33 Machine Learning (ML) courses

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

Enhance your knowledge with our EnergyEdge course on Fundamentals of Seismic for Non-Geophysicists. Join us for classroom training to boost your expertise!

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

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 Course This 5 full-day course presents the most modern statistical and mathematical forecasting frameworks used by practitioners to tackle the load forecasting problem across short time and long time scales. The course presents practical applications to solving forecasting challenges, supported by real life examples from large control areas. It presents the weather impacts on the load forecasts and the methodologies employed to quantify the weather effect and building a repository of weather normal data. A good load forecast methodology must improve its forecasting accuracy and support a consistent load forecasting process. The load forecasting widely used in the power industry has evolved significantly with the advancement and adoption of Artificial Intelligence techniques such as Machine Learning. With the increased penetration of inverter-based resources, the operation of electric grids grew in complexity, leading to load forecasts that are updated more frequently than once a day. Furthermore, several jurisdictions adopted a smaller granularity than the hourly load forecasts in the effort to reduce the forecasting uncertainties. On the generation side, fuel forecasting professionals must meet energy requirements while making allowance for the uncertainty on both the demand and the supply side. This training course will also feature a guest speaker, who is a Ph.D candidate to provide insights into the most modern aspects of Artificial Intelligence in the context of load forecasting. Training Objectives This course offers a comprehensive approach to all aspects of load forecasting: Gain a perspective of load forecasting from both operators in the generating plant and system operators. Understand and review the advanced load forecasting concepts and forecasting methodologies Learn the application of Artificial Neural Networks and Probabilistic Forecasting methods to manage forecasting uncertainties in short time frames Appreciate market segmentation and econometric framework for long term forecasts Find out the most recent practical application of load forecasting as examples from large power companies Get access to recent industry reports and developments Target Audience Energy load forecasting professionals from power plant and system operators Energy planners and energy outlook forecasters and plant operators Fuel procurement professionals Planners and schedulers of thermal generating units Course Level Intermediate Trainer Your expert course instructor is a Utility Executive with extensive global experience in power system operation and planning, energy markets, enterprise risk and regulatory oversight. She consults on energy markets integrating renewable resources from planning to operation. She led complex projects in operations and conducted long term planning studies to support planning and operational reliability standards. Specializing in Smart Grids, Operational flexibilities, Renewable generation, Reliability, Financial Engineering, Energy Markets and Power System Integration, she was recently engaged by the Inter-American Development Bank/MHI in Guyana. She was the Operations Expert in the regulatory assessment in Oman. She is a registered member of the Professional Engineers of Ontario, Canada. She is also a contributing member to the IEEE Standards Association, WG Blockchain P2418.5. With over 25 years with Ontario Power Generation (Revenue $1.2 Billion CAD, I/S 16 GW), she served as Canadian representative in CIGRE, committee member in NSERC (Natural Sciences and Engineering Research Council of Canada), and Senior Member IEEE and Elsevier since the 90ties. Our key expert chaired international conferences, lectured on several continents, published a book on Reliability and Security of Nuclear Power Plants, contributed to IEEE and PMAPS and published in the Ontario Journal for Public Policy, Canada. She delivered seminars organized by the Power Engineering Society, IEEE plus seminars to power companies worldwide, including Oman, Thailand, Saudi Arabia, Malaysia, Indonesia, Portugal, South Africa, Japan, Romania, and Guyana. Our Key expert delivered over 60 specialized seminars to executives and engineers from Canada, Europe, South and North America, Middle East, South East Asia and Japan. Few examples are: Modern Power System in Digital Utilities - The Energy Commission, Malaysia and utilities in the Middle East, GCCIA, June 2020 Assessment of OETC Control Centre, Oman, December 2019 Demand Side management, Load Forecasting in a Smart Grid, Oman, 2019 Renewable Resources in a Smart Grid (Malaysia, Thailand, Indonesia, GCCIA, Saudi Arabia) The Modern Power System: Impact of the Power Electronics on the Power System The Digital Utility, AI and Blockchain Smart Grid and Reliability of Distribution Systems, Cyme, Montreal, Canada Economic Dispatch in the context of an Energy Market (TNB, Sarawak Energy, Malaysia) Energy Markets, Risk Assessment and Financial Management, PES, IEEE: Chicago, San Francisco, New York, Portugal, South Africa, Japan. Provided training at CEO and CRO level. Enterprise Risk methodology, EDP, Portugal Energy Markets: Saudi Electricity Company, Tenaga National Berhad, Malaysia Reliability Centre Maintenance (South East Asia, Saudi Electricity Company, KSA) EUSN, ENERGY & UTILITIES SECTOR NETWORK, Government of Canada, 2016 Connected+, IOT, Toronto, Canada September 2016 and 2015 Smart Grid, Smart Home HomeConnect, Toronto, Canada November 2014 Wind Power: a Cautionary Tale, Ontario Centre for Public Policy, 2010 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

Explore cutting-edge power system training with EnergyEdge. Learn about integrating solar, storage, and DERs for efficient energy management. Enroll now!

Gain expertise in managing digitalized oil and gas assets with EnergyEdge's course, focusing on practical applications of digital transformation.

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

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

ITIL® 4 Specialist: Create, Deliver and Support The ITIL® 4 Specialist: Create, Deliver, and Support module is part of the Managing Professional stream for ITIL® 4. Candidates need to pass the related certification exam for working towards the Managing Professional (MP) designation. This course is based on the ITIL® 4 Specialist: Create, Deliver, and Support exam specifications from AXELOS. With the help of ITIL® 4 concepts and terminology, exercises, and examples included in the course, candidates acquire the relevant knowledge required to pass the certification exam. What You Will Learn The learning objectives of the course are based on the following learning outcomes of the ITIL® 4 Specialist: Create, Deliver, and Support exam specification: Understand how to plan and build a service value stream to create, deliver, and support services Know how relevant ITIL® practices contribute to the creation, delivery, and support across the SVS and value streams Know how to create, deliver, and support services Organization and Culture Organizational Structures Team Culture Continuous Improvement Collaborative Culture Customer-Oriented Mindset Positive Communication Effective Teams Capabilities, Roles, and Competencies Workforce Planning Employee Satisfaction Management Results-Based Measuring and Reporting Information Technology to Create, Deliver, and Support Service Integration and Data Sharing Reporting and Advanced Analytics Collaboration and Workflow Robotic Process Automation Artificial Intelligence and Machine Learning CI / CD Information Model Value Stream Anatomy of a Value Stream Designing a Value Stream Value Stream Mapping Value Stream to Create, Deliver, and Support Services Value Stream for Creation of a New Service Value Stream for User Support Value Stream Model for Restoration of a Live Service Prioritize and Manage Work Managing Queues and Backlogs Shift-Left Approach Prioritizing Work Commercial and Sourcing Considerations Build or Buy Sourcing Models Service Integration and Management