Reservoir Engineering Training Courses > Marginal Field Evaluation and Development Decision – Rapid Reservoir Evaluation, AI-Assisted Data Review, Production Forecasting, Well Performance and Screening Economics
Code Date Format Currency Team of 10
Per Person*
Team of 7
Per Person*
Early Bird Fee
Per Person
Normal Fee
Per Person
PE2376 14 - 17 Jun 2027 Kuala Lumpur, Malaysia SGD 5,245 5,489 5,899 6,099
PE2376 14 - 17 Jun 2027 Kuala Lumpur, Malaysia USD 4,299 4,499 4,799 4,999
PE2376 14 - 17 Jun 2027 Muscat, Oman SGD 5,675 5,939 6,399 6,599
PE2376 14 - 17 Jun 2027 Muscat, Oman USD 4,643 4,859 5,199 5,399
PE2377 15 - 18 Nov 2027 Kuala Lumpur, Malaysia SGD 5,245 5,489 5,899 6,099
PE2377 15 - 18 Nov 2027 Kuala Lumpur, Malaysia USD 4,299 4,499 4,799 4,999
PE2377 15 - 18 Nov 2027 Muscat, Oman SGD 5,675 5,939 6,399 6,599
PE2377 15 - 18 Nov 2027 Muscat, Oman USD 4,643 4,859 5,199 5,399

*Fee per person in a team of 7 or 10 participating from the same organisation, registering 6 weeks before the course date
Request for a quote if you have different team sizes, content customisation, alternative dates or course timing requirements
Request for in-person classroom training or online (VILT) training format

Learn in teams and save more! Enjoy group discounts of up to 50% off normal fees for team based learning. Contact us on [email protected] to learn more today!

Code

PE2376

Date

14 - 17 Jun 2027

Format

Kuala Lumpur, Malaysia

Currency

SGD

Team of 10
Per Person*

5,245

Team of 7
Per Person*

5,489

Early Bird Fee
Per Person

5,899

Normal Fee
Per Person

6,099

Code

PE2376

Date

14 - 17 Jun 2027

Format

Kuala Lumpur, Malaysia

Currency

USD

Team of 10
Per Person*

4,299

Team of 7
Per Person*

4,499

Early Bird Fee
Per Person

4,799

Normal Fee
Per Person

4,999

Code

PE2376

Date

14 - 17 Jun 2027

Format

Muscat, Oman

Currency

SGD

Team of 10
Per Person*

5,675

Team of 7
Per Person*

5,939

Early Bird Fee
Per Person

6,399

Normal Fee
Per Person

6,599

Code

PE2376

Date

14 - 17 Jun 2027

Format

Muscat, Oman

Currency

USD

Team of 10
Per Person*

4,643

Team of 7
Per Person*

4,859

Early Bird Fee
Per Person

5,199

Normal Fee
Per Person

5,399

Code

PE2377

Date

15 - 18 Nov 2027

Format

Kuala Lumpur, Malaysia

Currency

SGD

Team of 10
Per Person*

5,245

Team of 7
Per Person*

5,489

Early Bird Fee
Per Person

5,899

Normal Fee
Per Person

6,099

Code

PE2377

Date

15 - 18 Nov 2027

Format

Kuala Lumpur, Malaysia

Currency

USD

Team of 10
Per Person*

4,299

Team of 7
Per Person*

4,499

Early Bird Fee
Per Person

4,799

Normal Fee
Per Person

4,999

Code

PE2377

Date

15 - 18 Nov 2027

Format

Muscat, Oman

Currency

SGD

Team of 10
Per Person*

5,675

Team of 7
Per Person*

5,939

Early Bird Fee
Per Person

6,399

Normal Fee
Per Person

6,599

Code

PE2377

Date

15 - 18 Nov 2027

Format

Muscat, Oman

Currency

USD

Team of 10
Per Person*

4,643

Team of 7
Per Person*

4,859

Early Bird Fee
Per Person

5,199

Normal Fee
Per Person

5,399

*Fee per person in a team of 7 or 10 participating from the same organisation, registering 6 weeks before the course date
Request for a quote if you have different team sizes, content customisation, alternative dates or course timing requirements
Request for in-person classroom training or online (VILT) training format

About this Training Course

Marginal and late-life fields require a different approach from large conventional developments. The objective is not to build the most complicated model, but to identify rapidly the technical and commercial factors that determine whether a field can be developed economically.

This four-day practical course provides an integrated approach to screening discovered resources, marginal fields and brownfield redevelopment opportunities. It combines AI-assisted technical review, rapid reservoir evaluation, independent production-forecast cross-checks, well-performance assessment, development concept selection and screening economics.

The emphasis is on engineering judgement, uncertainty and decision quality. Participants are not expected to build full technical models from scratch during the course. Instructor-prepared datasets, populated models and economic templates are used so that class time is spent interpreting results, challenging assumptions, comparing alternatives and making investment decisions.

The course culminates in one major greenfield/discovered-resource case and a shorter brownfield optimisation case, followed by concise investment-committee recommendations.

By the end of the course, participants will be able to:

  • Rapidly identify the few technical and commercial parameters that determine marginal-field value
  • Use AI tools to review technical documents, extract key facts and assumptions, identify inconsistencies and maintain source traceability
  • Estimate recoverable volumes and establish a defensible low / base / high production range using independent forecasting methods
  • Identify reservoir, well, artificial-lift and surface-facility constraints that control deliverability
  • Translate technical uncertainty into screening economics, breakeven and value-driver sensitivities
  • Prepare and defend a concise Develop / Appraise / Redevelop / Bid / Walk Away recommendation

The course is designed for reservoir, production, petroleum and development engineers; geologists and geophysicists; field development planners; asset engineers; commercial and business-development personnel; and asset / technical managers involved in marginal fields, discovered resources, mature fields, brownfield redevelopment, acquisitions, bid rounds and field-development planning.

  • Intermediate
  • Advanced

The course is designed as a practical decision-making workshop rather than a software training course. No specialist software licences or software packages are included as part of the course.

The trainer will use worked examples, prepared datasets, spreadsheets and practical exercises to demonstrate the evaluation and decision-making process. Where participants have access to relevant software such as MBAL or PROSPER, the trainer can incorporate these tools into the exercises and demonstrations, subject to the software being available and accessible during the course.

The focus remains on understanding, challenging and interpreting the results rather than on learning the software itself. Participants will learn how to assess whether the outputs are technically credible, understand the underlying assumptions and translate the results into sound development and investment decisions. Where specialist software is not available, equivalent exercises can be conducted using simplified spreadsheet-based models and instructor-prepared datasets.

Unlock the potential of your workforce with customized in-house training programs designed specifically for the energy sector. Our tailored, in-house courses not only enhance employee skills and engagement but also offer significant cost savings by eliminating travel expenses. Invest in your team’s success and achieve specific outcomes aligned with your organization’s goals through our expert training solutions. Request for further information regarding our on-site or in-house training opportunities.

In our ongoing commitment to sustainability and environmental responsibility, we will no longer providing hard copy training materials. Instead, all training content and resources will be delivered in digital format. Inspired by the oil and energy industry’s best practices, we are leveraging on digital technologies to reduce waste, lower our carbon emissions, ensuring our training content is always up-to-date and accessible. Click here to learn more.

To further optimise your learning experience from our courses, we also offer individualised coaching support. 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 can be delivered virtually through video conference or face to face by one of our senior subject matter experts. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Learn more about our post training coaching services here.
Q1. What is marginal field evaluation?

Marginal field evaluation determines whether a discovered or producing field can create enough technical and commercial value to justify further investment.

The process reviews recoverable volumes, production potential, well performance, facilities, CAPEX, OPEX and field life. It also considers price and other commercial assumptions.

Marginal field evaluation and development focuses on the factors that have the greatest effect on value. It also helps teams decide whether more technical work is worth the cost.

Q2. What makes an oil or gas field economically marginal?

An oil or gas field may become economically marginal when expected production cannot justify the required investment and operating costs.

Several factors can reduce value. These include small recoverable volumes, declining production, high water cut, well limits and infrastructure constraints. High CAPEX, OPEX or low production rates can also affect the result.

Teams should assess technical and commercial marginality separately. A field may contain recoverable hydrocarbons but still fail to create enough economic value.

Q3. How are production forecasts developed for marginal fields?

Engineers can use several methods to forecast production from marginal fields. These include decline-curve analysis, material balance and fractional-flow forecasting.

Decline curves use production history to estimate future performance. Material balance considers pressure behaviour, reservoir support and connected volume.

Teams can compare the different forecasts to identify major differences. They should also check the results against reservoir behaviour, well limits and operating history.

This approach helps establish a practical low, base and high production range.

Q4. What is the role of AI in reservoir and field evaluation?

AI can speed up technical reviews during marginal field evaluation.
It can help teams review reports, extract key facts and assumptions, identify inconsistencies and organise information. AI can also support production-history reviews and alternative scenario development.

However, engineers should verify important AI outputs. They should compare them with original documents, calculations and field behaviour.

AI supports faster analysis, but engineering judgement remains essential.

Q5. How does well performance affect marginal field economics?

Well performance directly affects production and project value.

Reservoir inflow, productivity index, skin and vertical lift performance all influence deliverability. Tubing size, PVT, wellhead pressure and separator pressure can also affect production.
Teams may improve performance through gas lift, ESPs, choke optimisation or backpressure reduction. They should then compare the extra production with the cost of the intervention.

Even small production improvements can affect the economic case for a marginal field.

Q6. What is the difference between greenfield and brownfield field evaluation?

Greenfield evaluation focuses on an undeveloped or discovered resource. The main question is whether the field should move toward development.

Teams assess recoverable volumes, production potential, development concepts, costs and project value.

Brownfield evaluation focuses on an existing producing asset. Teams review remaining reserves, declining production, water cut, pressure support and existing facilities.

They may also assess options such as gas-lift optimisation, ESP installation, sidetracks or increased liquid handling.

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