A Paradigm Shift in Core Analysis

1) CoreDNA: Multi-sensor core logging technologies

2) Case Studies

3) Unsupervised Machine Learning application for automated lithology identification

Introduction

Objectives of This Talk: Presentation of CoreDNA solution that combines a selection of transdisciplinary, high resolution, non-destructive core logs to enable an early comprehensive description of cores and rapid estimation of properties of formations few days after opening core barrels.

Methodology, Procedures, or Processes: A perfectly leveled surface of maximum 4 cm is created by grinding the core with PDC cutters by removing at each passage not more than 200 μm of rock. In total, only a few millimeters of matter have been powdered. Several sensors are eventually run on this surface to produce continuous high-resolution core logs including elemental composition (XRF), grain size index, rock strength, ultra-high resolution images (definition similar to thin sections), etc…

Results, Observations, Discussions, and Conclusions: Results of these fast tests (3ft per hour) are analyzed real-time and turned into high resolution, continuous quantitative profiles of properties (petrophysical, geomechanical, and geochemistry) fed into (unsupervised) machine learning algorithms for the automated identification of lithofacies, enabling the detailed understanding of reservoir architecture and the design of tailored plug selections and the programming of subsequent steps in core analysis programs, even remotely. A number of case studies on reservoirs from different regions all underline the benefit of this disruptive technology in core analysis standards when run prior (i) taking any sample (plugs and preserved) and (ii) slabbing the cores.

Date:

2021 July 27 (Tuesday)

Time:

14:30 Iran local time, 12: 00 CET

Registration Deadline:

2021 July 25, 18:00 Iran local time, 15:30 CET

Eligibility qualification for the participants:

Faculty members, researchers, MSc/PhD students and several people from oil & gas industry

Main presenter:

Dr. Christophe Germay

Dr. Christophe Germay is a founder and managing director of Epslog since its creation in 2005. His current interests are with the development of technologies for the acquisition of high-quality core based data and core digitalization process for machine learning applications.

Dr. Germay holds a BSc degree in Physics from the University of Liège, Belgium. He obtained a MSc degree in civil engineering from the University of Minnesota within the group that invented and patented the scratch test technology and a joint PhD degree from the University of Liège and University of Minnesota.

Registration fee:

Registration is free.