered water injection between fracture segment and no-fracture segment. Under the guidance of the standard, it sloved the problem of uneven absorption profile in Block A in some degree and could improve the oil recovery by 3.5%. The sensitivity analysis shows that good performance of finely layered water injection in Block A requires the reservoir permeability ratio should be less than 10, the perforation thickness should not exceed 10 m, the amount of layered injection layers should be less than 3, the surface injection pressure should be below 14 MPa and the injection rate shuold be controlled at about 35 m3/d.

Unloading Frac Hits in Gas Wells: How Does the Nitrogen Injection Rate and Pressure Affect the Unloading Process?

2021 ◽  
Author(s):  
Miguel Angel Cedeno
Keyword(s):  
Multiphase Flow ◽  
Flow Rate ◽  
Injection Pressure ◽  
Injection Rate ◽  
Gas Wells ◽  
Eagle Ford Shale ◽  
Eagle Ford ◽  
Nitrogen Injection ◽  
Injection Flow ◽  
Transient Multiphase Flow

Abstract The unconventional resources development has grown tremendously as a result of the advancement in horizontal drilling technology coupled with hydraulic fracturing. However, as more wells are drilled and fractured close to each other, frac hits have become a major challenge in these wells. The aim of this work is to investigate the effect of nitrogen injection flow rate and pressure on unloading frac hits gas wells in transient multiphase flow. A numerical simulation model was created using a transient multiphase flow simulator to mimic the unloading process of frac hits by injecting nitrogen from the surface through the annulus section of the well. Many simulation cases were created and analyzed to comprehend the effect of the nitrogen injection rate and pressure on the unloading of frac hits. The model mimicked real field data from currently active well in the Eagle Ford Shale. The results showed that as the nitrogen injection pressure increases, the nitrogen volume and the time to unload the frac hits decrease. On the other hand, increasing the injection rate of nitrogen will increase the nitrogen volume required to unload the frac hits. In addition, the time to unload frac hits will be decreased as the nitrogen injection rate increases. These results indicate that the time required to unload frac hits will be minimized if higher flow rates of nitrogen were utilized. Nonetheless, the volume of nitrogen required to unload the frac hits will be maximized. An important observation to highlight is that the operators can save money by reducing the time for injecting nitrogen. This observation was verified when increasing the injection pressure in the frac hit well in the Eagle Ford Shale, the time of injection was reduced 20%. This study presents the effects of nitrogen injection flow rate and injection pressure for unloading frac hits in gas wells. Due to the lack of published studies about this topic, this work can serve as a practical guideline for unloading frac hits in gas wells.

scholarly journals Effect of Multiple Flow Pulses on Hydraulic Fracture Network Propagation in Naturally Fractured Volcanic Rock

Energies ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 633
Author(s):  
Guangzhi Yang ◽  
Shicheng Zhang ◽  
Jia Wang ◽  
Ning Li ◽  
Xinfang Ma ◽  
...  
Keyword(s):  
Pressure Drop ◽  
Hydraulic Fracture ◽  
Injection Pressure ◽  
Fracture Network ◽  
Injection Rate ◽  
Injection Method ◽  
Injection Scheme ◽  
Fracture Complexity ◽  
Naturally Fractured ◽  
Fluid Leak

Exploring engineering methods for increasing fracture network complexity is important for the development of unconventional oil and gas reservoirs. In this study, we conducted a series of fracturing experiments on naturally fractured volcanic samples. An injection method, multiple flow pulses, is proposed to increase fracture complexity. The results show that fluid leaked into the natural fracture network (NFN) when the injection rate was low (0.2 mL/min); hydraulic-fracture-dominant fracture geometry was created with an injection rate of 2 and 5 mL/min. Under the 2 mL/min-injection scheme with 3 pulses, the injection pressure during the intermittent stage was low (<5 MPa), resulting in a limited increase in fracture complexity. When the number of the flow pulses increased to 5, the pressure drop rate in the fourth and fifth intermittent stage significantly increased, indicating an increase in the aperture of natural fractures (NFs) and in the fluid leak-off effect. Under the 5 mL/min injection scheme containing 5 pulses, besides the enhanced fluid leak-off, a sharp injection pressure drop was observed, indicating the activation of NFs. The complexity and the aperture of the ultimate fracture network further increased. The injection method, multiple flow pulses, can be used to create complex fracture networks effectively.

scholarly journals A Study of Combustion Characteristics of Two Gasoline–Biodiesel Mixtures on RCEM Using Various Fuel Injection Pressures

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3265
Author(s):  
Ardhika Setiawan ◽  
Bambang Wahono ◽  
Ocktaeck Lim
Keyword(s):  
Heat Release ◽  
Ignition Delay ◽  
Fuel Injection ◽  
Injection Pressure ◽  
Fuel Mixture ◽  
Injection Rate ◽  
Injection Duration ◽  
Late Start ◽  
Fuel Injection Rate ◽  
Injection Pressures

Experimental research was conducted on a rapid compression and expansion machine (RCEM) that has characteristics similar to a gasoline compression ignition (GCI) engine, using two gasoline–biodiesel (GB) blends—10% and 20% volume—with fuel injection pressures varying from 800 to 1400 bar. Biodiesel content lower than GB10 will result in misfires at fuel injection pressures of 800 bar and 1000 bar due to long ignition delays; this is why GB10 was the lowest biodiesel blend used in this experiment. The engine compression ratio was set at 16, with 1000 µs of injection duration and 12.5 degree before top dead center (BTDC). The results show that the GB20 had a shorter ignition delay than the GB10, and that increasing the injection pressure expedited the autoignition. The rate of heat release for both fuel mixes increased with increasing fuel injection pressure, although there was a degradation of heat release rate for the GB20 at the 1400-bar fuel injection rate due to retarded in-cylinder peak pressure at 0.24 degree BTDC. As the ignition delay decreased, the brake thermal efficiency (BTE) decreased and the fuel consumption increased due to the lack of air–fuel mixture homogeneity caused by the short ignition delay. At the fuel injection rate of 800 bar, the GB10 showed the worst efficiency due to the late start of combustion at 3.5 degree after top dead center (ATDC).

Effect of Injection Parameters on the Spray Characteristics of DME Fuel

2006 ◽  
Author(s):  
Bong Woo Ryu ◽  
Seung Hwan Bang ◽  
Hyun Kyu Suh ◽  
Chang Sik Lee
Keyword(s):  
Dimethyl Ether ◽  
Diesel Fuel ◽  
Cone Angle ◽  
Injection Pressure ◽  
Injection Rate ◽  
Spray Characteristics ◽  
Spray Cone Angle ◽  
Spray Cone ◽  
Injection Duration ◽  
Injection Parameters

The purpose of this study is to investigate the effect of injection parameters on the injection and spray characteristics of dimethyl ether and diesel fuel. In order to analyze the injection and spray characteristics of dimethyl ether and diesel fuel with employing high-pressure common-rail injection system, the injection characteristics such as injection delay, injection duration, and injection rate, spray cone angle and spray tip penetration was investigated by using the injection rate measuring system and the spray visualization system. In this work, the experiments of injection rate and spray visualization are performed at various injection parameters. It was found that injection quantity was decreased with the increase of injection pressure at the same energizing duration and injection pressure In the case of injection characteristics, dimethyl ether showed shorter of injection delay, longer injection duration and lower injected mass flow rate than diesel fuel in accordance with various energizing durations and injection pressures. Also, spray development of dimethyl ether had larger spray cone angle than that of diesel fuel at various injection pressures. Spray tip penetration was almost same development and tendency regardless of injection angles.

scholarly journals Comparison of visualization tools for single-cell RNAseq data

2020 ◽  
Vol 2 (3) ◽  
Author(s):  
Batuhan Cakir ◽  
Martin Prete ◽  
Ni Huang ◽  
Stijn van Dongen ◽  
Pinar Pir ◽  
...  
Keyword(s):  
Single Cell ◽  
R Package ◽  
Data Format ◽  
Interactive Analysis ◽  
Rnaseq Data ◽  
Scientific Report ◽  
Visualization Tools ◽  
Time Required ◽  
User Friendly ◽  
The Web

Abstract In the last decade, single cell RNAseq (scRNAseq) datasets have grown in size from a single cell to millions of cells. Due to its high dimensionality, it is not always feasible to visualize scRNAseq data and share it in a scientific report or an article publication format. Recently, many interactive analysis and visualization tools have been developed to address this issue and facilitate knowledge transfer in the scientific community. In this study, we review several of the currently available scRNAseq visualization tools and benchmark the subset that allows to visualize the data on the web and share it with others. We consider the memory and time required to prepare datasets for sharing as the number of cells increases, and additionally review the user experience and features available in the web interface. To address the problem of format compatibility we have also developed a user-friendly R package, sceasy, which allows users to convert their own scRNAseq datasets into a specific data format for visualization.

Avoiding Pitfalls in Multiphase Thermo-Hydrodynamic Coupling

2002 ◽  
Author(s):  
Luis F. Ayala ◽  
Eltohami S. Eltohami ◽  
Michael A. Adewumi
Keyword(s):  
Multiphase Flow ◽  
Petroleum Industry ◽  
Material Balance ◽  
Petroleum Products ◽  
Special Consideration ◽  
Computational Time ◽  
Time Saving ◽  
Trade Off ◽  
Time Required ◽  
The Impact

Multiphase flow is prevalent in many industrial processes. Therefore, accurate and efficient modeling of multiphase flow is essential to the understanding of these processes as well as the development of technologies to handle and manage them. In the petroleum industry, the occurrence and consequence thereof associated with such hydrodynamic processes are encountered in offshore facilities, surface facilities as well as reservoir applications. In this paper, we consider the modeling of these processes with special consideration to the transport of petroleum products through pipelines. Multiphase hydrodynamic modeling is usually a trade-off between maximizing the accuracy level while minimizing the computational time required. The most fundamental modeling effort developed to achieve this goal is based on applying simplifications to the basic physical laws, as defined by continuum mechanics, governing these processes. However, the modeling of multiphase flow processes requires the coupling of these basic laws with a thermodynamic phase behavior model. This paper highlights the impact of the techniques used to computationally couple the system’s thermodynamics with its fluid mechanics while paying close attention to the trade off mentioned above. It will consider the consequences of the simplifications applied, as well as inherent deficiencies associated with such simplifications. Special consideration is given to the conservation of mass as well as the terms that govern its transfer between the phases. Furthermore, the implications related to the common simplification of isothermal conditions are studied, highlighting the loss of accuracy in the material balance associated with this computational time-saving assumption. This paper concludes by suggesting remedies to these problems, supported by results, showing considerable improvement in fulfilling both the basic constrains which are minimizing time and maximizing accuracy.

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