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2nd Edition: Decision Based Integrated Reservoir Modeling

Monday, 1 February Thursday, 4 February 2021, 12:30 a.m.–4:30 p.m.  |  Virtual Workshop via Zoom (Dubai, UAE time)

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What to Expect from the AAPG Virtual Experience:

Due to the ongoing travel restrictions and differing guidelines from companies and organizations, the AAPG Decision Based Integrated Reservoir Modeling GTW will now be taking place virtually from 1 – 4 February 2021 and then on-demand anytime, from anywhere, and from any device for the next 2 months. The workshop will provide the best opportunity to safely connect with industry colleagues and peers while travel restrictions, social distancing, and health concerns persist. The new dynamic all-digital platform makes it simple for you to access all the great science, networking, and technology to help you stay on the cutting edge of petroleum geoscience. Our businesses and industry are experiencing difficult times, but overcoming obstacles is what explorers do – so let’s do it together.

  • Benefits of our virtual events:
  • Easily view the live presentations, ask questions and chat with other attendees
  • Easily access the technical program and details of each presentation
  • View the profiles of each presenter
  • Participate in breakout discussion sessions
  • Networking with other attendees and schedule one on one meetings
  • Access to all the presentations for up to 2 months after the workshop
  • Access to a dedicated sponsorship page
  • Digital delegate bag and certificate of attendance

Following the successful 1st edition of the Decision based Integrated Reservoir Modeling GTW, the 2nd edition will focus on the latest technology and cost-effective approaches for building accurate and predictive 3D reservoir models for the oil and gas industry. Integrated reservoir modeling plays a pivotal role in the E&P workflow, where 3D quantitative geocellular models provide essential input for major oil and gas field development decisions. Static and dynamic data integration, new developments in 3D reservoir modeling techniques, and uncertainty quantification associated with reserves estimation, will be just a few topics, among others, to be tackled and discussed during the workshop.

Benefits of Attending

Just like many industries, the oil and gas industry is embracing machine learning (ML) and artificial intelligence (AI) technology that is expected to fundamentally transform the way we quantitatively characterize and model subsurface reservoirs. Fascinating geoscience-related ML and AI technological innovations, including challenges and opportunities, will be presented and debated. Will ML and AI help us achieve enhanced accuracy and cost-effectiveness when it comes to reservoir properties prediction and 3D reservoir modeling in complex reservoirs with large multi-disciplinary data?

The workshop will also include case studies presentations underscoring how advanced reservoir modeling technology and rigorous multi-disciplinary data integration facilitated the successful execution of complex field increments. Discussions are also expected on the most common pitfalls to avoid.

An optional one day field trip is planned in connection with the workshop.

Who Should Attend?

Geologists, geophysicists, reservoir modelers, petrophysicists, reservoir simulation engineers, reservoir management engineers, project managers, data scientists, and team leaders working in exploration, field development, and technology innovation.

 

Note: All program times are GST (Gulf Standard Time)

Details of the digital platform to be used will be shared with you shortly. Please check back for more information


Monday 1 February
12.30-12.40 Workshop Chair's Welcome and Introduction
12.40-12.55 Inaugural Keynote: Aus Al Tawil, Saudi Aramco
Session 1: DBM Current Best Practices – What can be Enhanced?
Session Chairs: Nicolas Leseur, Baker Hughes and Nazih Najjar, Saudi Aramco
12.55-13.25 Session Keynote: How a Tight Combination of Geostatistics and Machine Learning can Bring Significant Practical Advantages to Reservoir Modeling
Colin Daly, Schlumberger
13.25-13.50 Merging Machine Learning and Reservoir Physics to Make Better Decisions
Jon Sætrom, Resoptima
13.50-14.00 Coffee Break
14.00-14.25 Big Data in the Oil and Gas Industry: Current Practical Challenges and Opportunities
Mustafa Al Ibrahim, Saudi Aramco
14.25-14.50 Integration of Rock Physic Models and 4D Seismic Data in the Reservoir Model, Challenges and Examples from Edvard Grieg
Odd Kolbjørnsen, Lundin Energy
14.50-15.00 Coffee Break
15.00-16.00 Break Out Session
Tuesday 2 February
Session 2: Multi-Disciplinary Data Integration – New Approaches
Session Chairs: Guillaume Caumon, Nancy School of Geology and Mokhles Mezghani, Saudi Aramco
12.30-13.00 Session Keynote: The New Frontier: Predictive and Multi-Scales Reservoir Models from Process-Based Techniques
Gérard Massonnat, Total
13.00-13.25 Improved Facies Model by Using Novel Approach of Forward Stratigraphic Modeling - a Case Study
Muhammad Kamran Qureshi, Schlumberger
13.25-13.50 Non-Linear Least Square Optimization of Stratigraphic Carbonate Models
Hussain Alqattan, Saudi Aramco
13.50-14.00 Coffee Break
14.00-15.00 Break Out Session
Wednesday 3 February
Session 3: ML and AI – Practical Applications, Recent Innovations and Automation
Session Chairs: Behzad Alaei, Earth Science Analytics and Wael Abdallah, Schlumberger
12.30-13.00 Session Keynote: Artificial Intelligence-Based Earth Models Deliver Breakthroughs from Seismic Multiple Suppression to Seeing Ahead of the Drill Bit
Barry Zhang, Quantico Energy Solutions
13.00-13.25 Physics-Based Vs. Data-Driven. A False Dilemma?
Nicolas Leseur, Baker Hughes
13.25-13.35 Coffee Break
13.35-14.00 AI-Assisted Reservoir Characterization on a Cloud-Native Data Platform
Eirik Larsen, Earth Science Analytics
14.00-14.25 Injecting Physics, Domain Knowledge, and Geology in Data-Driven Approaches for the Interpretation of Subsurface Measurements Data
Smaine Zeroug, Schlumberger
14.25-14.35 Coffee Break
14.35-15.35 Break Out Session
Thursday 4 February
Session 4: Case Studies – Successes and Pitfalls
Session Chairs: Vasily Demyanov, Heriot-Watt University & Colin Daly, Schlumberger
12.30-13.00 Session Keynote: Predictive Intelligence Drives the Future: The Unified Field Development Platform
Tareq Zahrani, Saudi Aramco
13.00-13.25 The Challenge of Modelling Horizontal Wells in a Thin Pay Carbonate Reservoir
Sajeda Barni, Tatweer Petroleum
13.25-13.50 The Present is the Key to the Past, from Modern to Ancient, and from Rock Record to Subsurface Modeling: The Journey of Geological Reservoir Modeling
Mohammed Masrahy, Saudi Aramco
13.50-14.00 Coffee Break
14.00-15.00 Break Out Session
15.00-15.10 Workshop Wrap Up & Adjournment
 
 
Dubai, United Arab Emirates
4 February 2021

Field Trip Organizer: Dhahran Geoscience Society
Field Trip Leader: Mohammed Masrahy
Date: 4 February 2021
Time: 15.30 – 17.00 (GST/GMT+4)
Fee: Free of Charge

Field Trip Description

Over the past two decades, there have been major developments in the efforts to quantify the architectural elements, geometry, and dimensions of depositional bodies from analogues to provide quantitative input to geological models.

Fig 1Analogues, especially ancient outcrops and modern analogues have played a crucial role in improving the understanding of subsurface reservoir architectural elements. They provide important information on subsurface reservoir geobodies size, geometry, and potential connectivity, which all contribute to better reservoir characterization. This is especially vital for highly heterogeneous siliciclastic or carbonate reservoirs that require the integration and detailed analysis of reservoir petrophysical properties, facies, diagenesis, geometry, depositional environments and lateral and vertical variability.

Robust subsurface reservoir models heavily rely on the available geological input data. Outcrop and modern analogue data from comparable systems provide additional input to geological models of the subsurface. This virtual field trip will provide valuable insights into the nature of this complexity.

Aims and Objectives

Fig 2The virtual field trip comprises a field study of a range of continental clastic modern systems and related sedimentary facies, each of which possesses attributes that are comparable in part to the subsurface deposits.

Virtual field trip attendees will gain knowledge about key competencies related to field geology, such as understanding the geomorphology of continental systems, seeing examples that explain sedimentary structures, textures, and facies, identifying depositional environments, and linking sedimentological observations to subsurface reservoir modeling.

One specific aim of this virtual field trip is to emphasize that integrated reservoir characterization and modeling processes take into account actual depositional trends and distribution of the sedimentary bodies (sediment-body geometry and heterogeneity), through the understanding of modern analogues settings.

Intended Learning Outcomes

Fig 3This virtual field trip will provide insights and offer discussions of the following aspects:

  1. An introduction to techniques and criteria for the recognition of continental (fluvial and aeolian systems), and related sedimentary facies in modern system and discussions of the application of these techniques to the study of subsurface sedimentology and geological modeling.
  2. 1D, 2D and 3D facies architecture with particular consideration of the geometry and scale of key stratal bodies that have relevance for understanding subsurface hydrocarbon reservoirs.
  3. The nature of autocyclic (intrinsic) interactions between competing sedimentary processes and consideration of the implications of these in terms of reservoir quality.
  4. The nature of allocyclic (external) controls on sedimentary processes and consideration of the effects of temporal and spatial changes in these controls on the preserved successions.
  5. The significance of accurately determining the preserved geometry of reservoir successions and performing correlations at the interwell scale.
  6. 3D prediction of the distribution of net versus non-net reservoir.
Show more
 
$495
Expires on
21 February, 3020
Member Fee
$595
Expires on
21 February, 3020
Non-Member Fee
$200
Expires on
21 February, 3020
Faculty Member Fee
$250
Expires on
21 February, 3020
Faculty Non-Member Fee
$100
Expires on
21 February, 3020
Student Member Fee
$150
Expires on
21 February, 3020
Student Non-Member Fee
 

Note: All prices are in USD

  • Fees include access to all live presentations and on demand presentations for up to two months after the event
  • To register with member fees, you must be an active member of AAPG
Corporate Registration

For corporate registrations please contact , Marketing & Events Officer.

Corporate Group Pricing

  • 10+ pax > $4,210
  • 20+ pax > $7,920
  • 30+ pax please get in touch with for pricing.
Nazih F. Najjar Nazih Najjar Chair Sr Geological Consultant, Saudi Aramco, Saudi Arabia
Nicolas Leseur Nicolas Leseur Committee Member Baker Hughes
Behzad Alaei Behzad Alaei Committee Member Earth Science Analytics
Aymen Haouesse Aymen Haouesse Committee Member Emerson
Vasily Demyanov Vasily Demyanov Committee Member Heriot-Watt University
Guillaume Caumon Guillaume Caumon Committee Member Nancy School of Geology, France
Mokhles Mezghani Mokhles Mezghani Committee Member Saudi Aramco
Colin Daly Colin Daly Committee Member Schlumberger, England (U.K.)
Wael Abdallah Wael Abdallah Committee Member Schlumberger
Cora Navarro Marketing & Events Officer, Middle East
Katie Steibelt Events Manager, Middle East
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