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AI for Upstream Oil & Gas: Reservoir Modelling and Production Forecasting

AI-Driven Reservoir Modelling and Production Forecasting for Upstream Assets

AI for Upstream Oil & Gas: Reservoir Modelling and Production Forecasting

Course Schedule

Classroom

Online

Training Introduction

The AI for Upstream Oil & Gas: Reservoir Modelling and Production Forecasting Training Course explores how artificial intelligence and machine learning transform subsurface engineering workflows. Reservoir models and production forecasts guide critical decisions throughout the life of an oil and gas asset, directly influencing development plans, well placement, production targets, reserves estimates, and investment priorities. However, incomplete subsurface information, reservoir behavior uncertainties, and fluctuating operating conditions make production forecasting a continuous engineering challenge rather than a static calculation. 

This AI for Upstream Oil & Gas Training Course examines how advanced analytics complement established reservoir engineering and production forecasting methods, helping upstream teams analyze vast volumes of geological, petrophysical, well, and production data to reveal patterns, generate alternative forecasts, and evaluate development scenarios faster.

Key focus areas of this course

  • Data Preparation & Feature Selection: Cleaning, structuring, and selecting relevant static and dynamic subsurface variables.
  • Conventional vs. AI Forecasting Methods: Evaluating traditional decline curve analysis alongside machine learning models.
  • Proxy Reservoir Modelling: Developing predictive proxy models for rapid scenario evaluation and asset planning.
  • Uncertainty Assessment & Physics Constraints: Accounting for subsurface uncertainty while embedding physical reservoir principles.
  • Overfitting & Data Leakage Prevention: Recognizing common analytical pitfalls that lead to misleading forecast accuracy.
  • Decision Support & Workflow Integration: Communicating forecast ranges, assumptions, and implementation roadmaps to technical leadership.

What are the goals?

This comprehensive AI for Upstream Oil & Gas Training Course equips participants with the practical skill set needed to integrate artificial intelligence into modern reservoir management and field development workflows. By blending analytics with fundamental petroleum engineering principles, participants gain hands-on expertise in building, evaluating, and deploying reliable predictive models.

By the end of this Reservoir Modelling Training Course, participants will be able to:

  • Identify high-value upstream applications where artificial intelligence supports reservoir modelling and forecasting workflows.
  • Prepare, clean, and assess complex subsurface, well, and production data for analytical workflows.
  • Select and engineer relevant geological, petrophysical, reservoir, and operational variables.
  • Compare conventional forecasting approaches with advanced machine learning-based techniques.
  • Develop and evaluate robust predictive models for well-level and field-wide production forecasting.
  • Recognize and mitigate data leakage, overfitting, and other primary sources of misleading analytical results.
  • Assess subsurface uncertainty and effectively communicate probabilistic forecast ranges to key decision-makers.
  • Combine machine learning outputs with established reservoir engineering knowledge and physical constraints.
  • Define a structured, phased implementation plan for an upstream artificial intelligence use case.

Who is this Training Course for?

This specialized Reservoir Modelling Training Course is designed for technical professionals and operational leaders seeking to harness artificial intelligence to improve asset performance, optimize recovery, and streamline forecasting precision. It caters to multidisciplinary teams across the upstream sector who interact with subsurface data and field development decisions.

This AI for Upstream Oil & Gas Training Course will greatly benefit:

  • Reservoir and petroleum engineers seeking to enhance traditional analytical workflows.
  • Production and well performance engineers aiming to optimize production forecasts and surveillance.
  • Geoscientists and petrophysicists working with static reservoir characterization and dynamic data integration.
  • Field development and asset planning professionals responsible for long-term capital allocation.
  • Upstream data analysts and data scientists focusing on petroleum analytics solutions.
  • Digital transformation teams in oil and gas driving tech adoption across subsurface assets.
  • Technical managers responsible for production forecasts, reserves evaluation, and engineering compliance.

How will this Training Course be Presented?

This AI for Upstream Oil & Gas Training Course is delivered through an interactive, applied learning format that balances technical theory with practical, hands-on engineering execution. Participants engage with real-world technical presentations, illustrative upstream case studies, structured group discussions, and guided data exercise sessions. Throughout the modules, delegates work directly with representative reservoir and production datasets to prepare inputs, compare alternative forecasting techniques, evaluate model performance metrics, and build actionable engineering recommendations.

To ensure seamless integration across multidisciplinary asset teams, no advanced programming experience is required to follow and apply the core concepts of this Reservoir Modelling Training Course. The emphasis remains firmly on engineering interpretation, physical validation, comparing machine learning outputs against conventional physics-based benchmarks, and clearly articulating forecast assumptions and operational limitations to asset leadership.

The Course Content

Day 1: Upstream Data and AI Applications

  • Reservoir modelling and production forecasting decisions across the asset lifecycle
  • Conventional reservoir engineering and forecasting approaches
  • AI and machine learning applications in upstream operations
  • Sources of geological, petrophysical, well and production data
  • Data quality, missing values and inconsistent reporting
  • Aligning production data with well events and operating conditions
  • Defining the forecast target, time horizon and decision context
  • Selecting an upstream use case for analysis

Day 2: Preparing Data and Characterising Reservoir Behaviour

  • Integrating static reservoir and dynamic production data
  • Selecting features related to rock, fluid and well performance
  • Analysing pressure, rates, water cut and gas–oil ratio trends
  • Accounting for shut-ins, workovers and artificial lift changes
  • Identifying outliers and separating errors from significant events
  • Segmenting wells and reservoirs with comparable characteristics
  • Exploring relationships between inputs and production outcomes
  • Documenting data assumptions and limitations

Day 3: AI Methods for Reservoir Modelling

  • Using AI to support reservoir characterisation
  • Predicting reservoir properties from available measurements
  • Identifying patterns across wells and geological zones
  • Developing proxy models for rapid scenario evaluation
  • Comparing AI predictions with geological and engineering understanding
  • Incorporating physical constraints into model evaluation
  • Validating results where subsurface observations are limited
  • Interpreting model outputs for field development decisions

Day 4: AI-Based Production Forecasting

  • Establishing decline curve and engineering forecast benchmarks
  • Preparing time-series data for well and field forecasts
  • Comparing machine learning approaches for production prediction
  • Defining training, validation and test periods
  • Preventing data leakage and unrealistic forecast accuracy
  • Forecasting under changing operating conditions
  • Evaluating errors across wells, time horizons and production levels
  • Comparing AI forecasts with conventional methods

Day 5: Uncertainty, Deployment and Decision Support

  • Identifying geological, operational and model uncertainty
  • Developing forecast ranges and alternative production scenarios
  • Stress-testing forecasts against changing assumptions
  • Explaining model results to engineering and asset teams
  • Integrating forecasts into reservoir surveillance and planning
  • Monitoring performance and updating models as new data arrives
  • Presenting an AI-supported asset forecasting case
  • Developing a phased implementation roadmap for an upstream team

Providers and Associations

Anderson

Anderson

Aztech Training

Aztech Training

COPEX

COPEX

Frequently Asked Questions

Quick answers to common questions about this training course.

Absolutely. Coventry Academy provides customised in-house training solutions for organisations seeking a tailored learning experience. The AI for Upstream Oil & Gas: Reservoir Modelling and Production Forecasting training course can be adapted to reflect your organisation's objectives, industry requirements, operational challenges, and strategic priorities. Delivered exclusively for your team, customised training enables organisations to maximise relevance, encourage collaboration, and achieve targeted development outcomes. Our team will be pleased to discuss your requirements and develop a solution that aligns with your goals.

Absolutely! If you’re attending one of our courses at an international venue, we can help
with hotel reservations and entry visas. Just reach out to our Customer Service team:

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No prior experience is required to attend the AI for Upstream Oil & Gas: Reservoir Modelling and Production Forecasting training course. The course is designed to accommodate participants from diverse professional backgrounds and varying levels of experience. While some familiarity with the subject matter may help participants gain additional value from certain discussions and activities, the course content is structured to ensure that both newcomers and experienced professionals can fully engage with the learning experience and benefit from the training.

Our dedicated support team is available to assist you with any questions regarding the AI for Upstream Oil & Gas: Reservoir Modelling and Production Forecasting training course, including course content, scheduling, registration, corporate bookings, and customised training solutions. We are committed to providing prompt and professional assistance throughout your learning journey.

📞 Phone: +971 58 840 7925

📧 Email: info@coventryacademy.com

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Registering for a course is super easy! Here’s how you can do it:

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The AI for Upstream Oil & Gas: Reservoir Modelling and Production Forecasting training course is designed to be practical, engaging, and highly interactive. Participants benefit from a dynamic learning environment that combines expert-led presentations, facilitated discussions, case studies, practical exercises, and collaborative learning activities. The focus is on developing knowledge that can be applied immediately within the workplace, ensuring participants gain both valuable insights and practical skills that support improved professional performance.

Your course fees cover:

  • For classroom courses: printed materials, lunch, and refreshments.
  • For online courses: all materials sent to you by email.
  • A certificate of completion or attendance.

You’ll need to make payment before the course starts. Here are your options:

  • Bank draft
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Heads up: If we don’t receive payment before the course begins, we may have to deny
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We delivers training courses in carefully selected professional venues that provide a comfortable and productive learning environment. Classroom-based courses are typically hosted in premium international venues with modern facilities and dedicated training spaces designed to support effective learning. Participants also benefit from a professional setting that encourages networking, collaboration, and knowledge sharing with peers from diverse industries and backgrounds.

The AI for Upstream Oil & Gas: Reservoir Modelling and Production Forecasting training course is designed for professionals seeking to strengthen their knowledge, enhance their capabilities, and achieve greater impact within their organisations. It is suitable for managers, supervisors, team leaders, technical specialists, consultants, and professionals at all career stages who wish to expand their expertise and stay current with industry developments. Whether you are looking to advance your career, improve workplace performance, or prepare for new responsibilities, this course provides valuable knowledge and practical insights to support your professional growth.

Our courses are led by top-notch international instructors. They’re not just academically qualified—they’ve also got years of real-world experience. They bring practical insights and deep knowledge to every session, making your learning experience truly valuable!

Yes. Participants who successfully complete the AI for Upstream Oil & Gas: Reservoir Modelling and Production Forecasting training course will receive a Coventry Academy Certificate of Completion, recognising their commitment to professional development and continuous learning. This certificate serves as formal evidence of participation and achievement and can support career progression, professional credibility, and ongoing development objectives. Where applicable, details regarding professional development credits or accreditation will be provided within the course information.

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