2069 RES courses in London

About this Training Course Reservoir engineering methods, data and models are used in the E&P business to describe and optimise hydrocarbon recovery. This 5 full-day course addresses reservoir engineering concepts and methods to enable cross-disciplinary team work and the smooth exchange of ideas and experience. In this course, participants will gain an in-depth understanding of the fundamentals of reservoir engineering and a broad range of modern reservoir engineering principles and practices for reservoir development and production, including the estimation of oil and gas reserves. The topics covered in this course will be illustrated with practical and actual field cases. Some self-study or reading will be required from participants. Training Objectives By the end of this course, participants will be able to: Describe use of permeability and fluid saturation in reservoir engineering. Explain the assessment of hydrocarbon resources and recoverable reserves estimation. Understand analysis and modelling of fluid behaviour. Explain oil and gas reservoir performance. Describe material balance methods in oil and gas reservoirs. Understand design and analysis of well tests. Understand analysis and production of producing wells and forecasting methods. Describe fluid displacement at the pore and reservoir scale. Explain reservoir simulation approaches. Describe tools for handling the uncertainty in reservoir analysis. Describe various recovery methods from primary to enhanced recovery. Target Audience This course is intended for professionals with prior technical or engineering exposure to exploration and production activities. Targeted participants include geoscientists, production engineers, petrophysicists and petroleum engineers involved with exploration and development of oil & gas reservoirs. The course will also benefit petroleum engineering team leaders as well as IT staff and support staff who work with reservoir engineering, development and production departments. Course Level Basic or Foundation Trainer Your expert course leader is an independent Reservoir Engineering Consultant, providing project consultancy and reservoir engineering training for global customers. He retired from Shell in 2012 and during the last years of his Shell career, he held the Senior Reserves Consultant for the Middle East and Reservoir Engineering Discipline Lead positions. He is a seasoned Petroleum Engineering professional, with global experience in Shell companies and joint ventures (NAM, SSB, SCL, PDO, SKDBV). His technical expertise is in reserves and resource management, reservoir engineering quality assurance, and staff development as well as carbonate reservoirs, modelling and reservoir simulation.  PROFESSIONAL EXPERIENCE 2012 to date Independent Reservoir Engineering Consultant Petroleum and reservoir engineering advice, training and services. Reservoir engineering training for major oil companies, engineering firms and other global customers. Assurance of SPE and SEC reserves compliance. Participation in SPE reserves and resources estimation Advanced Technology Workshops both as an organising committee member and as session speaker.   2008 - 2012 Shell International E&P, the Hague, the Netherlands Senior Reserves Consultant for Shell business units and joint ventures in the Middle East Region Assurance of SEC and SPE compliance of reserves and resources. Industry publications and conference contributions a.o. SPE guidelines on probabilistic reserves estimation.   2006 - 2008 Shell E&P Technology Solutions, Rijswijk, the Netherlands Reservoir Engineering Discipline Lead Responsible for Reservoir Engineering in global projects and for staff planning and development (over 60 international Reservoir Engineers).   2001 - 2005 Centre for Carbonate Studies, SQU, Oman / Shell International E&P Applications and Research / Shell Representative Office Oman   Petroleum Engineering Manager PE Manager in the Carbonate Research Centre, a joint venture between Sultan Qaboos University in Oman and Shell International. Industrial research projects and teaching on recovery aspects of carbonate reservoir development.   1997 - 2000 Shell International E&P, Rijswijk, the Netherlands Principal Reservoir Engineer Coordination of the NOV subsurface team in Shell Kazakhstan Development BV in 2000. Leading role in Shell Gamechanger project on natural gas hydrates. Acting Shell Group Reserves Co-ordinator in 1997-1998. Facilitation of workshops with government shareholders, including discussions on sensitive reserves issues (BSP Petroleum Unit Brunei, PDO Oman, SPDC government Nigeria).   1992 - 1996 Shell Training Centre, Noordwijkerhout, the Netherlands Reservoir Engineering Programme Training Director Advanced PE training events, QA/QC, design and delivery of courses to Shell staff.   1985 - 1992 Shell International, SIPM, the Hague, The Netherlands Senior Reservoir Engineer Reservoir simulation, integrated reservoir modelling and gas field development and major contributor to the Shell internal Gas Field Planning Tool development. Full field reservoir simulation projects supporting Field Development Plans, operational strategies and unitisation negotiations for Shell Group Operating Companies in the United Kingdom, New Zealand and Egypt.   1984 - 1985 Geological Survey of the Netherlands, Ministry of Economic Affairs Reservoir Engineering Section Head Responsible for Petroleum Engineering advice on oil and gas licences to the Ministry of Economic Affairs. First-hand experience with a government view on resource management.   1976 - 1984 NAM, Assen, The Netherlands and SSB/SSPC, Miri, Malaysia Wellsite Operations Engineer / Operational Reservoir Engineer 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

MICROBLADING HAS BECOME ONE OF THE MOST POPULAR TREATMENTS IN RECENT YEARS, BUT RESULTS ARE LIMITED TO HAIRSTROKE BROWS AND FREQUENTLY CLIENTS WILL REQUEST SOME SHADING WHICH IS MORE EASILY ACHIEVED WITH DIGITAL PERMANENT MAKEUP.

Professor Meredith A. Crowley, Professor of Economics at Cambridge University, will give the 2025 IFS Annual Lecture on "Trade Wars and the Future of Globalisation". The world enjoyed a dramatic fall in policy barriers to international trade and rising international integration of national markets throughout the 1990s and 2000s. However, since 2010, trade integration has stalled, with the global trade to GDP ratio hovering around 30 percent. Over the last fifteen years, the world has witnessed Britain’s exit from the EU, the 2018 US-China Trade War, major trade sanctions against Russia, and, most recently, the threat of broader American trade restrictions. This lecture will examine recent evidence on exporting firms in multiple countries and suggest new approaches to evaluating the price and welfare impacts of market fragmentation due to Brexit and the US-China Trade War. Meredith A. Crowley is a Professor of Economics at the University of Cambridge, a Fellow of St. John’s College Cambridge, President of the International Economics and Finance Society, and a Research Fellow at the Centre for Economic Policy Research (CEPR – London). Her research, focused on international trade, trade policy, and exchange rates has been published in numerous peer-reviewed journals including the American Economic Review and the Journal of International Economics. She has appeared or been cited in over 100 print and broadcast media outlets including the BBC, The New York Times, The Washington Post, The Economist, The Financial Times, The Guardian, The Telegraph, The Times and National Public Radio (US). Prior to arriving at Cambridge in 2013, Crowley worked in the Research Department of the Federal Reserve Bank of Chicago. She has taught at Georgetown University, the Shanghai University of Finance and Economics, and Nanjing University. She has presented her research at central banks and international institutions around the world, including the International Monetary Fund, the World Bank, and the World Trade Organization. Crowley received her MPP from Harvard University and her PhD in Economics from the University of Wisconsin-Madison.

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Lean Six Sigma Black Belt Certification Program This course is specifically for people wanting to become Lean Six Sigma Black Belts, who are already Lean Six Sigma practitioners. If advanced statistical analysis is needed to identify root causes and optimal process improvements, (Lean) Six Sigma Green Belts typically ask Black Belts or Master Black Belts to conduct these analyses. This course will change that. Green Belts wanting to advance their statistical abilities will have a considerable amount of hands-on practice in techniques such as Statistical Process Control, MSA, Hypothesis Testing, Correlation and Regression, Design of Experiments, and many others. Participants will also work throughout the course on a real-world improvement project from their own business environment. This provides participants with hands-on learning and provides the organization with an immediate ROI once the project is completed. IIL instructors will provide free project coaching throughout the course. What you Will Learn At the end of this program, you will be able to: Use Minitab for advanced data analysis Develop appropriate sampling strategies Analyze differences between samples using Hypothesis Tests Apply Statistical Process Control to differentiate common cause and special cause variation Explain and apply various process capability metrics Conduct Measurement System Analysis and Gage R&R studies for both discrete and continuous data Conduct and analyze simple and multiple regression analysis Plan, execute, and analyze designed experiments Drive sustainable change efforts through leadership, change management, and stakeholder management Successfully incorporate advanced analysis techniques while moving projects through the DMAIC steps Explain the main concepts of Design for Six Sigma including QFD Introduction: DMAIC Review IIL Black Belt Certification Requirements Review Project Selection Review Define Review Measure Review Analyze Review Improve Review Control Introduction: Minitab Tool Introduction to Minitab Minitab basic statistics and graphs Special features Overview of Minitab menus Introduction: Sampling The Central Limit Theorem Confidence Interval of the mean Sample size for continuous data (mean) Confidence Interval for proportions Sample size for discrete data (proportions) Sampling strategies (review) Appendix: CI and sample size for confidence levels other than 95% Hypothesis Testing: Introduction Why use advanced stat tools? What are hypothesis tests? The seven steps of hypothesis tests P value errors and hypothesis tests Hypothesis Testing: Tests for Averages 1 factor ANOVA and ANOM Main Effect Plots, Interaction Plots, and Multi-Vari Charts 2 factor ANOVA and ANOM Hypothesis Testing: Tests for Standard Deviations Testing for equal variance Testing for normality Choosing the right hypothesis test Hypothesis Testing: Chi Square and Other Hypothesis Test Chi-square test for 1 factor ANOM test for 1 factor Chi-square test for 2 factors Exercise hypothesis tests - shipping Non-parametric tests Analysis: Advanced Control Charts Review of Common Cause and Special Cause Variation Review of the Individuals Control Charts How to calculate Control Limits Four additional tests for Special Causes Control Limits after Process Change Discrete Data Control Charts Control Charts for Discrete Proportion Data Control Charts for Discrete Count Data Control Charts for High Volume Processes with Continuous Data Analysis: Non-Normal Data Test for normal distribution Box-Cox Transformation Box-Cox Transformation for Individuals Control Charts Analysis: Time Series Analysis Introduction to Time Series Analysis Decomposition Smoothing: Moving Average Smoothing: EWMA Analysis: Process Capability Process capability Discrete Data: Defect metrics Discrete Data: Yield metrics Process Capability for Continuous Data: Sigma Value Short- and long-term capabilities Cp, Cpk, Pp, Ppk capability indices Analysis: Measurement System Analysis What is Measurement System Analysis? What defines a good measurement system? Gage R&R Studies Attribute / Discrete Gage R&R Continuous Gage R&R Regression Analysis: Simple Correlation Correlation Coefficient Simple linear regression Checking the fit of the Regression Model Leverage and influence analysis Correlation and regression pitfalls Regression Analysis: Multiple Regression Analysis Introduction to Multiple Regression Multicollinearity Multiple Regression vs. Simple Linear Regression Regression Analysis: Multiple Regression Analysis with Discrete Xs Introduction Creating indicator variables Method 1: Going straight to the intercepts Method 2: Testing for differences in intercepts Logistic Regression: Logistic Regression Introduction to Logistic Regression Logistic Regression - Adding a Discrete X Design of Experiments: Introduction Design of Experiment OFAT experimentation Full factorial design Fractional factorial design DOE road map, hints, and suggestions Design of Experiments: Full Factorial Designs Creating 2k Full Factorial designs in Minitab Randomization Replicates and repetitions Analysis of results: Factorial plots Analysis of results: Factorial design Analysis of results: Fits and Residuals Analysis of results: Response Optimizer Analysis of results: Review Design of Experiments: Pragmatic Approaches Designs with no replication Fractional factorial designs Screening Design of Experiment Case Study Repair Time Blocking Closing: Organizational Change Management Organizational change management Assuring project sponsorship Emphasizing shared need for change Mobilizing stakeholder commitment Closing: Project Management for Lean Six Sigma Introduction to project management Project management for Lean Six Sigma The project baseline plan Work Breakdown Structure (WBS) Resource planning Project budget Project risk Project schedule Project executing Project monitoring and controlling and Closing Closing: Design for Lean Six Sigma Introduction to Design for Lean Six Sigma (DMADV) Introduction to Quality Function Deployment (QFD) Summary and Next Steps IIL's Lean Six Sigma Black Belt Certification Program also prepares you to pass the IASSC Certified Black Belt Exam (optional)

Lean Six Sigma Black Belt Certification Program: In-House Training This course is specifically for people wanting to become Lean Six Sigma Black Belts, who are already Lean Six Sigma practitioners. If advanced statistical analysis is needed to identify root causes and optimal process improvements, (Lean) Six Sigma Green Belts typically ask Black Belts or Master Black Belts to conduct these analyses. This course will change that. Green Belts wanting to advance their statistical abilities will have a considerable amount of hands-on practice in techniques such as Statistical Process Control, MSA, Hypothesis Testing, Correlation and Regression, Design of Experiments, and many others. Participants will also work throughout the course on a real-world improvement project from their own business environment. This provides participants with hands-on learning and provides the organization with an immediate ROI once the project is completed. IIL instructors will provide free project coaching throughout the course. What you Will Learn At the end of this program, you will be able to: Use Minitab for advanced data analysis Develop appropriate sampling strategies Analyze differences between samples using Hypothesis Tests Apply Statistical Process Control to differentiate common cause and special cause variation Explain and apply various process capability metrics Conduct Measurement System Analysis and Gage R&R studies for both discrete and continuous data Conduct and analyze simple and multiple regression analysis Plan, execute, and analyze designed experiments Drive sustainable change efforts through leadership, change management, and stakeholder management Successfully incorporate advanced analysis techniques while moving projects through the DMAIC steps Explain the main concepts of Design for Six Sigma including QFD Introduction: DMAIC Review IIL Black Belt Certification Requirements Review Project Selection Review Define Review Measure Review Analyze Review Improve Review Control Introduction: Minitab Tool Introduction to Minitab Minitab basic statistics and graphs Special features Overview of Minitab menus Introduction: Sampling The Central Limit Theorem Confidence Interval of the mean Sample size for continuous data (mean) Confidence Interval for proportions Sample size for discrete data (proportions) Sampling strategies (review) Appendix: CI and sample size for confidence levels other than 95% Hypothesis Testing: Introduction Why use advanced stat tools? What are hypothesis tests? The seven steps of hypothesis tests P value errors and hypothesis tests Hypothesis Testing: Tests for Averages 1 factor ANOVA and ANOM Main Effect Plots, Interaction Plots, and Multi-Vari Charts 2 factor ANOVA and ANOM Hypothesis Testing: Tests for Standard Deviations Testing for equal variance Testing for normality Choosing the right hypothesis test Hypothesis Testing: Chi Square and Other Hypothesis Test Chi-square test for 1 factor ANOM test for 1 factor Chi-square test for 2 factors Exercise hypothesis tests - shipping Non-parametric tests Analysis: Advanced Control Charts Review of Common Cause and Special Cause Variation Review of the Individuals Control Charts How to calculate Control Limits Four additional tests for Special Causes Control Limits after Process Change Discrete Data Control Charts Control Charts for Discrete Proportion Data Control Charts for Discrete Count Data Control Charts for High Volume Processes with Continuous Data Analysis: Non-Normal Data Test for normal distribution Box-Cox Transformation Box-Cox Transformation for Individuals Control Charts Analysis: Time Series Analysis Introduction to Time Series Analysis Decomposition Smoothing: Moving Average Smoothing: EWMA Analysis: Process Capability Process capability Discrete Data: Defect metrics Discrete Data: Yield metrics Process Capability for Continuous Data: Sigma Value Short- and long-term capabilities Cp, Cpk, Pp, Ppk capability indices Analysis: Measurement System Analysis What is Measurement System Analysis? What defines a good measurement system? Gage R&R Studies Attribute / Discrete Gage R&R Continuous Gage R&R Regression Analysis: Simple Correlation Correlation Coefficient Simple linear regression Checking the fit of the Regression Model Leverage and influence analysis Correlation and regression pitfalls Regression Analysis: Multiple Regression Analysis Introduction to Multiple Regression Multicollinearity Multiple Regression vs. Simple Linear Regression Regression Analysis: Multiple Regression Analysis with Discrete Xs Introduction Creating indicator variables Method 1: Going straight to the intercepts Method 2: Testing for differences in intercepts Logistic Regression: Logistic Regression Introduction to Logistic Regression Logistic Regression - Adding a Discrete X Design of Experiments: Introduction Design of Experiment OFAT experimentation Full factorial design Fractional factorial design DOE road map, hints, and suggestions Design of Experiments: Full Factorial Designs Creating 2k Full Factorial designs in Minitab Randomization Replicates and repetitions Analysis of results: Factorial plots Analysis of results: Factorial design Analysis of results: Fits and Residuals Analysis of results: Response Optimizer Analysis of results: Review Design of Experiments: Pragmatic Approaches Designs with no replication Fractional factorial designs Screening Design of Experiment Case Study Repair Time Blocking Closing: Organizational Change Management Organizational change management Assuring project sponsorship Emphasizing shared need for change Mobilizing stakeholder commitment Closing: Project Management for Lean Six Sigma Introduction to project management Project management for Lean Six Sigma The project baseline plan Work Breakdown Structure (WBS) Resource planning Project budget Project risk Project schedule Project executing Project monitoring and controlling and Closing Closing: Design for Lean Six Sigma Introduction to Design for Lean Six Sigma (DMADV) Introduction to Quality Function Deployment (QFD) Summary and Next Steps IIL's Lean Six Sigma Black Belt Certification Program also prepares you to pass the IASSC Certified Black Belt Exam (optional)

This module focuses on developing leadership confidence through self-discovery, emphasising the importance of understanding one's unique leadership style and personal philosophy. Participants will explore their core identity as leaders and learn strategies to enhance their influence, credibility, and relationships within their organisation. Exploring the link between self-discovery and effective leadership, focusing on developing confidence to lead from within. Testimonial: “Without guidance, personal branding can quickly become an exercise in aspiration and competition; letting the carefully curated public personas of others dictate our own validity and definition of success. Clarity on who we truly are, what matters to us and therefore how we position ourselves in the world takes reflection and time. Rachael’s work in this area has inspired the nearly 100 delegates who have been part of our HR Leadership Academy over the past 8 years, and I have no doubt will continue to resonate with future cohorts.” MD, Nina Metson - Suffolk

Our training programme will provide those involved at any stage of the process for procuring goods and/or services within their organisations with the knowledge and skillset to identify and mitigate the threat posed by the breadth and multi-layered complexity of procurement fraud, corruption and associated financial crime and money laundering.

Our training programme will provide those involved at any stage of the process for procuring goods and/or services within their organisations with the knowledge and skillset to identify and mitigate the threat posed by the breadth and multi-layered complexity of procurement fraud and corruption.

The objective of the ID Liner Permanent Eyeliner fundamental course is to teach you how to achieve this look for your clients. It is the perfect solution for clients who struggle to draw on their own eyeliner or who just want an expertly enhanced look 24/7