Dear Members and Friends,
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We hope you can join us, and make the most of SPE Distinguished Lecturer– Shahab D. Mohaghegh’s virtual visit to our section.
SPE Distinguished Lecturers are industry experts and outstanding speakers, nominated by their peers, to share their knowledge and expertise on the latest industry trends and technologies with SPE members throughout the world through visits to local sections.
Java Indonesia Section
Monday, 19 April 2021
08:30 AM
for Non Member, please register by sending an email to Java@spemail.org
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Abstract:
Subsurface Analytics is an alternative to traditional reservoir modeling and res. management.
Positively influencing subsurface related decision making is the most important contribution of any new technology. Subsurface Analytics is the application of Artificial Intelligence and Machine Learning (AI&ML) in Reservoir Engineering, Characterization, Modeling, and Management. Applicable to both conventional and unconventional plays, Subsurface Analytics goes far beyond the traditional statistical algorithms that use only production data and fail to take into consideration the important field measurements such as well trajectories, well logs, seismic, core data, PVT, well test, completion, and operational constraints. Subsurface Analytics is the manifestation of Digital Transformation in Reservoir Engineering, Modeling, and Management.
Subsurface Analytics is a new and innovative technology that has been tested and validated in a large number of real life cases in North and Central America, North Sea, Middle East, and Southeast Asia. It has been successfully applied in several highly complex mature fields where conventional commercial reservoir simulators were unable to simultanuously history match multiple dynamic variables for large number of wells. Results and field validations from multiple case studies are included in the presentation.
Subsurface Analytics addresses realistic and useful applications of AI&ML in the upstream Exploration and Production Industry. The technology has been validated and confirmed for (a) prediction of well behavior under different operational conditions, (b) modeling and forecasting pressure and saturation distribution throughout the reservoir, (c) infill well location optimization for both producers and injectors, (d) choke optimization for production improvement, and (e) completion optimization for production enhancement.