Aria Abubakar
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| Membership | Honorary Member |
|---|---|
| PhD | Technical Sciences |
| PhD university | Delft University of Technology |
Aria Abubakar was born in Bandung, Indonesia. He received an MSc degree in Electrical Engineering in 1997 and a PhD in Technical Sciences in 2000, both from the Delft University of Technology, The Netherlands. He joined Schlumberger-Doll Research in Ridgefield, CT, USA in 2003, where he remained for 10 years, ending his tenure as a Scientific Advisor and the Manager of the Multi-Physics Modeling and Inversion Program. From 2013 until mid-2017, he was the Interpretation Engineering Manager at Schlumberger Houston Formation Evaluation in Sugar Land, TX. From mid-2017 until mid-2020, he was Data Analytics Program Manager for Software Technology and then Head of Data Science for the Schlumberger Exploration and Field Development Platform based in Houston, TX.
Aria is currently the Head of Data Science for the Digital Subsurface Solutions. His main responsibility is to oversee and coordinate the utilization of artificial intelligence, machine-learning, and data-analytics technology for subsurface applications throughout Schlumberger. Aria is quite active in SEG and currently serves as Associate Editor of Geophysics, Member of the Research Committee, Director of SEAM, and 2021 SEG Annual Meeting Technical Program Co-Chair.
Aria was the 2014 SEG North America Honorary Lecturer. He holds 40 U.S. patents/patent applications, has published five book/book chapters, and written more than 90 scientific articles in journals, 200 conference proceedings papers, and 60 conference abstracts. He also has presented more than 300 invited and contributed talks in international conferences, institutes, and universities.
SEG Honorary Membership 2022
James E. Gaiser has made major contributions to exploration geophysics during his 45 years of work in elastic-wave seismology and anisotropy as applied to surface and borehole seismic methods. He is an innovative researcher who has spent his career in the energy industry working in leading positions with companies including ARCO, Western Geophysical, WesternGeco, GX Technology (ION Geophysical), GeoKinetics, and CGG, where he used advanced analytical techniques to solve exploration problems. Gaiser is especially known for his work in borehole anisotropic phase velocity analysis and in the application of converted waves to improve the understanding of shear-wave anisotropy and coordinate systems for fracture characterization, three-component (3C) vector fidelity, and VP/VS analyses. With this work, he enhanced the full multicomponent framework and workflow from acquisition to imaging and inversion to interpretation. Throughout his career, he has generously shared his knowledge and experience with others. He has given more than 100 presentations at SEG and European Association of Geoscientists and Engineers (EAGE) meetings. He has taught “Application and interpretation of converted waves” for 25 years with SEG’s Continuing Education program and presented his Distinguished Instructor Short Course, “3C seismic and VSP: Converted waves and vector wavefield applications” 16 times. Gaiser has actively participated in numerous SEG committees as well as contributed to EAGE, Denver Geophysical Society, Geophysical Society of Houston, Canadian Society of Exploration Geophysicists, American Association of Petroleum Geologists, and Society of Petroleum Engineers. He received SEG Life Membership in 2007
Biography Citation for SEG Honorary Membership
Contributed by Wenyi Hu
During the past 20 years, Aria Abubakar's crucial and groundbreaking contribution to the advancement of the science of geophysical exploration and his tireless service to the scientific community have benefited both the oil and gas industry and SEG. It is my great pleasure to write the Honorary Membership award citation for Aria.
Standing at the forefront of technology innovation, Aria's insightful research spans many important areas of applied geophysics. After receiving his PhD from Delft University of Technology, he rapidly achieved a recognized lead status and established himself as a pioneer in the areas of 2.5D modeling and inversion algorithms for crosswell electromagnetics, controlled source electromagnetics, and magnetotellurics. He and his team received a 2010 Hart Meritorious Award for Engineering Excellence for Schlumberger's DeepLook EM technology. The award recognized his distinguished creative achievements in his electromagnetics research and his invaluable initiative and lasting contributions to the progress of this technology, now a main processing workhorse for subsurface information retrieval.
Aria then dedicated effort to pushing forward the potential of seismic full-waveform inversion (FWI). Thanks to his strong interdisciplinary technical background, he invented various unconventional techniques to improve the accuracy and efficiency of FWI, such as automated regularization and contrast source inversion algorithm. Both inventions are not only regarded as real breakthroughs in geophysical inverse problems but also are cited widely and hailed in the world of medical imaging. After that, Aria and his team brought these technologies to the next level by integrating seismic, electromagnetic, gravity, and dynamic information such as production data and demonstrated its great potential in 4D reservoir monitoring applications. Because of the immense and influential impacts of these works, he served as the 2014 SEG North America Honorary Lecturer, giving the lecture titled Joint inversion of multiphysics data for petrophysical and engineering properties.
Since late 2017, Aria has been pushing the utilization of machine learning and artificial intelligence for geologic and geophysical problems. He and his collaborators have shown successful applications of these technologies, such as seismic fault and salt body detection; seismic stratigraphy interpretation; log quality control, correlation, and interpretation; static model building (via seismic inversion and/or property inversion); etc. Due to his drive on the topic, he has been chairing the Data Analytics Subcommittee in the SEG Research Committee. He was selected as a 2020 SEG-AAPG Distinguished Lecturer, offering a lecture titled Potential and challenges of applying artificial intelligence and machine learning methods for geoscience.
Aria plays a critical role in many SEG activities and continuously contributes to the Society in various aspects and fields. He has been serving as an associate editor for Geophysics in the areas of electrical and electromagnetics and seismic inversion since 2011. In 2019, he proposed and successfully organized a special section in Geophysics on machine learning and data analytics for geoscience applications. Aria is the current chair of the SEG Research Committee. In addition, he has been on the SEAM Board of Directors since 2018 and is the board liaison for the SEAM Artificial Intelligence project. This year, he has been working as the Technical Program chair for the IMAGE 2022 conference in Houston and the 2022 Energy in Data conference (a joint event between SEG, the American Association of Petroleum Geologists, and the Society of Petroleum Engineers) in Austin.
Today, Aria's tremendous scientific achievements and his relentless dedication to SEG are recognized with Honorary Membership. His pioneering accomplishments, dedication to innovative research, and exemplary leadership will continue to have a huge impact on geophysical exploration, digital transformation, and other scientific and technology domains.
2020 SEG 3Q/4Q Distinguished Lecturer
Potential and challenges of applying artificial intelligence and machine-learning methods for geoscience
In recent years we have witnessed great achievements accomplished by artificial intelligence (AI), machine learning (ML), and/or data analytics in various areas such as e-commerce, computer vision, social media, self-driving cars, natural language processing, and healthcare. Driven by the advances in the GPU technology, cloud computing, and the rapidly increasing data volumes within the geoscience applications, the energy industry has recognized and embraced the tremendous potential of AI/ML and data analytics. Early research and development utilizing these algorithms for geoscience applications have shown encouraging and promising results. This lecture will present the potential and challenges of AI/ML and data analytics practice in geoscience, as well as the successes and failures to date.
We will discuss a variety of highly successful geoscience applications that leverage AI/ML and data-analytics algorithms to improve efficiency, accuracy, and to automate geoscience workflows, and to explore a new way of extracting values from geoscience data. In addition, we also will touch upon a variety of general questions which naturally arise due to the emergence of these technologies in geosciences. Some of these questions are: What other challenging problems can be formulated and solved effectively by AI/ML? How do we tailor the AI/ML and data analytics algorithms and paradigms to meet the specific properties of geoscience data? How do we fully exploit the power of AI/ML and data analytics while combining them with physical constraints? When should we and should we not apply AI/ML and data analytics approaches? Lastly but more importantly, how can we translate AI/ML and data analytics-based workflows from proof-of-concept works to scalable commercial products.
Additional Resources
A recording of the lecture is available.[1]
Listen to Aria discuss his lecture in Applying machine learning and AI to the geosciences, Episode 86[2] of Seismic Soundoff, in-depth conversations in applied geophysics.
2014 SEG Honorary Lecturer, North America
Joint inversion of multiphysics data for petrophysical and engineering properties
A variety of measurements may illuminate the reservoir with varying coverage and resolution such as: electromagnetic (EM); controlled-source EM (CSEM); magnetotelluric (MT), surface-to-borehole EM (STB-EM); crosswell EM; seismic (surface seismic, crosswell seismic, and VSP); gravity (surface and borehole); and production history/well testing data. The interpretation of each measurement on its own will provide incomplete information due to nonuniqueness and limited spatial resolution. However, when integrated and combined with other measurements such as near-wellbore data, they may provide considerable value such as, for example, to enable estimation of reservoir properties, to obtain an improved reservoir model, and to provide a physics-based reservoir upscaling. At the end, it will help us in making appropriate field management decisions with reduced uncertainty.
This presentation will review joint inversion algorithms and workflows for integrating EM, seismic, and production data. It will analyze challenges, advantages, and disadvantages of these approaches. In particular, for reservoir characterization applications, joint structural and petrophysical algorithms for integrating EM and seismic data (CSEM and surface seismic, and crosswell EM and crosswell seismic) will be presented. For reservoir monitoring applications, the talk will describe EM data (for single-well, crosswell and STB) inversion algorithms constrained by the fluid-flow simulator. In the inversion for both EM and seismic, a full nonlinear approach (the so-called full-waveform inversion) will be employed so that all the information in the data can be utilized. Some test cases will be discussed.
References
External links
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