413 Confidence courses in Manchester

About this Training Course Comprising 5 full-day sessions, this intermediate to advanced level course is specifically designed for senior exploration geoscientists currently active in hydrocarbon play and prospect mapping, to optimise conceptual geological input into their technical evaluation. The course focuses on seismic stratigraphic analysis in different basin settings - i.e., passive, convergent, extension and oblique - in order to construct a coherent geological story line, underpinning hydrocarbon play and prospect evaluation. The course is largely based on seismic stratigraphic case histories and exercises, with the support of seismic, well log and outcrop examples. Training Objectives Through short, focused presentations and a series of industry case history-based examples and exercises, participants will learn to optimise conceptual geoscience input into technical subsurface analysis. This will help to produce coherent geological subsurface interpretations for use in Play-based, Prospect and Appraisal evaluations. Target Audience This course is intended for senior geoscientists with more than five years of work experience, with a background in play and/or prospect evaluation and experience in seismic interpretation. Course Level Intermediate Advanced Training Methods Participants will be exposed to short lectures throughout the 5 days, followed by hands-on individual and team exercises in a variety of geological settings. 'Let the data tell their story' is a key recurring theme in this course. Trainer Your expert course leader has 38 years of experience as Exploration Geologist for Shell globally, with field experience in a/o Egypt, NW Borneo, MENA, China, Madagascar, North Sea, Oman and The Netherlands (Shell EP Research and Training Centre in Rijswijk). He has strong evaluation and project lead skills in Play-based Exploration, Prospect Maturation, Opportunity Screening and NFE / Appraisal disciplines. He developed key geoscience skills in Seismic and Sequence Stratigraphy as well as Reservoir Characterization, including sedimentology and diagenesis. He has extensive supervisory, teaching, and coaching experience as well as a strong interest in Geoscience (Depositional Systems, Regional and Reservoir Geology) and Petroleum Geology Learning. 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 The Seismic Uncertainty Evaluation (SUE) course has evolved after a number of years of work experience in the sub-surface domain. A common question closely related to well planning is the quantification and qualification of depth uncertainty and robust estimation of the volumetric ranges, and this course addresses these topics. Training Objectives Upon completion of this course, participants will be able to: Define a structured approach toward seismic depth uncertainty analysis Construct data analytics on seismic products (well logs, velocities, and seismic) Classify advance vertical ray tomography on FWI models to assure a drill ready depth seismic, faults, surfaces, and logs Interpret probabilistic volumetric and automatic spill point control, amplitude conformance closures De-risk the depth uncertainty by providing drilling and completion with a risking score card Target Audience This course is intended for individuals who needs to understand the basic theory and procedures for assessment/ quantification/qualification of all drill-ready products (seismic, faults, horizons, etc.) Geologist Geophysicist Reservoir engineer Drilling engineer Course Level Intermediate Trainer Your expert course leader is a cross-functional Geoscientist and Published Author with 27 years of international experience working in Upstream Petroleum Exploration and Production for Oil and Gas Companies in Australia, India, Singapore, Saudi Arabia, and Oman. During his career he actively supported field development, static & dynamic reservoir modelling & well planning, 3D Seismic data acquisition with Schlumberger & SVUL, 3D seismic data processing with CGG & interpretation, Q.I. and field development with Woodside, Applied Geoscience, and Reliance. 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 This 5-day training course enables participants to learn and understand the fundamental concepts of well test analysis. The methodology described in the course, which has become the standard of the industry, presents a systematic way of interpreting well tests in homogeneous and heterogeneous reservoirs, including fissured and multilayered systems. Recommendations for designing tests in such formations, examples, and problem-solving sessions for practical experience and immediate application are included in the course. Training Objectives Upon completion of this course, participants will be able to: Understand the well test analysis methodology Present the straight line, log-log pressure, derivative and deconvolution analysis methods Learn the most common reservoir behaviours and boundary effects Carry out the gas and multiphase analysis Target Audience The course is intended for individuals who involved with the design and interpretation of well tests. The following personnel will benefit from the knowledge shared in this course: Petroleum Production Engineers Production and Wellsite Geologist Geophysicist Reservoir Engineer Drilling Engineer Trainer Your expert course leader has taught numerous well test interpretation industry courses around the world and has been involved in many consulting projects. He is a member of the Society of Petroleum Engineers (SPE) since 1969, and he was elected a Distinguished Member in 2002 and an Honorary Member in 2009. He has chaired or organized many SPE Advanced Technology Workshops. He is a recognized expert in well test analysis and has published over one hundred technical papers and was responsible for many advances in well test interpretation, including: the use of Greens functions; wellbore storage and skin, fractured wells, and wells with double porosity behavior; the first major commercial computer-aided interpretation software; single-well and multi-well deconvolution; and a well test interpretation methodology which has become standard in the oil industry. 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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About this Training Course Materials Management is an essential link in the Supply Chain process. It takes an even bigger significance in the Upstream industry when the cost of a rupture in equipment or stock can be tremendous, without even considering the cost of the equipment itself. The downside may result in the accumulation of out-of-commission materials which leads to business inefficiency. What does it take to maintain efficient Materials Management? This 3 full-day course will explain more in detail. This course can also be offered through Virtual Instructor Led Training (VILT) format. Training Objectives At the end of this course, participants will be able to: Understand the importance of an efficient Materials Management in the Supply Chain process Examine the control and validation of Stock processes Understand the role of the Duet and work within the Stock Duet in materials management Learn about the key factors in Stock optimisation Target Audience This course will benefit all personnel involved in Supply Chain including Stock Controllers, Cost Controllers, Buyers, Logisticians and those from the technical department such as Technical Administrators and members of the duet. Course Level Basic or Foundation Trainer Your expert course leader has 25 years of experience in management positions in Contracting, Procurement and Logistics, mainly in the Oil & Gas Industry. He was a Lecturer for IFP Training for 5 years. During his Oil & Gas industry experience, he has worked on major Oil and Gas development projects like the Yadana project in Myanmar, Akpo project in Nigeria and YLNG in Yemen. His international experience allows him to adapt very easily and integrate the multicultural specificities of the Oil & Gas industry in his teaching. 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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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

Advanced Python training course description This course caters to network engineers aiming to enhance both their Python proficiency and network automation skills. Delving deeper into key areas such as netmiko, Nornir, and ncclient, we also focus on automating network testing and validation. Participants gain greater confidence working with Python functions, classes, objects, and error handling. The course additionally introduces more libraries like Scrapli, TTP, pyATS, Genie, pybatfish, and Suzieq, which cover parsing strategies, automation testing, validation, network analysis, observability, and telemetry. The curriculum also encompasses concurrency techniques. What will you learn Write Python modules and functions. Evaluate techniques to parse unstructured data. Use NETCONF filters. Handle Python errors effectively (try, assert…). Use postman. Automate testing and validation of the network. Use scrapli, Genie, batfish and Suzieq. Advanced Python training course details Who will benefit: Network engineers. Prerequisites: Python for network engineers Duration 5 days Advanced Python training course contents Review CLI, NETCONF, RESTCONF, structured versus unstructured data, gNMI and when to use which. PEP 8. Naming conventions. Packages, modules, Classes and methods. The scrapli library. Netmiko versus scrapli. Hands on: scrapli, Dictionaries versus Regular Expressions. Modules and Functions Writing your own modules, containers versus packages, virtual environments. Best practices, calling functions, writing your own functions. Parameters, arguments. Named arguments, dictionaries as arguments. Builtins. Docstrings. Main. __name__, __main__ . Program arguments. Hands on: Getting interfaces, showing interface status using Netmiko and functions. Using dictionaries as arguments. Writing your own modules. Parsing strategies Turning unstructured data into structured data. textfsm, PyATS Genie parser, NAPALM getters, Template Text Parser. Hands on: Genie parser, TTP. Accessing structured data with lists and dictionaries. Classes, objects and Python Python classes in Genie, PyEZ and others . Hands on: studying network automation classes, objects, methods and attributes. Configuration management - more nornir, ncclient, requests Nornir tasks. Nornir results, Nornir functions, Nornir plugins. Nornir processors. YANG, YANG models, pyang. NETCONF hello. Capabilities. Schemas. Filters. Subtrees. XPATH. Exploring available YANG data models. NETCONF and network wide transactions. Asserting NETCONF capabilities. Configuration types. Locking configurations, commits. NETCONF data stores. Netconf-console. RESTCONF differences from NETCONF. URI construction. Postman. More XML and JSON. Git and configuration versions. Hands on: Nornir and Jinja2. Exploring available models, NETCONF filters. Using postman. Python error handling and debugging Context handlers, try, assert, logging, pdb, pytest, unit testing, chatgpt. Hands on: Writing code with each of the error handling methods, investigating what happens on an error. Use chatgpt to debug your code. Python Automation Testing Testing and validation. pyATS, Genie. Testbed file. Genie parse, genie learn, genie diff. Genie conf, Genie ops, Genie SDK, Genie harness. Xpresso. Hands on: Using Genie for state comparisons of the network. Network analysis Batfish, pybatfish, configuration analysis, analysing routing, analysing ACLs. Pandas. Pandas dataframe. Filtering and selecting values of interest. Hands on: Use Batfish to analyse network snapshots, find network adjacencies, flow path analysis. Network observability Suzieq, using docker, using as a package. Sqpoller, suzieq-gui, suzieq-cli, sq-rest-server. Namespaces and seeing devices, network state and Asserts. Time based analysis, snapshots and changes. Hands on: Suzieq: Gathering data from the network, analysing data from the network. Network state assertion. Telemetry gRPC, gNMI. CAP, GET, SET. Subscriptions. Model Driven telemetry. Hands on: Analysing telemetry data with Python. Concurrency asyncio, threads, processes. Nornir concurrency. Scrapli and netmiko concurrency. Hands on: Multiple SSH connections to devices at same time. Scarpli asyncio.