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New Approach in Horizontal Wells Drilling: Cost Efficient Opportunities with AI


Disciplines: Data Science and Engineering Analytics | Drilling | Management | Reservoir

Course Description

  • Reservoir characteristics for horizontal and multilateral well applications
  • Evaluation of Well Performance
  • Geological Well Placement and Reservoir Geology
  • Well trajectory
  • Wellbore Stability of Horizontal Wells
  • Stress Field Effect on Drilling, Completion, Production, And Stimulation
  • Application of LWD measurements for geosteering
  • Geosteering Methods
  • Completions for horizontal well applications
  • Horizontal Well Stimulation - Hydraulic Fracturing
  • Horizontal Well Stimulation - Acidizing

Learning Level

Intermediate

Course Length

3 Days

Why Attend

The course will present how horizontal well drilling will help to achieve cost efficiency, higher production with better well control, and maintained integrity.

Who Attends

Well Planning, Drilling, Completion, Reservoir, and Production Engineers

Cancellation Policy

All cancellations must be received no later than 14 days prior to the course start date. Cancellations made after the 14-day window will not be refunded. Refunds will not be given due to no show situations.

Training sessions attached to SPE conferences and workshops follow the cancellation policies stated on the event information page. Please check that page for specific cancellation information.

SPE reserves the right to cancel or re-schedule courses at will. Notification of changes will be made as quickly as possible; please keep this in mind when arranging travel, as SPE is not responsible for any fees charged for cancelling or changing travel arrangements.

We reserve the right to substitute course instructors as necessary.

Instructor

None Dr. Ashwin Venkatraman is the Founder and CEO of Resermine, a niche award-winning oil and gas technology company (MOST Promising at OTC 2018). He is the recipient of the inaugural SPE International Technical Award in Data Science and Engineering Analytics at SPE ATCE 2021 held in Dubai. The award recognized his contributions to bringing hybrid workflows that combine AI/ML with traditional approaches to accelerate subsurface decision making.

Resermine’s products have been used to optimize mature field injection operations and accelerate field development planning for fields in USA, Germany, Oman, UAE, Egypt, Mexico, India and Malaysia. Resermine is based in USA (HQ) with technology delivery centers in Kuala Lumpur (ARMC - Advanced Modeling Center), Dubai (UAE) and Muscat (Oman) to support projects in different regions.

Dr. Venkatraman has published over 30 manuscripts and is on the advisory board of SPE’s Data Science and Engineering Analytics Committee. He previously worked with Shell for over 12 years at all their technology centers (India, Netherlands and Houston).

Dr. Venkatraman served as faculty in the Petroleum Engineering Department of University of Oklahoma (2019-2020) and held research appointments in Princeton University as well as at Institute of Computational Engineering & Sciences (ICES) at the University of Texas before founding the Resermine. Dr. Venkatraman holds BSc and MSc in Chemical Engineering from IIT Bombay (India) and earned his PhD from University of Texas at Austin in Petroleum Engineering.

Other courses by this instructor

Application of Digital Hybrid Tools That Combine Analytics, Machine Learning & Reduced Physics Models to Increase Oil Recovery in Mature Conventional Fields
Ashwin Venkatraman

Conventional mature fields spread across the world – USA, Russia, Canada, Middle East, North Africa, South America and Southeast Asia, contribute to as much as 70% of all world’s oil. The cheapest and the quickest way to add oil is to increase from exist…

(Read More)

Disciplines: Data Science and Engineering Analytics | Reservoir

Drilling Process Improvement using Advanced Analytics and Machine Learning Algorithms
Ashwin Venkatraman

Advanced analytics and ML algorithms are transforming subsurface decision making in the oil and gas industry. The democratization of analytical tools is seeing historical data being analyzed more routinely than was done earlier. This is helping accelerat…

(Read More)

Disciplines: Data Science and Engineering Analytics | Drilling | Management

Introduction to Machine Learning for Oil and Gas Professionals
Ashwin Venkatraman

Machine learning (ML) algorithms are transforming workflows in the oil and gas industry. The democratization and access to advanced computational tools is helping organizations exponentially accelerate their decision making using these powerful tools. Th…

(Read More)

Disciplines: Completions | Data Science and Engineering Analytics | Drilling | Management | Production and Operations | Projects, Facilities, and Construction | Reservoir

Reservoir Engineering Applications of Advanced Data Analytics and Machine Learning Algorithms
Ashwin Venkatraman

Data driven modeling is becoming a key differentiation to unlock higher recoveries from existing fields as well as identify new opportunities. The availability of data and democratization of these advanced algorithms is changing the landscape of subsurfa…

(Read More)

Disciplines: Data Science and Engineering Analytics | Drilling | Production and Operations | Reservoir

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