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About this Training Course This intensive 5 full-day has been designed as a separately bookable course comprising 3 days of Well Integrity (Basic) and 2 days of Advanced Well Integrity. The intensive 3 full-day course will equip the participants with a thorough knowledge of well integrity management and risk assessment in producing assets. Based on the regulatory requirements and using real examples and exercises from around the world, this represents best practice integrity management within the oil and gas industry. When to take action with a well is a critical decision, both from a safety and economic perspective. A consistent approach to decision-making provides certainty within the organisation, focusing effort, and spending wisely. The decision-making steps will be set out to ensure all critical aspects are captured consistently. Risk analysis approaches used by different organisations and examples of risk management and risk-ranking methods will be discussed. The 2 full-day course will deepen the participants' knowledge of well integrity management, and skills for designing, operating, and maintaining well equipment. The ultimate goal is to optimise productivity at the lowest Unit Operating Cost (UOC) and to maintain mechanical integrity throughout well life cycle. Well Integrity management is looked at in three distinct stages. The first stage is during the well design which includes material selection, engineering design, cement design, coating and inhibitors and cathodic protection. The second stage is monitoring the well during the life of the well, locating possible leaks and / or loss of metal. The last stage is to manage and control any well integrity issues using specialised products, services and techniques. Training Objectives 1. Well Integrity Training: Upon completion of this course, the participants will be able to: Define the building blocks of a successful well integrity management system Develop an approach to risk management, understand risk analysis and methods applied across the industry How do we 'Make Wells Safer', learn about emerging technologies for well integrity problem diagnosis and new techniques available to 'repair' the issues Execute the basic elements of well integrity management training for field operators Evaluate well design elements that enhance or hinder well integrity status definition during the operating phase of the well life-cycle Gain the demonstrable benefits of well integrity management from field experience Review cases studies and discuss them to enhance knowledge and take on board lessons learned 2. Advanced Well Integrity: Define well integrity well categorization based on compliance to the barrier policy outlined in the regulations and develop an approach to risk management Discuss well-completion design and construction to create a 'integer' well with the lowest life cycle maintenance cost from a WIM perspective Monitoring and surveillance of well integrity, focusing on barrier competence such as cementing and corrosion Investigate and manage well integrity issues, causes & potential solutions Understand repairs needed to address 'Loss of Well Operating Envelope' Gain an overview understanding of Well Suspension & Well Abandonment Discuss further case studies as well as conduct a post course test Target Audience Invaluable for production, operations, and integrity professionals involved in implementing & managing well integrity and seeking to improve performance. It is also essential for those who need to develop and implement such systems, or who have a general need to know and understand more about well integrity management. The course will also provide a fresh approach for senior professionals and managers. Designed for professionals in the oil and gas industry who are involved in the design, construction and operation of wells from the following disciplines: Production Maintenance Production Operations Drilling Engineering Safety engineering Well Intervention Well Integrity Engineering Asset Management Course Level Intermediate Advanced Trainer Gordon Duncan has over 40 years of experience in the Oil & Gas industry. During that time, he has worked exclusively in well intervention and completions. After a number of years working for intervention service companies (completions, slickline & workovers), he joined Shell as a well service supervisor. He was responsible for the day-to-day supervision of all well intervention work on Shell's Persian/Arabian Gulf platforms. This included completion running, coil tubing, e-line, slickline, hydraulic workovers, well testing and stimulation operations. An office-based role as a senior well engineer followed. He was responsible for planning, programming and organising of all the well engineering and intervention work on a number of fields in the Middle East. He had a brief spell as a Site Representative for Santos in Australia before joining Petro-Canada as Completions Superintendent in Syria, then moved to Australia as Completions Operations Superintendent for Santos, before returning to Shell as Field Supervisor Completions and Well Interventions in Iraq where he carried out the first ever formal abandonment of a well in the Majnoon Field. While working on rotation, he regularly taught Completion Practices, Well Intervention, Well Integrity and Reporting & Planning courses all over the world. In 2014, he started to focus 100% on training and became the Technical Director for PetroEDGE. Since commencing delivering training courses in 2008, he has taught over 300 courses in 31 cities in 16 countries to in excess of 3,500 participants. 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

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Machine literacy in data wisdom is a fleetly expanding discipline and now is the crucial element. This groundbreaking field equips computers and systems with the capacity to learn from data and ameliorate their performance over time without unequivocal programming. Statistical ways are employed to train algorithms to produce groups or prognostications and to find significant findings in data mining systems. immaculately, the conclusions made from these perceptivity impact crucial growth pointers in operations and companies. What's Machine Learning? . Machine learning classes in pune The machine literacy term was chased by Arthur Samuel in 1959. It's the discipline solely concentrated on studying and erecting tools and ways that can let machines learn. These styles use data to enhance the computer performance of a particular set of tasks. Machine literacy algorithms induce prognostications or possibilities and produce a model grounded on data samples, also called training data. There's a need for machine literacy as these algorithms are applied in a broad range of operations, for illustration, computer vision, dispatch filtering, speech recognition, husbandry, and drugs, where it's a challenge to produce traditional algorithms that can negotiate the needed tasks. orders in Machine Learning Being such a vast and complicated field, machine literacy is divided into three different orders machine literacy orders Supervised literacy – In this system, the algorithm is trained using data that has been labeled and in which the target variable or asked result is known. Once trained, the algorithm may make prognostications grounded on unidentified information by learning how to associate input variables with the willed affair. Unsupervised literacy – In this case, the algorithm is trained on unlabeled data, and its thing is to discover structures or patterns within the data without having a specific target variable in mind. Common unsupervised literacy tasks include dimensionality reduction and clustering. underpinning literacy – An algorithm is trained via relations with the terrain in this type of literacy. The algorithm learns how to operate in order to maximize a price signal or negotiate a particular ideal. Through prices or penalties, it receives feedback that helps it upgrade its decision-making process. Artificial Intelligence and Machine Learning Artificial intelligence( AI) is divided into several subfields, and machine literacy( ML) is one of them. In order to produce intelligent machines that can pretend mortal intelligence, a variety of methodologies, approaches, and technologies are used. This notion is known as artificial intelligence( AI). The development of ways and models that allow computers to acquire knowledge from data and make recommendations or judgments without unequivocal programming is the focus of machine literacy( ML). Some academics were interested in the idea of having machines learn from data in the early stages of AI as an academic field. They tried to approach the issue using colorful emblematic ways and neural networks. They were primarily perceptrons, along with other models that were ultimately discovered to be reimaginings of the generalized direct models of statistics. For this case, you aim to make a system secerning cows and tykes. With the AI approach, you'll use ways to make a system that can understand the images with the help of specific features and rules you define. Machine literacy models will bear training using a particular dataset of pre-defined images. You need to give numerous farmlands of cows and tykes with corresponding markers. Why is Machine Learning Important? Machine literacy is an abecedarian subfield of artificial intelligence that focuses on assaying and interpreting patterns and structures in data. It enables logic, literacy, and decision-making outside of mortal commerce. The significance of machine literacy is expanding due to the extensively more expansive and more varied data sets, the availability and affordability of computational power, and the availability of high-speed internet. It facilitates the creation of new products and provides companies with a picture of trends in consumer geste and commercial functional patterns. Machine literacy is a high element of the business operations of numerous top enterprises, like Facebook, Google, and Uber. Prophetic Analytics Machine learning course in pune Machine literacy makes prophetic analytics possible by using data to read unborn results. It's salutary in the fields of finance, healthcare, marketing, and logistics. Associations may prognosticate customer growth, spot possible troubles, streamline operations, and take visionary action to ameliorate results using prophetic models. Personalization and recommendation systems Machine literacy makes recommendation systems and substantiated gests possible, impacting every aspect of our diurnal lives. Platforms like Netflix, Amazon, and Spotify use machine literacy algorithms to comprehend stoner preferences and offer substantiated recommendations. Personalization boosts stoner pleasure and engagement while promoting business expansion. Image and speech recognition Algorithms for machine literacy are particularly good at jobs like speech and picture recognition. Deep literacy, a branch of ML, has converted computer vision and natural language processing. It makes it possible for machines to comprehend, dissect, and produce visual and audio input. This technology is helpful for driverless vehicles, surveillance, medical imaging, and availability tools, among other effects. Machine learning training in pune

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