Interpretation Special-Section: Insights into digital oilfield data using artificial intelligence and big data analytics
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Recent advancements in deep learning and AI have transformed decision-making in the oil and gas industry through big data analysis. Companies are increasingly utilizing cloud-based AI and machine learning to enhance operations, manage risks, and improve safety, despite challenges in investing in these technologies. A call for papers is issued for a special section on the application of AI and big data analytics to improve digital oil field data interpretation, with submissions due by October 1, 2018, for publication in August 2019.
Interpretation Special-Section: Insights into digital oilfield data using artificial intelligence and big data analytics
- 1. Recent advances in deep learning algorithms, artificial intelligence and increases in compu- tational efficiency have driven modern-day decision making through the analysis and interpretation of big data. The digital and connected oil field has led to petabytes of rich, heterogeneous data from a diverse set of sources. Seamless interactions between computational scale, intelligent algorithms, databases, and web services now are neces- sities. A comprehensive set of cloud-based solutions from leading technology com- panies are in some ways answering these needs. Artificial intelligence (AI) technologies and machine learning (ML) systems staged on cloud-based solutions have now become an integral part of the operations of most oil and gas companies. Data now are viewed as an extremely valuable resource with a huge upside for companies with innovative, robust machine learning strategies. In the ongoing “new normal” low commodity price environ- ment, machine learning can save time, reduce costs, boost efficiencies, manage risk, and improve safety. However, investing in predictive technology to become more productive is challenging and easier said than done. What are the strategic considerations and challenges for adopting an AI platform? How can you seamlessly integrate an AI platform with other systems without prohibitively high costs? And what’s the guarantee for return on investment? In this special section, we address the studies surrounding the heterogeneous integration, assumptions, case studies and application of robust algorithms that can partially automate the interpretation and characterization of geo- logical, geophysical, petrophysical and engi- neering data within an integrated stratigraphic framework. The editors of Interpretation (www.seg.org/ interpretation) invite papers on the topic Insights into digital oil field data using ar- tificial intelligence and big data analytics for publication in a special section of the August 2019 issue to supplement the journal’s regular technical papers on various subject areas. We are seeking submissions on related topics including: • Applications in drilling optimization • Rapid interpretation of downhole sensors and instrumentation including but not lim- ited to DTS/DAS • Automated well logging QC, interpretation, and correlation • Use of drilling data to optimize comple- tions, and future drilling operations. • Completion design, well placement, frac- ture placement and artificial lift optimization • Applications in reservoir modeling and simulations • Applications to seismic processing and other related geophysical problems (e.g. velocity analysis, de-multiple techniques) • Application for automated seismic interpre- tation (automated salt and fault applications and horizon interpretation) • Application of seismic analysis and inver- sion and 4D analysis • Applications to reservoir characterization and reservoir management • Applications for various predictive analysis (e.g. reservoir property prediction, well-log analyses, production forecasting) • Applications in unconventional reservoirs • Integrated case studies pertaining to any of the topics above • Futuristic ideas/trends on application of data analytics in the oil and gas industry Interested authors should submit their man- uscript(s) for review no later than 1 October 2018 via the normal online submission system for Interpretation (https://mc.manu- scriptcentral.com/interpretation) and select the Insights into digital oil field data using artificial intelligence and big data analytics manuscript type. The special section editors would like to receive a provisional title and list of authors via email as soon as possible. The submitted papers will be subjected to the reg- ular peer-review process, and the contributing authors also are expected to participate in the peer-review process. CALL FOR PAPERS https://mc.manuscriptcentral.com/interpretation The submissions will be processed according to the following timeline: Submission deadline: Publication of issue: 1 October 2018 August 2019 Interpretation, copublished by SEG and AAPG, aims to advance the practice of subsurface interpretation. Special section editors: Vikram Jayaram Vikram.Jayaram@pxd.com Andrea Cortis Andrea.Cortis@pxd.com Bill Barna bibar@microsoft.com Atish Roy Atish.Roy@bp.com Deepak Devegowda Deepak.Devegowda@ou.edu Jacqueline S. Floyd Jacqueline.Floyd@bhge.com Pradeepkumar Ashok pradeepkumar@mail.utexas.edu Satyam Priyadarshy Satyam.Priyadarshy@halliburton.com Insights into digital oil field data using artificial intelligence and big data analytics Aria Abubakar aabubakar@slb.com Chiranth Hegde chiranth.hegde@utexas.edu