Increasing interest by governments worldwide on reducing CO2 released into the atmosphere form a nexus of of opportunity with enhanced oil recovery which could benefit mature oil fields in nearly every country. Overall approximately two-thirds of original oil in place (OOIP) in mature conventional oil fields remains after primary or primary/secondary recovery efforts have taken place. CO2 enhanced oil recovery (CO2 EOR) has an excellent record of revitalizing these mature plays and can dramatically increase ultimate recovery. Since the first CO2 EOR project was initiated in 1972, more than 154 additional projects have been put into operation around the world and about two-thirds are located in the Permian basin and Gulf coast regions of the United States. While these regions have favorable geologic and reservoir conditions for CO2 EOR, they are also located near large natural sources of CO2.
In recent years an increasing number of projects have been developed in areas without natural supplies, and have instead utilized captured CO2 from a variety of anthropogenic sources including gas processing plants, ethanol plants, cement plants, and fertilizer plants. Today approximately 36% of active CO2 EOR projects utilize gas that would otherwise be vented to the atmosphere. Interest world-wide has increased, including projects in Canada, Brazil, Norway, Turkey, Trinidad, and more recently, and perhaps most significantly, in Saudi Arabia and Qatar. About 80% of all energy used in the world comes from fossil fuels, and many industrial and manufacturing processes generate CO2 that can be captured and used for EOR. In this 30 minute presentation a brief history of CO2 EOR is provided, implications for utilizing captured carbon are discussed, and a demonstration project is introduced with an overview of characterization, modeling, simulation, and monitoring actvities taking place during injection of more than a million metric tons (~19 Bcf) of anthropogenic CO2 into a mature waterflood.
Longer versions of the presentation can be requested and can cover details of geologic and seimic characterization, simulation studies, time-lapse monitoring, tracer studies, or other CO2 monitoring technologies.
We are all familiar with the production systems through which reservoir fluids flow to reach our processing facilities. This is a journey characterized by complex multiphase flow phenomena that govern pressure and temperature changes along the way. A monumental amount of research and development work has been invested towards better understanding multiphase flow behavior over the past fifty years. Yet, many challenges remain as we strive to optimize ever more complex production systems fraught with difficult flow assurance issues. Just how good is the science? And more importantly, how does this impact our bottom line? This lecture will discuss key concepts of multiphase flow leading to the current “state-of-the-art” models used today. Looking towards the future, the science must be advanced to address areas of greatest uncertainty and align with trends in field development strategies. Recommendations will be presented covering the top 5 areas of research necessary for these purposes. The economic impact of multiphase operations will be illustrated using two examples that provide insight towards maximizing asset value.
Mack Shippen is a Principal Engineer with Schlumberger in Houston, where he is responsible for the global business of the PIPESIM multiphase flow simulation software. He has extensive experience in well and network simulation studies, ranging from flow assurance to dynamic coupling of reservoir and surface simulation models. He has served on a number of SPE committees and chaired the SPE Reprint Series on Offshore Multiphase Production Operations. He holds BS and MS degrees in Petroleum Engineering from Texas A&M University, where his research focused on multiphase flow modelling.
The weakness of reservoir simulations is the lack of quantity and quality of the required input; their strength is the ability to vary one parameter at a time. Therefore, reservoir simulations are an appropriate tool to evaluate relative uncertainty but absolute forecasts can be misleading, leading to poor business decisions. As recovery processes increase in complexity, the impact of such decisions may have a major impact on the project viability. A responsible use of reservoir simulations is discussed, addressing both technical users and decision makers. The danger of creating a false confidence in forecasts and the value of simulating complex processes are demonstrated with examples. This is a call for the return of the reservoir engineer who is in control of the simulations and not controlled by them, and the decision maker who appreciates a black & white graph of a forecast with realistic uncertainties over a 3-D hologram in colour.
Reservoir simulation is a sophisticated technique of forecasting future recoverable volumes and production rates that is becoming commonplace in the management and development of oil and gas reservoirs, small and large. Calculation and estimation of reserves continues to be a necessary process to properly assess the value and manage the development of an oil and gas producer’s assets. These methods of analysis, while generally done for different purposes, require knowledge and expertise by the analyst (typically a reservoir engineer) to arrive at meaningful and reliable results. Increasingly, the simulation tool is being incorporated into the reserves process. However, as with any reservoir engineering technique, certain precautions must be taken when relying on reservoir simulation as the means for estimating reserves. This discussion highlights some of the important facets one should consider when applying numerical simulation methods to use for, or augment, reserves estimates. The main take away will be an appreciation for the areas to focus on to arrive at meaningful and defendable estimates of reserves that are based on reservoir models.
Increasing interest by governments worldwide on reducing CO2 released into the atmosphere form a nexus of of opportunity with enhanced oil recovery which could benefit mature oil fields in nearly every country. Overall approximately two-thirds of original oil in place (OOIP) in mature conventional oil fields remains after primary or primary/secondary recovery efforts have taken place. CO2 enhanced oil recovery (CO2 EOR) has an excellent record of revitalizing these mature plays and can dramatically increase ultimate recovery. Since the first CO2 EOR project was initiated in 1972, more than 154 additional projects have been put into operation around the world and about two-thirds are located in the Permian basin and Gulf coast regions of the United States. While these regions have favorable geologic and reservoir conditions for CO2 EOR, they are also located near large natural sources of CO2.
In recent years an increasing number of projects have been developed in areas without natural supplies, and have instead utilized captured CO2 from a variety of anthropogenic sources including gas processing plants, ethanol plants, cement plants, and fertilizer plants. Today approximately 36% of active CO2 EOR projects utilize gas that would otherwise be vented to the atmosphere. Interest world-wide has increased, including projects in Canada, Brazil, Norway, Turkey, Trinidad, and more recently, and perhaps most significantly, in Saudi Arabia and Qatar. About 80% of all energy used in the world comes from fossil fuels, and many industrial and manufacturing processes generate CO2 that can be captured and used for EOR. In this 30 minute presentation a brief history of CO2 EOR is provided, implications for utilizing captured carbon are discussed, and a demonstration project is introduced with an overview of characterization, modeling, simulation, and monitoring actvities taking place during injection of more than a million metric tons (~19 Bcf) of anthropogenic CO2 into a mature waterflood.
Longer versions of the presentation can be requested and can cover details of geologic and seimic characterization, simulation studies, time-lapse monitoring, tracer studies, or other CO2 monitoring technologies.
We are all familiar with the production systems through which reservoir fluids flow to reach our processing facilities. This is a journey characterized by complex multiphase flow phenomena that govern pressure and temperature changes along the way. A monumental amount of research and development work has been invested towards better understanding multiphase flow behavior over the past fifty years. Yet, many challenges remain as we strive to optimize ever more complex production systems fraught with difficult flow assurance issues. Just how good is the science? And more importantly, how does this impact our bottom line? This lecture will discuss key concepts of multiphase flow leading to the current “state-of-the-art” models used today. Looking towards the future, the science must be advanced to address areas of greatest uncertainty and align with trends in field development strategies. Recommendations will be presented covering the top 5 areas of research necessary for these purposes. The economic impact of multiphase operations will be illustrated using two examples that provide insight towards maximizing asset value.
Mack Shippen is a Principal Engineer with Schlumberger in Houston, where he is responsible for the global business of the PIPESIM multiphase flow simulation software. He has extensive experience in well and network simulation studies, ranging from flow assurance to dynamic coupling of reservoir and surface simulation models. He has served on a number of SPE committees and chaired the SPE Reprint Series on Offshore Multiphase Production Operations. He holds BS and MS degrees in Petroleum Engineering from Texas A&M University, where his research focused on multiphase flow modelling.
The weakness of reservoir simulations is the lack of quantity and quality of the required input; their strength is the ability to vary one parameter at a time. Therefore, reservoir simulations are an appropriate tool to evaluate relative uncertainty but absolute forecasts can be misleading, leading to poor business decisions. As recovery processes increase in complexity, the impact of such decisions may have a major impact on the project viability. A responsible use of reservoir simulations is discussed, addressing both technical users and decision makers. The danger of creating a false confidence in forecasts and the value of simulating complex processes are demonstrated with examples. This is a call for the return of the reservoir engineer who is in control of the simulations and not controlled by them, and the decision maker who appreciates a black & white graph of a forecast with realistic uncertainties over a 3-D hologram in colour.
Reservoir simulation is a sophisticated technique of forecasting future recoverable volumes and production rates that is becoming commonplace in the management and development of oil and gas reservoirs, small and large. Calculation and estimation of reserves continues to be a necessary process to properly assess the value and manage the development of an oil and gas producer’s assets. These methods of analysis, while generally done for different purposes, require knowledge and expertise by the analyst (typically a reservoir engineer) to arrive at meaningful and reliable results. Increasingly, the simulation tool is being incorporated into the reserves process. However, as with any reservoir engineering technique, certain precautions must be taken when relying on reservoir simulation as the means for estimating reserves. This discussion highlights some of the important facets one should consider when applying numerical simulation methods to use for, or augment, reserves estimates. The main take away will be an appreciation for the areas to focus on to arrive at meaningful and defendable estimates of reserves that are based on reservoir models.
"Drilling" often refers to all aspects of well construction, including drilling, completions, facilities, construction, the asset team, and other groups. Good performance measures drive performance and reduce conflict between these groups, while bad performance measures mislead and confuse. The first key to success is how to communicate drilling performance in terms that answer the questions of executives and managers, which requires a business-focused cross-functional process. The second key to success is to drive operational performance improvement, which requires a different set of measures with sufficient granularity to define actions. Over the past 10 years, a very workable system has evolved through various approaches used in drilling more than 16,000 wells in the US, South America, and the Middle East. The system has delivered best-in-class performance. It has proven that an effective performance measurement system which addresses both executive requirements and operational requirements can both deliver outstanding results, and also communicate those results, with remarkable value to the organization. The basic principles are widely applicable to areas other than drilling.
In 2010 Shell began investigating how to automate the initial response to a well control incident. The first phase of the project was to develop a rig system that could reliably detect an influx across a broad spectrum of floating rig well construction related rig operations. The results of a fault tree style sensitivity analysis pointed to the high value of improving sensor data quality (both accuracy and reliability) and the importance of improving kick detection software for alarming (both in terms of coverage and how the driller is alerted to respond to a confirmed kick condition). Based on the analysis results, a Smart Kick Detection System functional specification was developed and used to upgrade the kick detection system on an offshore rig.
Early in the project it was realized that focusing on adding robust kick detection during
connections was important but especially challenging due to the associated transient flow and pit volume signatures. A separate in-house initiative was therefore kicked-off to develop new software based on pattern recognition technology and machine learning. The resulting IDAPS (Influx Detection at Pumps Stopped) software has now been implemented as a real-time monitoring application for all Shell operated deep water wells. Further developments in smart kick detection are coming, ultimately leading to rigs being equipped with automated kick detection systems that are relied upon to detect a kick and secure the well in case the driller fails to act.
ResAssure - The World’s Fastest Reservoir Simulator | A Revolution in Reserve...Stochastic Simulation
This Presentation Will:
1. Introduce a new way of evaluating reservoir uncertainty with RESASSURE
2. Illustrate the concepts used
3. Highlight the benefits achieved
4. Demonstrate the value of the results
Stochastic Simulation has unleashed the world’s fastest reservoir simulator, ResAssure, which is set to revolutionize production planning and reserves reporting in the Oil & Gas industry.
ResAssure easily computes > 1 Million realisations within a 24 hour period, a fraction of the time it currently takes with traditional methods and software packages. The release of ResAssure marks a significant milestone in the history of reservoir simulation – the first real industry technology advance in 30 years.
Dr Wadsley, Chief Technology Officer at Stochastic Simulation, commented “ResAssure is capable of quickly generating more accurate reserve estimates than is currently possible by any other software system. The approach taken generates a complete distribution of history matched models all of which are consistent with the geological model and observed production history. The time taken for this is orders of magnitude faster than current history matching methods.”
“Field development planning based on ResAssure’s distribution of models (rather than just upon a single history-matched model using conventional methodologies) will significantly reduce uncertainty and risk.” he added.
By enabling faster and more accurate analysis of dynamic subsurface geological data than has previously been possible, ResAssure markedly reduces the risk in the development of oil and gas fields by narrowing the range of uncertainty in reserves estimates: thereby supporting better production and financing decisions, with substantial increases in project ROI.
ResAssure’s innovation in reservoir simulation solves fully-implicit, dynamic three-phase fluid flow equations for every geological realisation. The speed breakthrough was achieved by a combination of proprietary algorithms, polygonal gridding and aggressive spatial coarsening and time stepping, based upon a conventional finite-difference discretization of the reservoir.
Key Insights Identified:
1. Consistency between volumetric, material balance and fractional flow places very strong constraints on feasible reservoir models.
2. The mathematics of reservoir simulation is NOT complex – it is the geology which is complex.
3. Reserves uncertainty is not quantified, but estimated from current ‘best’ estimate in an ad hoc unsystematic way.
4. What’s the point of preserving mass balance in the simulator when the hydrocarbons in the reservoir are imprecise and we don’t include all production data – mass balance should act to regularise our solution, not to define it.
5. The role of reservoir simulation is not to compute an exact solution of a poorly defined geological model – it is to define a range of feasible reservoir models and associated production forecasts.
Title: Evaluation of Multistage Hydraulic Fracturing Techniques for Production Optimization in Naturally Fractured Reservoirs Using Coupled Geomechanics Fracture and Flow Model
Title: Maximizing the Opportunity in Multi-Layered Tight Sand Reservoirs in a Mature Field by Hydraulic Fracturing: A Case Study of Tight Sand Development Project in Thailand
Overview of Reservoir Simulation by Prem Dayal Saini
Reservoir simulation is the study of how fluids flow in a hydrocarbon reservoir when put under production conditions. The purpose is usually to predict the behavior of a reservoir to different production scenarios, or to increase the understanding of its geological properties by comparing known behavior to a simulation using different geological representations.
Apresentação de Victor Manuel Salazar Araque, da Computer Modelling Group, durante o evento promovido pelo Sistema FIEB, Fundamentos da Exploração e Produção de Não Convencionais: a Experiência Canadense.
"Drilling" often refers to all aspects of well construction, including drilling, completions, facilities, construction, the asset team, and other groups. Good performance measures drive performance and reduce conflict between these groups, while bad performance measures mislead and confuse. The first key to success is how to communicate drilling performance in terms that answer the questions of executives and managers, which requires a business-focused cross-functional process. The second key to success is to drive operational performance improvement, which requires a different set of measures with sufficient granularity to define actions. Over the past 10 years, a very workable system has evolved through various approaches used in drilling more than 16,000 wells in the US, South America, and the Middle East. The system has delivered best-in-class performance. It has proven that an effective performance measurement system which addresses both executive requirements and operational requirements can both deliver outstanding results, and also communicate those results, with remarkable value to the organization. The basic principles are widely applicable to areas other than drilling.
In 2010 Shell began investigating how to automate the initial response to a well control incident. The first phase of the project was to develop a rig system that could reliably detect an influx across a broad spectrum of floating rig well construction related rig operations. The results of a fault tree style sensitivity analysis pointed to the high value of improving sensor data quality (both accuracy and reliability) and the importance of improving kick detection software for alarming (both in terms of coverage and how the driller is alerted to respond to a confirmed kick condition). Based on the analysis results, a Smart Kick Detection System functional specification was developed and used to upgrade the kick detection system on an offshore rig.
Early in the project it was realized that focusing on adding robust kick detection during
connections was important but especially challenging due to the associated transient flow and pit volume signatures. A separate in-house initiative was therefore kicked-off to develop new software based on pattern recognition technology and machine learning. The resulting IDAPS (Influx Detection at Pumps Stopped) software has now been implemented as a real-time monitoring application for all Shell operated deep water wells. Further developments in smart kick detection are coming, ultimately leading to rigs being equipped with automated kick detection systems that are relied upon to detect a kick and secure the well in case the driller fails to act.
ResAssure - The World’s Fastest Reservoir Simulator | A Revolution in Reserve...Stochastic Simulation
This Presentation Will:
1. Introduce a new way of evaluating reservoir uncertainty with RESASSURE
2. Illustrate the concepts used
3. Highlight the benefits achieved
4. Demonstrate the value of the results
Stochastic Simulation has unleashed the world’s fastest reservoir simulator, ResAssure, which is set to revolutionize production planning and reserves reporting in the Oil & Gas industry.
ResAssure easily computes > 1 Million realisations within a 24 hour period, a fraction of the time it currently takes with traditional methods and software packages. The release of ResAssure marks a significant milestone in the history of reservoir simulation – the first real industry technology advance in 30 years.
Dr Wadsley, Chief Technology Officer at Stochastic Simulation, commented “ResAssure is capable of quickly generating more accurate reserve estimates than is currently possible by any other software system. The approach taken generates a complete distribution of history matched models all of which are consistent with the geological model and observed production history. The time taken for this is orders of magnitude faster than current history matching methods.”
“Field development planning based on ResAssure’s distribution of models (rather than just upon a single history-matched model using conventional methodologies) will significantly reduce uncertainty and risk.” he added.
By enabling faster and more accurate analysis of dynamic subsurface geological data than has previously been possible, ResAssure markedly reduces the risk in the development of oil and gas fields by narrowing the range of uncertainty in reserves estimates: thereby supporting better production and financing decisions, with substantial increases in project ROI.
ResAssure’s innovation in reservoir simulation solves fully-implicit, dynamic three-phase fluid flow equations for every geological realisation. The speed breakthrough was achieved by a combination of proprietary algorithms, polygonal gridding and aggressive spatial coarsening and time stepping, based upon a conventional finite-difference discretization of the reservoir.
Key Insights Identified:
1. Consistency between volumetric, material balance and fractional flow places very strong constraints on feasible reservoir models.
2. The mathematics of reservoir simulation is NOT complex – it is the geology which is complex.
3. Reserves uncertainty is not quantified, but estimated from current ‘best’ estimate in an ad hoc unsystematic way.
4. What’s the point of preserving mass balance in the simulator when the hydrocarbons in the reservoir are imprecise and we don’t include all production data – mass balance should act to regularise our solution, not to define it.
5. The role of reservoir simulation is not to compute an exact solution of a poorly defined geological model – it is to define a range of feasible reservoir models and associated production forecasts.
Title: Evaluation of Multistage Hydraulic Fracturing Techniques for Production Optimization in Naturally Fractured Reservoirs Using Coupled Geomechanics Fracture and Flow Model
Title: Maximizing the Opportunity in Multi-Layered Tight Sand Reservoirs in a Mature Field by Hydraulic Fracturing: A Case Study of Tight Sand Development Project in Thailand
Overview of Reservoir Simulation by Prem Dayal Saini
Reservoir simulation is the study of how fluids flow in a hydrocarbon reservoir when put under production conditions. The purpose is usually to predict the behavior of a reservoir to different production scenarios, or to increase the understanding of its geological properties by comparing known behavior to a simulation using different geological representations.
Apresentação de Victor Manuel Salazar Araque, da Computer Modelling Group, durante o evento promovido pelo Sistema FIEB, Fundamentos da Exploração e Produção de Não Convencionais: a Experiência Canadense.
Is your business Google-ized? This 3 hour class gives an overview of Inbound Marketing strategies that Google loves! We review on-site SEO, content creation, promotion through social media, lead generation, and the importance of mobile.
Implementing a Hyper-V Virtualization InfrastructureASPE, Inc.
Virtualization is a hot topic today and for good reason. Using virtualization technologies organizations can reduce costs while increasing service provision and technical capabilities. Hyper-V, Microsoft’s latest offering in the virtualization market, presents a whole new virtual machine technology in the Microsoft product line. Comparable to VMware’s ESX server solution, Hyper-V comes out-of-the-box with Windows 2008 Server systems and can integrate with other Microsoft management tools such as System Center and group policies.
In this webinar, we will introduce you to the features and benefits of Hyper-V and you will gain important knowledge including:
· Hardware requirements of Hyper-V
· Benefits of Hyper-V over Virtual Server 2005
· Management options for large-scale implementations
· Deployment planning
· Keys to performance within virtual machines
New Approach to Design Capillary Pressure Curves, which Would Improve Simulat...Faisal Al-Jenaibi
This presentation is discussing New Approach to Design Capillary Pressure Curves, which Would Improve Simulation Models Initialization and shorten History Match time consumed.
An effective reservoir management by streamline based simulation, history mat...Shusei Tanaka
The use of the streamline-based method for reservoir management is receiving increased interest in recent years because of its computational advantages and intuitive appeal for reservoir simulation, history matching and rate allocation optimization. Streamline-based method uses snapshots of flow path of convective flow. Previous studies proved its applicability for convection dominated process such as waterflooding and tracer transport. However, for a case with gas injection with strong capillarity and gravity effects, the streamline-based method tends to lose its advantages for reservoir simulation and may result in loss of accuracy and applicability for history-matching and optimization problems.
In this study, we first present the development of a 3D 3-phase black oil and compositional streamline simulator. Then, we introduce a novel approach to incorporate capillary and gravity effects via orthogonal projection method. The novel aspect of our approach is the ability to incorporate transverse effects into streamline simulation without adversely affecting its computational efficiency. We demonstrate our proposed method for various cases, including CO2 injection scenario. The streamline model is shown to be particularly effective to examine and visualize the interactions between heterogeneity which resulting impact on the vertical and areal sweep efficiencies.
Next, we apply the streamline simulator to history matching and rate optimization problems. In the conventional approach of streamline-based history matching, the objective is to match flow rate history, assuming that reservoir energy was matched already, such as pressure distribution. The proposed approach incorporates pressure information as well as production flow rates, aiming that reservoir energy are also reproduced during production rate matching.
Finally, we develop an NPV-based optimization method using streamline-based rate reallocation algorithm. The NPV is calculated along streamline and used to generate diagnostic plots of the effectiveness of wells. The rate is updated to maximize the field NPV. The proposed approach avoids the use of complex optimization tools. Instead, we emphasize the visual and the intuitive appeal of streamline methods and utilize flow diagnostic plots for optimal rate allocation.
We concluded that our proposed approach of streamline-based simulation, inversion and optimization algorithm improves computational efficiency and accuracy of the solution, which leads to a highly effective reservoir management tool that satisfies industry demands.
Using Six Sigma to reduce ATF pipeline transfer lossesNeelesh Bhagwat
My team's six sigma green belt project where we addressed the high transfer losses during pumping of Jet Fuel from Refinery to Aviation Filling Station.
The lifecycle of developed fields, onshore and offshore will go through different stages of production up to the decline into late field life. Effective reservoir engineering management will lead to prolonging the life of field if a cost effective processing surface facilities strategy is put in place. Factors that lead to the decline in oil production or increase in OPEX may include increased water production, solids handling and the need for relatively higher compression requirements for gas lift. In order to maintain productivity and profitability, an effective holistic engineering approach to optimizing the process surface facilities must be utilized. The challenges of Optimizing Mature Field Production are: 1. Reservoir understanding with potential definition of additional reserves 2. Complete re-appraisal of the operability issues in the production facilities 3. Develop confidence to invest to optimize the process handling capabilities and capacity 4. Low CAPEX simplification of the surface facilities infrastructure to meet challenges 5. An implementation plan that recognizes the ‘Brownfield’ complexities 6. Selection of suitable optimum technology, configuration and training 7. Optimum upgrade plan of the facilities with minimum production losses Successful operation of mature fields and their surface facilities requires successful change management to the new operating strategy. Using a holistic approach can maximize the full potential of mature processing facilities at a manageable CAPEX and OPEX.
Dr. Wally Georgie Dr. Wally Georgie has a B.Sc degree in Chemistry, M.Sc in Polymer Technology, M.Sc in Safety Engineering and PhD in Applied Chemistry with training courses in oil and gas process engineering, production, reservoir and corrosion engineering. He has worked for over 37 years in different areas of oil and gas production facilities, including corrosion control, flow assurance, fluid separation, separator design, gas handling and produced water. He started his career in oil and gas services sector in 1978 based in the UK and working globally with different production issues then joined Statoil as senior staff engineer and later as technical advisor in the Norwegian sector of the North Sea. Working as part of operation team on oil and gas production facilities key focus areas included optimization, operation trouble-shooting, de-bottlenecking, oil water separation, slug handling, process verification, and myriad other fluid and gas handling issues. He then started working in March 1999 as a consultant globally both offshore and onshore, conventional and unconventional in the area of separation trouble shooting, operation assurance, produced water management, gas handling problems, flow assurance, system integrities and production chemistry, with emphasis in dealing with mature facilities worldwide.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
1. POSEIDON
business case
Powered by:
Delivering value-driven solutions
for the Upstream Oil&Gas industry
TM
An innovative breakthrough technology for
Reservoir Management, Surveillance and
Locate The Remaining Oil
7. TIME STEP 1 TIME STEP 2 TIME STEP 3
An effective method to determine and visualize the extent of contact movements within a well.
The impact of intervention (pre vs. post) on well flow characteristics can be readily estimated
using 3-phase inflow calculations.
perforations
Gas shut-off opportunity
Water shut-off opportunity
Pre Post
Liquid rate 1050 530
WCT 55% 15%
GOR 8,000 1,100
Estimated zone
production
characteristics pre
and post gas & water
shutoff
VT_2413
(for illustration purpose only)
ROCM - Complex fractional flow production
inversion of saturation and contacts
Effective
Method
07
12. First Time Step
Validating C-Track
Comparison of invaded zone by gas: Production
calculated gas-liquid contact using POSEIDONTM’s
C-Track Inversion algorithm allows an accurate
estimation of fluid distribution in the well:
SIMULATORPOSEIDONTM
Gas WaterOil
SSTVD
(ft)
Perf
GOC POSEIDONTM
GOC range from simulator
(diffuse flow conditions &
gridblock size)
Last Time Step
• Excellent accuracy of POSEIDONTM’s C-
Track Algorithm vs. simulation.
• C-Track allows to seamlessly assess OWC
and GOC in producing wells
• Log resolution prediction possible
In-well saturation prediction
12
Due to the explicit nature of the saturation function, the ROCM numerical computation is 100x-1000x faster than conventional simulation (seconds vs. minutes or hours)
The inverse problem – finding a saturation distribution that honours material balance and individual well production – becomes solvable within minutes rather than months