37 Inventor courses

About this training course Gas-lift is one of the predominant forms of artificial lift used for lifting liquids from conventional, unconventional, onshore and offshore assets. Gas-lift and its various forms (intermittent lift, gas-assisted plunger lift) allows life of well lift-possibilities when selected and applied properly. This 5-day training course is designed to give participants a thorough understanding of gas-lift technology and related application concepts. This training course covers main components such as application envelope, relative strengths and weaknesses of gas-lift and its different forms like intermittent lift, gas-assisted plunger lift. Participants solve examples and class problems throughout the course. Animations and videos reinforce the concepts under discussion. Unique Features: Hands-on usage of SNAP Software to solve gas-lift exercises Discussion on digital oil field Machine learning applications in gas-lift optimization Training Objectives After the completion of this training course, participants will be able to: Understand the fundamental theories and procedures related to Gas-Lift operations Easily recognize the different components of the gas-lift system and their basic structural and operational features Be able to design a gas-lift installation Comprehend how digital oilfield tools help address ESP challenges Examine recent advances in real-time approaches to the production monitoring and lift management Target Audience This training course is suitable and will greatly benefit the following specific groups: Production, reservoir, completion, drilling and facilities engineers, analysts, and operators Anyone interested in learning about implications of gas-lift systems for their fields and reservoirs Course Level Intermediate Advanced Training Methods The training instructor relies on a highly interactive training method to enhance the learning process. This method ensures that all participants gain a complete understanding of all the topics covered. The training environment is highly stimulating, challenging, and effective because the participants will learn by case studies which will allow them to apply the material taught in their own organization. Course Duration: 5 days in total (35 hours). Training Schedule 0830 - Registration 0900 - Start of training 1030 - Morning Break 1045 - Training recommences 1230 - Lunch Break 1330 - Training recommences 1515 - Evening break 1530 - Training recommences 1700 - End of Training The maximum number of participants allowed for this training course is 20. This course is also available through our Virtual Instructor Led Training (VILT) format. Prerequisites: Understanding of petroleum production concepts. Each participant needs a laptop/PC for solving class examples using software to be provided during class. Laptop/PC needs to have a current Windows operating system and at least 500 MB free disk space. Participants should have administrator rights to install software. Trainer Your expert course leader has over 35 years' work-experience in multiphase flow, artificial lift, real-time production optimization and software development/management. His current work is focused on a variety of use cases like failure prediction, virtual flow rate determination, wellhead integrity surveillance, corrosion, equipment maintenance, DTS/DAS interpretation. He has worked for national oil companies, majors, independents, and service providers globally. He has multiple patents and has delivered a multitude of industry presentations. Twice selected as an SPE distinguished lecturer, he also volunteers on SPE committees. He holds a Bachelor's and Master's in chemical engineering from the Gujarat University and IIT-Kanpur, India; and a Ph.D. in Petroleum Engineering from the University of Tulsa, USA. Highlighted Work Experience: At Weatherford, consulted with clients as well as directed teams on digital oilfield solutions including LOWIS - a solution that was underneath the production operations of Chevron and Occidental Petroleum across the globe. Worked with and consulted on equipment's like field controllers, VSDs, downhole permanent gauges, multiphase flow meters, fibre optics-based measurements. Shepherded an enterprise-class solution that is being deployed at a major oil and gas producer for production management including artificial lift optimization using real time data and deep-learning data analytics. Developed a workshop on digital oilfield approaches for production engineers. Patents: Principal inventor: 'Smarter Slug Flow Conditioning and Control' Co-inventor: 'Technique for Production Enhancement with Downhole Monitoring of Artificially Lifted Wells' Co-inventor: 'Wellbore real-time monitoring and analysis of fracture contribution' Worldwide Experience in Training / Seminar / Workshop Deliveries: Besides delivering several SPE webinars, ALRDC and SPE trainings globally, he has taught artificial lift at Texas Tech, Missouri S&T, Louisiana State, U of Southern California, and U of Houston. He has conducted seminars, bespoke trainings / workshops globally for practicing professionals: Companies: Basra Oil Company, ConocoPhillips, Chevron, EcoPetrol, Equinor, KOC, ONGC, LukOil, PDO, PDVSA, PEMEX, Petronas, Repsol, , Saudi Aramco, Shell, Sonatrech, QP, Tatneft, YPF, and others. Countries: USA, Algeria, Argentina, Bahrain, Brazil, Canada, China, Croatia, Congo, Ghana, India, Indonesia, Iraq, Kazakhstan, Kenya, Kuwait, Libya, Malaysia, Oman, Mexico, Norway, Qatar, Romania, Russia, Serbia, Saudi Arabia, S Korea, Tanzania, Thailand, Tunisia, Turkmenistan, UAE, Ukraine, Uzbekistan, Venezuela. Virtual training provided for PetroEdge, ALRDC, School of Mines, Repsol, UEP-Pakistan, and others since pandemic. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information post training support and fees applicable Accreditions And Affliations

About this training course Artificial lift systems are an important part of production operations for the entire lifecycle of an asset. Often, oil and gas wells require artificial lift for most of the life cycle. This 5-day training course offers a thorough treatment of artificial lift techniques including design and operation for production optimization. With the increasing need to optimize dynamic production in highly constrained cost environments, opportunities and issues related to real-time measurements and optimization techniques needs to be discussed and understood. Artificial lift selection and life cycle analysis are covered. These concepts are discussed and reinforced using case studies, quizzing tools, and exercises with software. Participants solve examples and class problems throughout the course. Animations and videos reinforce the concepts under discussion. Understanding of these important production concepts is a must have to exploit the existing assets profitably. Unique Features: Hands-on usage of SNAP Software to solve gas-lift exercises Discussion on digital oil field Machine learning applications in gas-lift optimization Training Objectives After the completion of this training course, participants will be able to: Understand the basics and advanced concepts of each form of artificial lift systems including application envelope, relative strengths, and weaknesses Easily recognize the different components from downhole to the surface and their basic structural and operational features Design and analyze different components using appropriate software tools Understand challenges facing artificial lift applications and the mitigation of these challenges during selection, design, and operation Learn about the role of digital oilfield tools and techniques and their applications in artificial lift and production optimization Learn about use cases of Machine learning and artificial intelligence in the artificial lift Target Audience This training course is suitable and will greatly benefit the following specific groups: Production, reservoir, completion, drilling and facilities engineers, analysts, and operators Anyone interested in learning about selection, design, analysis and optimum operation of artificial lift and related production systems will benefit from this course. Course Level Intermediate Advanced Training Methods The training instructor relies on a highly interactive training method to enhance the learning process. This method ensures that all participants gain a complete understanding of all the topics covered. The training environment is highly stimulating, challenging, and effective because the participants will learn by case studies which will allow them to apply the material taught in their own organization. Course Duration: 5 days in total (35 hours). Training Schedule 0830 - Registration 0900 - Start of training 1030 - Morning Break 1045 - Training recommences 1230 - Lunch Break 1330 - Training recommences 1515 - Evening break 1530 - Training recommences 1700 - End of Training The maximum number of participants allowed for this training course is 20. This course is also available through our Virtual Instructor Led Training (VILT) format. Prerequisites: Understanding of petroleum production concepts. Each participant needs a laptop/PC for solving class examples using software to be provided during class. Laptop/PC needs to have a current Windows operating system and at least 500 MB free disk space. Participants should have administrator rights to install software. Trainer Your expert course leader has over 35 years' work-experience in multiphase flow, artificial lift, real-time production optimization and software development/management. His current work is focused on a variety of use cases like failure prediction, virtual flow rate determination, wellhead integrity surveillance, corrosion, equipment maintenance, DTS/DAS interpretation. He has worked for national oil companies, majors, independents, and service providers globally. He has multiple patents and has delivered a multitude of industry presentations. Twice selected as an SPE distinguished lecturer, he also volunteers on SPE committees. He holds a Bachelor's and Master's in chemical engineering from the Gujarat University and IIT-Kanpur, India; and a Ph.D. in Petroleum Engineering from the University of Tulsa, USA. Highlighted Work Experience: At Weatherford, consulted with clients as well as directed teams on digital oilfield solutions including LOWIS - a solution that was underneath the production operations of Chevron and Occidental Petroleum across the globe. Worked with and consulted on equipment's like field controllers, VSDs, downhole permanent gauges, multiphase flow meters, fibre optics-based measurements. Shepherded an enterprise-class solution that is being deployed at a major oil and gas producer for production management including artificial lift optimization using real time data and deep-learning data analytics. Developed a workshop on digital oilfield approaches for production engineers. Patents: Principal inventor: 'Smarter Slug Flow Conditioning and Control' Co-inventor: 'Technique for Production Enhancement with Downhole Monitoring of Artificially Lifted Wells' Co-inventor: 'Wellbore real-time monitoring and analysis of fracture contribution' Worldwide Experience in Training / Seminar / Workshop Deliveries: Besides delivering several SPE webinars, ALRDC and SPE trainings globally, he has taught artificial lift at Texas Tech, Missouri S&T, Louisiana State, U of Southern California, and U of Houston. He has conducted seminars, bespoke trainings / workshops globally for practicing professionals: Companies: Basra Oil Company, ConocoPhillips, Chevron, EcoPetrol, Equinor, KOC, ONGC, LukOil, PDO, PDVSA, PEMEX, Petronas, Repsol, , Saudi Aramco, Shell, Sonatrech, QP, Tatneft, YPF, and others. Countries: USA, Algeria, Argentina, Bahrain, Brazil, Canada, China, Croatia, Congo, Ghana, India, Indonesia, Iraq, Kazakhstan, Kenya, Kuwait, Libya, Malaysia, Oman, Mexico, Norway, Qatar, Romania, Russia, Serbia, Saudi Arabia, S Korea, Tanzania, Thailand, Tunisia, Turkmenistan, UAE, Ukraine, Uzbekistan, Venezuela. Virtual training provided for PetroEdge, ALRDC, School of Mines, Repsol, UEP-Pakistan, and others since pandemic. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information post training support and fees applicable Accreditions And Affliations

About this training course Business Impact: The main aim is to provide insight and understanding of data analytics and machine learning principles through applications. Field data is used to explain data-analysis workflows. Using easy to follow solution scripts, the participants will assess and extract value from the data sets. Hands-on solution approach will give them confidence to try out applicable techniques on data from their field assets. Data analysis means cleaning, inspecting, transforming, and modeling data with the goal of discovering new, useful information and supporting decision-making. In this hands-on 2-day training course, the participants learn some data analysis and data science techniques and workflows applied to petroleum production (specifically artificial lift) while reviewing code and practicing. The focus is on developing data-driven models while keeping our feet closer to the underlying oil and gas production principles. Unique Features: Eight business use cases covering their business impact, code walkthroughs for most all and solution approach. Industry data sets for participants to practice on and take home. No software or complicated Python frameworks required. Training Objectives After the completion of this training course, participants will be able to: Understand digital oil field transformation and its impact on business Examine machine learning methods Review workflows and code implementations After completing the course, participants will have a set of tools and some pathways to model and analyze their data in the cloud, find trends, and develop data-driven models Target Audience This training course is suitable and will greatly benefit the following specific groups: Artificial lift, production and facilities engineers and students to enhance their knowledge base, increase technology awareness, and improve the facility with different data analysis techniques applied on large data sets Course Level Intermediate Advanced Training Methods The course discusses several business use-cases that are amenable to data-driven workflows. For each use case, the instructor will show the solution using a data analysis technique with Python code deployed in the Google cloud. Trainees will solve a problem and tweak their solution. Course Duration: 2 days in total (14 hours). Training Schedule 0830 - Registration 0900 - Start of training 1030 - Morning Break 1045 - Training recommences 1230 - Lunch Break 1330 - Training recommences 1515 - Evening break 1530 - Training recommences 1700 - End of Training The maximum number of participants allowed for this training course is 20. This course is also available through our Virtual Instructor Led Training (VILT) format. Prerequisites: Understanding of petroleum production concepts Knowledge of Python is not a must but preferred to get the full benefit. The training will use the Google Collaboratory environment available in Google-Cloud for hands-on exercises Trainees will need to bring a computer with a Google Chrome browser and a Google email account (available for free) Trainer Your expert course leader has over 35 years' work-experience in multiphase flow, artificial lift, real-time production optimization and software development/management. His current work is focused on a variety of use cases like failure prediction, virtual flow rate determination, wellhead integrity surveillance, corrosion, equipment maintenance, DTS/DAS interpretation. He has worked for national oil companies, majors, independents, and service providers globally. He has multiple patents and has delivered a multitude of industry presentations. Twice selected as an SPE distinguished lecturer, he also volunteers on SPE committees. He holds a Bachelor's and Master's in chemical engineering from the Gujarat University and IIT-Kanpur, India; and a Ph.D. in Petroleum Engineering from the University of Tulsa, USA. Highlighted Work Experience: At Weatherford, consulted with clients as well as directed teams on digital oilfield solutions including LOWIS - a solution that was underneath the production operations of Chevron and Occidental Petroleum across the globe. Worked with and consulted on equipment's like field controllers, VSDs, downhole permanent gauges, multiphase flow meters, fibre optics-based measurements. Shepherded an enterprise-class solution that is being deployed at a major oil and gas producer for production management including artificial lift optimization using real time data and deep-learning data analytics. Developed a workshop on digital oilfield approaches for production engineers. Patents: Principal inventor: 'Smarter Slug Flow Conditioning and Control' Co-inventor: 'Technique for Production Enhancement with Downhole Monitoring of Artificially Lifted Wells' Co-inventor: 'Wellbore real-time monitoring and analysis of fracture contribution' Worldwide Experience in Training / Seminar / Workshop Deliveries: Besides delivering several SPE webinars, ALRDC and SPE trainings globally, he has taught artificial lift at Texas Tech, Missouri S&T, Louisiana State, U of Southern California, and U of Houston. He has conducted seminars, bespoke trainings / workshops globally for practicing professionals: Companies: Basra Oil Company, ConocoPhillips, Chevron, EcoPetrol, Equinor, KOC, ONGC, LukOil, PDO, PDVSA, PEMEX, Petronas, Repsol, , Saudi Aramco, Shell, Sonatrech, QP, Tatneft, YPF, and others. Countries: USA, Algeria, Argentina, Bahrain, Brazil, Canada, China, Croatia, Congo, Ghana, India, Indonesia, Iraq, Kazakhstan, Kenya, Kuwait, Libya, Malaysia, Oman, Mexico, Norway, Qatar, Romania, Russia, Serbia, Saudi Arabia, S Korea, Tanzania, Thailand, Tunisia, Turkmenistan, UAE, Ukraine, Uzbekistan, Venezuela. Virtual training provided for PetroEdge, ALRDC, School of Mines, Repsol, UEP-Pakistan, and others since pandemic. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information post training support and fees applicable Accreditions And Affliations

Elevate your knowledge in gas lift design optimization with EnergyEdge's classroom training. Join us to stay ahead in the industry!

Enhance oilfield production with our Artificial Lift and Real-Time Production Optimization course. Join EnergyEdge's classroom training for expert insights.

Enhance your skills in data analytics for artificial lift production and facility engineering with EnergyEdge's course. Sign up now!

Overview This one day course covers the basics of brainstorming and then goes on to look at a number of different yet highly effective techniques that can be employed. Description Brainstorming is probably the most well known and most widely used method for bringing groups of people together to generate ideas about an issue or problem. This is because it’s a good way to gather a lot of ideas very quickly. It is also a great way of bringing people together and helping to build them as a team. Just imagine the effect on the team and its morale if ideas that they generate are actually used. There is no doubt that people are more likely to buy into the ideas that they came up with themselves. Although brainstorming is widely used for decision-making, it is not always handled very well. If that is the case, it can have the opposite effect to the one that is intended. Rather than creating ideas it can stifle them and rather than motivating people it demotivates them. This highly interactive course will help learners to make the most of brainstorming sessions and also provides alternative techniques to enliven any session that is beginning to flag. Topics covered: What is Brainstorming? – A discussion to help participants understand what brainstorming is, and what it involves. Brainstorming rules – A quick look at the very limited rules suggested by Alex Osborn who is generally credited with being the inventor of brainstorming. Preparation – Although many brainstorming sessions take place on the spur of the moment they all require some preparation. We look at the importance of defining the purpose of the session, selecting the right participants, and then briefing them properly. Storm and Floods – This is an activity that we re-visit on several occasions to take participants through the whole brainstorming process and to give them plenty of practice. The Three R’s of Facilitation – The three R’s take you through the essential elements of facilitating an effective brainstorming session. Closing the Session – Effective closing of the brainstorm may be just as important as the session itself. We look at the essential elements that the facilitator needs to cover. Clarify and Nurture – Learners discover the importance of ensuring that all ideas that are unclear are clarified and that ideas are nurtured. They also learn what this involves practically. Alternative Techniques – There are many ways to enliven a flagging brainstorming session, provide a fresh approach or simply build on initial ideas. The learners are introduced to some of the most important of these. Brainstorming Scenarios – Learners work through up to 6 scenarios so that they can practice the alternative techniques covered during the programme. Who should attend Anyone who facilitates or takes part in brainstorming sessions, or wants to work with organisational teams to develop their problem-solving abilities. Requirements for Attendees None.

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Network DevOps course description This course is not a soft skills course covering the concepts of DevOps but instead concentrates on the technical side of tools and languages for network DevOps. Particular technologies focussed on are ansible, git and Python enabling delegates to leave the course ready to starting automating their network. Hands on sessions follow all major sections. More detailed courses on individual aspects of this course are available. What will you learn Evaluate network automation tools. Automate tasks with ansible. Use git for version control. Use Python to manage network devices. Use Python libraries for network devices. Network DevOps course details Who will benefit: Administrators automating tasks. Prerequisites: TCP/IP Foundation Duration 5 days Network DevOps course contents What is DevOps Programming and automating networks, networks and clouds, AWS, OpenStack, SDN, DevOps for network operations. Initial configuration Configuring SSH, ZTP, POAP. Hands on Initial lab configuration. Getting started with ansible The language, the engine, the framework. Uses of ansible, orchestration. The architecture, Controlling machines, nodes, Agentless, SSH, modules. Configuration management, inventories, playbooks, modules, roles. Hands on Installing ansible, running ad hoc commands. Ansible playbooks ansible-playbook, YAML, plays, tasks, handlers, modules. Playbook variables. Register module, debug module. Hands on Running playbooks. Ansible Inventories /etc/ansible/hosts, hosts, groups, static inventories, dynamic inventories. Inventory variables, external variables. Limiting hosts. Hands on Static inventories, variables in inventory files. Ansible modules for networking Built in modules, custom modules, return values. Core modules for network operations. Cisco and/or Juniper modules. ansible_connection. Ansible 2.6 CLI. Hands on Using modules. Ansible templating and roles aConfiguration management, full configurations, partial configurations. The template module, the assemble module, connection: local, Jinja2 templates, variables, if, for, roles. Hands on Generating multiple configurations from a template. Network programming and modules Why use Python? Why use ansible? alternatives, ansible tower, Linux network devices. Programming with Python Python programming Functions. Classes, objects and instances, modules, libraries, packages. Python strings, Python file handling, pip list, pip instal. Hands on Python programming with pyping. More Python programming Functions. Classes, objects and instances, modules, libraries, packages. Python strings, Python file handling, pip list, pip install. Hands on Python programming with pyping. Git Distributed version control, repositories, Git and GitHub, Alternatives to GitHub, Installing git, git workflows, creating repositories, adding and editing files, branching and merging, merge conflicts. Hands on working with Git. Python and networking APIs, Sockets, Telnetlib, pysnmp, ncclient, ciscoconfparse. Paramiko SSH and Netmiko Integrating Python and network devices using SSH. Netmiko, Netmiko methods. Hands on Netmiko. NAPALM What is NAPALM, NAPALM operations, getters, Replace, merge, compare, commit, discard. Hands on Configuration with NAPALM. Integrating ansible and NAPALM. Python and REST REST APIs, enabling the REST API. Accessing the REST API with a browser, cURL, Python and REST, the request library. Hands on Using a REST API with network devices.

Network automation course description This course is not a soft skills course covering the concepts of DevOps but instead concentrates on the technical side of tools and languages for network DevOps. Particular technologies focussed on are ansible, git and Python enabling delegates to leave the course ready to starting automating their network. Hands on sessions follow all major sections. More detailed courses on individual aspects of this course are available. What will you learn Evaluate network automation tools. Automate tasks with ansible. Use git for version control. Use Python to manage network devices. Use Python libraries for network devices. Network automation course details Who will benefit: Network engineers. Prerequisites: TCP/IP foundation for engineers. Duration 5 days Network automation course contents What is DevOps Programming and automating networks, networks and clouds, AWS, OpenStack, SDN, DevOps for network operations. Initial configuration Configuring SSH, ZTP, POAP. Hands on Initial lab configuration. Getting started with ansible The language, the engine, the framework. Uses of ansible, orchestration. The architecture, Controlling machines, nodes, Agentless, SSH, modules. Configuration management, inventories, playbooks, modules, roles. Hands on Installing ansible, running ad hoc commands. Ansible playbooks ansible-playbook, YAML, plays, tasks, handlers, modules. Playbook variables. Register module, debug module. Hands on Running playbooks. Ansible Inventories /etc/ansible/hosts, hosts, groups, static inventories, dynamic inventories. Inventory variables, external variables. Limiting hosts. Hands on Static inventories, variables in inventory files. Ansible modules for networking Built in modules, custom modules, return values. Core modules for network operations. Cisco and/ or Juniper modules. ansible_connection. Ansible 2.6 CLI. Hands on Using modules. Ansible templating and roles Configuration management, full configurations, partial configurations. The template module, the assemble module, connection: local, Jinja2 templates, variables, if, for, roles. Hands on Generating multiple configurations from a template. Network programming and modules Why use Python? Why use ansible? alternatives, ansible tower, Linux network devices. Programming with Python Scripting versus application development, Python interactive mode, Python scripts, Python 2.7 vs Python 3. A simple Python script. Variables, loops, control statements, operators. PEP style guide. Python IDEs. Hands on Simple Python programs. More Python programming Functions. Classes, objects and instances, modules, libraries, packages. Python strings, Python file handling, pip list, pip install, Hands on Python programming with pyping. Git Distributed version control, repositories, Git and GitHub, Alternatives to GitHub, Installing git, git workflows, creating repositories, adding and editing files, branching and merging, merge conflicts. Hands on working with Git. Python and networking APIs, Sockets, Telnetlib, pysnmp, ncclient, ciscoconfparse. Paramiko SSH and Netmiko Integrating Python and network devices using SSH. Netmiko, Netmiko methods. Hands on Netmiko. PyEZ Juniper, NETCONF, installing PyEZ, a first pyEZ script, pyEZ configuration management. Hands on Juniper configuration management with pyEZ. NAPALM What is NAPALM, NAPALM operations, getters, Replace, merge, compare, commit, discard. Hands on Configuration with NAPALM. Integrating ansible and NAPALM. Python and REST REST APIs, enabling the REST API. Accessing the REST API with a browser, cURL, Python and REST, the request library. Hands on Using a REST API with network devices.