The Data Science and Engineering Analytics (DSEA) Technical Section is available for all members focused on Digitalization, creating value from data. Given the size of prize, where even a small percentage improvement in efficiency or production can yield big bottom-line impact, the interest and relevance of DSEA applies across all SPE disciplines and beyond.

As Petroleum industry rapidly evolves towards better and faster innovative end-to-end processes from Exploration, Appraisal, Development, Production to Operations, including Abandonment with heightened global focus on safety, sustainability, resources, and environmental footprint – the role of DSEA is increasingly recognized by all disciplines and upstream business sectors, beyond typical IT and data organizations.

Innovative technologies and software solutions are more commonly available, enabling DSEA arena to covert big volumes of data to “smart” data for timely decision making aimed for value generation. Technology maturation, architectural agility, multidisciplinary integrated processes bundled with business focus on right strategic problems, will drive data sciences to accelerate digitalization and aspired business transformation.

The current and the future growing opportunities using AI, automation vs. manual, autonomous processes, predictive analytics for mitigating risks and failures, faster problem solving, targeted simplification – DSEA arena has tremendous potential for unlocking value across the industry with stronger collaboration with all technical disciplines driving the aspired Digital Energy journey.

Join us – Let's focus on top priorities, solve pressing challenges, adopt innovative technical solutions, and together make a difference for world’s growing energy needs.

Our Goals

The DSEA technical section will serve as knowledge sharing and learning forum for all SPE members, from varied disciplines, interested in value creation from data and information leveraging Computing, Data, and Predictive Analytics sciences.  The SPE DSEATS is intended to accelerate and enhance the digital asset life cycle management, given the current business dynamics and enable the future strategic energy transformation aspirations.

The DSEA Technical Section will drive activities focusing on the already established key arenas (refer: SPE Petrowiki taxonomy), namely:

Data Science & Engineering Analytics
I. Information Management and Systems
- Knowledge Management
- Data Integration
- Data Security
- Data Mining
- Metadata Management
- Artificial Intelligence
- Neural Networks
II. Research & Development and Emerging Technology Program
- New Technology Deployment
- New Technology Valuation
- New Technology Funding

Any other Data Science and Analytics related or relevant areas (e.g., Data Quality, Data Standards, Machine Learning, etc.) that are implicitly included within these categories, maybe addressed in the Technical Section. Additionally, any necessary updates will be considered with the DSEA Board team, and with inputs from the DSEA Advisory Board and SPE’s other disciples’ Board teams.

These foundational DSEA technical arenas will be addressed by the DSEA Board team, and with cross collaboration with SPE’s technical disciplines covering end-to-end value chain, predominantly for the Upstream business but also overarchingly across the Energy sector and outside the industry: Reservoir Engineering, Geology/Geophysics, Wells, Geothermal, Sustainability, Zero Carbon Footprint, Digital Twin, etc. supporting Digital and dynamic Energy Transformation aspirations.

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For more information on sanctions, visit our website here.

Message from the Chairperson

Thank you SPE for the opportunity to serve as SPE’s Data Science & Engineering Analytics (DSEA) Technical Section (TS) Chair.  I deeply appreciate this honor. I am so delighted to welcome our new DSEA TS board and subcommittee members.  This group includes a diverse array of well-known SPE and industry leaders, recognized experts, and some very talented young professionals. Each brings to the table their own unique set of experiences, multidisciplinary knowhow, and global industry insights. It is personally gratifying to have more women colleagues stepping up to serve and contribute on this board.  Additionally, I want to take this opportunity to thank the past leaders who have devoted time and effort to DETS and PD2A and built a core digital community that we will further grow to meet the industry’s current--and future--demands.

We look forward to working with all SPE technical sections and disciplines using a hub-and-spoke model and having liaisons coordinate activities with the regional chapters.

As digitalization momentum accelerates across our industry (including the evolution of the next-gen digital oil field, more end-to-end process data integration, automation and technology innovations, simpler cross-discipline processes, and increased sustainability focus) the timing is just right for launching our new DSEA TS. In the coming months, we aim to break any regional discipline or organizational silos and increase more collaborative efforts, not only within SPE, but also with our academic and industry partners.

Please join our technical section and let’s together make a difference for the increasing energy needs of the world. You can share your ideas for DSEA TS program at dsea.spe@gmail.com or contact any of the board members (https://connect.spe.org/dsea/aboutus/sectionofficers).

Looking forward to a very productive, inclusive, and an impactful term.


2022 ATCE DSEA Technical Section Dinner

The Data Science Engineering and Analytics Technical Section (DSEATS) would like to invite you to a networking dinner at 2022 SPE ATCE. The dinner is open to all SPE members.

The 2022 SPE ATCE will be held in Houston, Texas and the DSEATS dinner will be held alongside on Sunday, 2 October from 7:30 pm to 9:00 pm CDT.

This year’s DSEATS dinner is entitled:

"Artificial Intelligence & Machine Learning: A Paradigm Shift in Science and Engineering" listed under ATCE Special Event Tickets.

The science of Artificial Intelligence and Machine Learning is a complete paradigm shift when it is compared with traditional approaches to modeling physics and engineering problem-solving. Paradigm shifts in science have examples of Copernican Paradigm in the 16th century, Newtonian Paradigm in the 19th century, and Einsteinian Paradigm in the 20th century. Artificial Intelligence and Machine Learning in the 21st-century version of science and technology. The talk will address the advancements and breakthroughs in Artificial Intelligence and Machine Learning domain which led to a paradigm shift in the way the industry is approaching and solving challenging engineering problems. These technologies, together with the availability of large volumes of data and significant computational capabilities have rapidly changed the landscape for every aspect of the oil and gas industry. The talk will also address the impact of this shift on the new generation of engineers and scientists and their new normal operating environments.


This is a ticketed event and seats are limited! Register to reserve your seat today! REGISTER HERE

With gratitude to our generous dinner sponsor: i2k Connect


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