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Technical Sessions - North America Series - 2021

June 17 - November 18, 2021
Technical Sessions - North America Series - 2021

Our current environment has been profoundly changed, forcing all of us to work from home and connect differently, while facing growing challenges in the oil and gas industry.

In light of these circumstances, Emerson is introducing a series of online Technical Sessions covering the breadth of geoscience domains; from seismic depth imaging to reservoir modeling. We hope you will use this time to sharpen skills, learn new methods to help you improve efficiency, and connect with a geoscience subject matter expert who will answer your questions during each live session. 

We invite you to register for any or all of the lectures. 

Date

Title

Register

Thursday, June 17
9:00 AM CT

Presented by: 
Andrey Klimushin

Roxar API:Python Scripting for Geomodelers​
Technology:  RMS™​

Learn how to extend the functionality of the RMS geomodeling platform using libraries of pre-existing, customizable Python scripts, or bring your own scripts (open source or not) and plug them in. The possibilities are literally endless!

During this session, you will see how Roxar’s API (Application Programming Interface) helps to bridge the data science and geoscience worlds, through easy steps with Python-based scripts. It is simple and straightforward, and was designed for geoscientists, both those with prior experience with Python coding and those without. Prerequisites: An analytic mind and curiosity!

Wednesday, June 30
9:00 AM CT

Presented by: 
Dennis Ellison

A Step Change for Stochastic Inversion — Getting Results Faster
Technology:  Quantitative Seismic Interpretation (QSI)
This session will show how the Emerson E&P modified approach to stochastic inversion helps our customers to de-risk reservoir models and identify new drilling targets within their acreage faster without sacrificing quality. As seismic and well data contribute to different frequency bands, our technology accelerates the integration stochastic inversion results constrained to the seismic. Traditional stochastic inversion requires several stochastic predictions, from which only those that match the seismic data are selected. In our implementation, deterministic inversion outputs are merged with numerous broadband-frequency well simulations to generate multiple realizations of the reservoir. This merging of the seismic after these simulations significantly reduces computation time while increasing reservoir resolution and rock property knowledge while honouring the match to the seismic data.

Thursday, July 15
9:00 AM CT

Presented by: 
Sasan Ghabari

A Collaborative Approach to Calibrating and Maintaining Evergreen Subsurface Models for Reliable Development Planning and Production Forecasting
Technology:  Big Loop™
See how Tempest ENABLE, Emerson’s machine-learning based technology for assisted history matching, can help ease the time-consuming history matching process and help identify multiple calibrated models critical for reliable production forecasts. A step-by-step assisted history matching and ensemble-based prediction workflow will be explained in detail.

 

Thursday, July 29
9:00 AM CT

Presented by: 
Pat Stirling

Advanced Tips and Tricks for Petrophysicists, Geoscientists and Data Technicians​
Featured technologies:  Geolog™

This presentation will focus on various methods of data searching, data querying and data manipulation available in Geolog. Most of the topics presented are a result of common ‘How to’ questions from our users.  Our solutions leverage the unique functionalities, flexibility and customization features inherent in the software, primarily in the base installation, but suplemented in some cases with the custom programing add on Loglan.

 

Thursday, August 19
9:00 AM CT

Presented by: 
Zahary Vera

Seismic Facies Analysis: Reservoir Insights Enabled by Machine Learning Technologies​
Featured technologies:  Epos™ 

In this session we will show how geoscientists can quickly gain insight into depositional settings using Machine Learning solutions to establish a relationship between the reservoir properties and natural cluster structures in the seismic data, resulting in a better understanding of reservoir quality and behavior. 

In this lecture, you will learn how to:

  • Reveal more geology from seismic data
  • Expand your seismic investigation toolkit
  • Improve confidence in reservoir prediction and delineation

Thursday, August 26
9:00 AM CT

Presented by:
Kim McLean
 

Optimizing Petrophysics to Solve Mineralogical Complexity in Conventionals and Unconventional Reservoirs
Featured technologies:  Geolog
Petrophysical analysis provides vital input to most, if not all, geoscience workflows. While a deterministic approach to formation evaluation will provide values for shale volume, porosity and saturation, taking into account mineral and fluid volume complexity can offer more insight into the distribution of your petrophysical properties.

In this session we will look at:

  • The theory behind the Multimin optimized petrophysical method in Geolog 
  • Utilizing the Monte Carlo method as part of the Multimin workflow
  • Probabilistic model switching

Thursday, September 23
9:00 AM CT

Presented by:
Elive Menyoli

3D Poststack RTM Demigration and Remigration​
Featured technologies:  The Kaleidoscope Project

Poststack demigration of an existing seismic image and remigration with alternative velocity models, enable seismic interpreters to economically evaluate different scenarios while incorporating their experience and knowledge of the field, maintaining consistency with the available dataset. This efficient workflow incorporates a modeling (demigration) step of the zero offset seismic data using the current best depth migrated image and its corresponding velocity model, followed by a zero offset remigration (poststack migration) using multiple sets of updated velocity models. The application utilizes the forward modeling and back propagation algorithm of the accurate Reverse Time Migration (RTM) method. The output is multiple depth images and depth structural maps.

 

Thursday, October 7
9:00 AM CT

Presented by:
Kim McLean

Integrated Petrophysical Interpretation to Unlock Unconventional Reservoirs​
Featured technologies:  Geolog™

Shale reservoirs are heterogeneous by nature, with facies that differ in mineralogy and geomechanical properties. We present a workflow that evaluates the mineralogy and geomechanical rock properties of a pilot well, and use the resulting logs as part of a machine learning workflow to identify our sweet spot facies in terms of original oil in place, mineralogy and mechanical properties. We then use this information to help optimally place a lateral well such that it leads to better placement within the reservoir sweet spot.

Thursday, October 21
9:00 AM CT

Presented by:
Bruno de Ribet

Enhanced Seismic Interpretation from Diffraction Energy​​
Featured technologies:  Epos™

Although diffracted energy is recorded during data acquisition, it is suppressed by conventional processing and standard imaging algorithms, where summations and averaging processes are applied, resulting in the loss of high-resolution structural information. Current processing workflows rightly focus on high specular amplitudes to enhance the continuity of seismic reflection events, thus improving the structural mapping of the subsurface. Consequently, in a traditional seismic interpretation workflow, some derived discontinuity attributes (e.g. coherence, curvature or fault likelihood) may carry only partial information. This presentation will describe the decomposition of the full wavefield, and the benefits of separating reflection and diffraction energy fields through various case studies, to provide geoscientists with high-resolution subsurface images containing different types and scales of discontinuous geometrical objects. The objective is to leverage the traditional seismic interpretation workflow by integrating information relative to diffraction energy like any another poststack attribute to be interpreted.

Thursday, November 18
9:00 AM CT

Presented by:
Craig Phillips, Petrophysicist, Crested Butte Petrophysical Consultants

Automating a Carbonate Characterization Workflow with Predictive Data Analytics: Arab D Case Study 
Featured technologies:  Geolog

This workflow will present a way to investigate, process, interpret and model the petrophysical properties for a typical Arab D carbonate reservoir, using advanced analytics, predictive modeling and the application of a machine-learning based approach. Cross plots and histograms as well as python opensource libraries Altair will be used for data visualization, followed by multi-mineral analysis, and a machine-learning kNN classification algorithm for predicting rock properties.


Biographies

Andrey Klimushin, Business Development Manager - Modeling

Andrey Klimushin has over 14 years of experience in subsurface modeling, business development and project execution. He spent eight years working in Moscow in geological modeling and subsurface studies for national (CGE, Gazprom-neft) and international companies (AGR petroleum, Roxar).


 

Dennis Ellison, Principal Consultant - Interpretation

As Principal Consultant for Interpretation at Emerson EPS North America, Dennis helps oil operators reduce costs and leverage their data with next-generation technology. His career started in depth imaging of geologically complex land data and transitioned into reservoir characterization and Quantitative Interpretation, focusing on unconventional reservoir property prediction. Dennis holds a Master’s degree in Geology and Geophysics from the University of Calgary in Canada. He is a member of CSEG, SEG, SPE, EAGE, and APEGA.

 

Sasan Ghanbari, Team Lead - Modeling

Sasan Ghanbari has extensive experience in offshore exploration and in the Canadian Oil Sands. He has also worked on various field studies and geostastical subsurface modeling in North America, South America, and the Middle East.  This work includes analyzing relevant data such as regional studies and uncertainty analysis to build realistic geological, geostatistical and reservoir simulation models. Sasan has been working with Emerson since 2004. He earned a degree in Petroleum Engineering from the University of Alberta and is a Professional Engineer.

 

Patrick Stirling, Sr Principal Consultant - Formation Evaluation & Drilling

Pat Stirling has over 18 years of experience in the oil and gas industry. He currently handles North American technical sales and support for Emerson's advanced Formation Evaluation solution; Geolog. Before joining Emerson in 2013, he worked at Schlumberger in Formation Evaluation acquisition, processing, interpretation and sales. Pat holds a BSc in Geology from the University of Saskatchewan, Canada.


Zahary Vera, Team Lead - Interpretation

Zahary Vera has been with Emerson for over 15 years, serving in a number of roles that provide support for Emerson E&P seismic interpretation and reservoir characterization workflows.  Zahary holds a BS Degree in Geophysical Engineering from Simon Bolivar University, Venezuela.


Kim McLean, Team Lead - Formation Evaluation

Kim McLean received her Bachelors of Science degree from the University of New Orleans before continuing to Central Washington University, where she studied the structural geology of the Tien Shan in Kyrgystan for her Master’s thesis. After receiving her MSc, Kim entered the energy industry, and now has over 15 years of experience. She worked at Halliburton and Paradigm before spending two years as the petrophysicist for the Pike Asset team with BP in Calgary.  At Emerson E&P Software, Kim applies her practical petrophysical experience to the work she does with the Geolog Formation Evaluation application.


Elive Menyoli, Business Development Manager - P&I

Dr. Elive Menyoli has over 15 years of experience in the oil and gas industry. Prior to joining Emerson, he worked at Marathon Oil and Total E&P USA, in deep water projects. Dr. Menyoli holds a MSc degree in Physics from the University of Goettingen, Germany and a PhD in Geophysics from the University of Hamburg, Germany.  He has authored numerous publications in seismic imaging and interpretation, with a recent emphasis on shale resource plays.

Dr. Bruno de Ribet, Technical Global Director - Strategic Projects

In this position, Dr. de Ribet advises on developing interpretation and reservoir characterization workflows that increase efficiency and take full advantage of the Emerson E&P Software suite of geophysical and geological innovations. Dr. de Ribet holds a Ph.D. in Geophysics from the Institute du Physique du Globe, Paris University. He has over 25 years of experience in the upstream oil and gas industry.