Tech Breakfast: Modern Seismic Reservoir Characterization: Applications of Some Conventional and ... - Jan 11th

Complete Title: Modern Seismic Reservoir Characterization: Applications of Some Conventional and Machine Learning Workflows

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Speaker: Satinder Chopra, SamiGeo Consulting Ltd., Founder and President 
Co-Author: Ritesh Kumar Sharma, SamiGeo Calgary

The seismic reservoir characterization of today is more sophisticated and comprehensive. Modern seismic data acquisition, processing, and imaging, with long offset, wide azimuth data is yielding higher resolution, and even with conventional workflows leads to improved quantitative interpretation. Conventional workflows can be improved upon by bringing in changes which can result in value addition to achieve the objective for a project. Example changes could be the use of a calibrated well-driven velocity field in place of the velocity field obtained from processing of seismic data, bringing in appropriate poststack processing steps for preconditioning noisy prestack seismic data from areas high-velocity near surface geological formations impact the quality of seismic data, generating more accurate low-frequency impedance models for prestack simultaneous impedance inversion using multiattribute analysis, and even using different facies trends for inversion of seismic data for multi-level pay formation as in the Permian Basin.

Successful implementation of such workflows could result in fully integrated, three-dimensional characterization, and information on reservoir heterogeneity. Accounting for anisotropy in seismic data during processing and reservoir characterization is important, whether that is in the form of amplitude or velocity. In such cases reservoir properties estimated from seismic data in the form of lithology and petrophysical properties are found to be more realistic. 

Additionally, utilization of machine learning workflows contributes to an improved level of understanding of the reservoir in terms of lithofacies and the overall heterogeneity. Application of advanced visualization tools aids such understanding. 

In our talk, example workflow applications will be demonstrated for seismic impedance inversion, and for deterministic and probabilistic machine learning facies classification that enable an integrated reservoir characterization. Such evolving reservoir characterization workflows tailormade for the end objectives are rightly being called ‘modern’. 

Speaker Biography: Satinder Chopra, SamiGeo Consulting Ltd., Founder and President
Satinder Chopra is the founder and President of SamiGeo Consulting Ltd., based in Calgary. He has 36 years of experience as a geophysicist specializing in processing, special processing, interactive interpretation of seismic data and reservoir characterization. His research interests focus on techniques aimed at characterization of reservoirs. He has excellent communication skills, as evidenced by the many presentations and talks delivered, as well as the books, reports, and papers he has written. He has published eight books and more than 500 papers and abstracts. His work and presentations have won several awards from international professional societies.  He has been the 2010/11 CSEG Distinguished Lecturer, the 2011/12 AAPG/SEG Distinguished Lecturer, and the 2014/15 EAGE e-Distinguished Lecturer.

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1/11/2023 7:00 AM - 8:00 AM
Central Standard Time

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