Subsurface Data Analysis, Geomodeling and Geostatistics

Instructor: David Garner, TerraMod Consulting
Dates: June 8-11, 2020 (4 days) | 8:30am-3:30pm
Location: CSPG Office Classroom, 540-5 Ave SW, 150, Calgary AB
CPD: 26

CSPG Early-Bird Member Rate
  $2300
Early-Bird Non-Member Rate   $2500

Rates increase by $200 when early bird ends - May 19th
Registration closes: June 1st

Become a CSPG member and receive discounted rates for courses!
Registration includes: Printed course manual, coffee breaks and lunch. 

Overview
Geostatistics is the mathematical engine of spatial data analysis and geomodeling. Dominant uses of geostatistics in the industry are multi-variate data analysis, mapping, integrating diverse variables, building geomodels, resource evaluation and decisions. Solid training in Geostatistics is an essential qualification of a proficient Geomodeler, data scientist and problem solver within subsurface teams. Deterministic and stochastic methods are combined. Uncertainty is a fundamental topic because many underlying applications are stochastic and data input are a sparse or imprecise sampling of reservoirs. Geostatistical basic theory and best practices are explained along with a variety of practical tips, tools of the trade. Uses of probabilistic results are discussed. Context for the subsurface team is given in context with workflow element descriptions and case studies. The course provides grounding in theory and thought process.

Afternoon exercises are designed to reinforce the theory and lecture through hands-on learning. The advanced exercises are scripted to allow flexibility to experience the impact of key parameter choices on model outcomes without getting bogged down in the software during a short course. The Isatis Geostatistics toolkit is used for exercises since it is a flexible software for learning where basic techniques are transferable to geomodeling packages.

Module 1 (computer exercises)
Introduction: Geomodeling and the Subsurface Team - What is Geostatistics?
Essential statistics and terminology
Purpose: Background for exploratory data analysis, preparing for mapping and model building
 · Regionalized Variables: Data Types, definitions
 · Univariate Statistics: Measures of position, spread, and shape; vertical facies proportions, stationarity, proportional effect
 · Box plots, Q-Q plots, Normal score transform
 · Bivariate Statistics: Covariance and correlation; principal components
 · Quantifying Variability/Spatial Continuity: Variograms- experimental, anisotropy; hand calculations; variogram maps; Behaviour, impact of outliers and calculation tips
 · Variogram Models: illustrations; nested, issues, fitting tips and tricks

Module 2 (computer exercises)
Geostatistical Estimation
 · General estimation techniques
 · Kriging: simple and ordinary; Kriging by hand with a variogram model; Kriging weights, Cross validation, stationarity
 · Multi-variate: Co-Kriging; collocated co-Kriging; Kriging with External Drift (universal Kriging)
 · Trends in data: handling non-stationarity
 · Case examples with mapping
 · Geostatistical Depth conversion and QC, brief introduction, e.g., for model framework
 · Multi-variate Special: Principal Components analysis; seismic attributes; statistical plays

Module 3 (computer exercises)
Simulation
 · Simulation versus Estimation concepts
 · Conditional Simulation; random walk and search neighbourhood
 · Sequential Gaussian Simulation processes
 · Petrophysical Trends and secondary data
 · Uses of models: probability mapping and uncertainty; risked volumetrics; avoiding bias in estimates
 · Post-processing special topic: Checking results, direct forecasting without simulation
 · Case History

Module 4 (computer exercises)
Facies Simulations
 · Stochastic Methods summary
 · Stratigraphic coordinate systems
 · Deterministic facies trend modeling as a model constraint
 · Object methods-summary
 · Pixel methods: Illustrated description of algorithms for Truncated Gaussian (TGS), Truncated Pluri-Gaussian (PGS), Sequential Indicator (SIS), Multiple Point (MPS)
 · Facies methods characteristics and choices

Module 5 & 6 (Lecture)
Generalized Subsurface Workflows and Workflow Elements
 · Case Histories
 · Compiling and checking the input databases, data types, model planning
 · Defining the structure and stratigraphic framework; faults, grids and model sizing
 · Facies inputs: Diverse Sources; Visual versus Electrofacies classification (machine learning); Issues, scale, rules for preparation of facies logs for modeling improvements
 · Facies trend modeling: proper techniques and choices for building 1D, 2D and 3D facies proportions; integration of seismic attributes
 · Topics on Petrophysical modeling for porous media and fluids: Porosity, water saturation methods, permeability, mechanical; scale and specific rules, oil in place
 · Re-scaling for the simulator techniques, specific parameter choices and critical issues
 · Post-processing: net pay, connectivity, summarizing uncertainty
 · Linking static to dynamic behavior through direct forecasting (proxies and type curves) in resource plays, delineation, and developments

                  

Learning outcomes:
To provide grounding in subsurface data analysis, geomodeling and geostatistical thought process. Improved understanding of best practices, tools of the trade and important workflows. An introductory overview of necessary basic geostatistical theory for data analysis and subject knowledge to improve team communication. Improved understanding of the uses and limitations of geostatistics and geomodeling.

Who should attend:
Technical and decision makers working on subsurface hydrocarbon reservoirs in multi-disciplinary teams using or considering using geomodeling. This includes geomodelers, technicians, geologists, geophysicists, petrophysicists, reservoir engineers, technical managers, and new hires.

Computer requirements: 
Windows based laptop. The Isatis (and Isatis.new) Geostatistics Toolkit Software from Geovariances will be provided for the course exercises and will be installed on attendees’ laptops at the start of the course.

Exercises:
Several on main topics with an integrated probabilistic volumetric study. Exercises are intended to reinforce concepts and practical application.

Prerequisites:
None, but general experience with integrated subsurface teams planning to use or using geomodeling would be helpful. Openness to seeing basic mathematical theory and new concepts.

Biography

David Garner has more than 30 years of technical experience in industry with 24 years in applied geostatistical studies in petroleum and mining. He has published and presented over 25 papers, many of which were peer-reviewed. Currently, he is a consulting geomodeling advisor and trainer and an associate of Geovariances in Fontainebleau, France. Previously Mr. Garner held positions in Halliburton as a Chief Scientist in R&D, as a Specialist in Statoil’s Heavy Oil Technology Centre-Unconventionals R&D, as Senior Advisor Geologic Modeling for Chevron Canada Resources, and Reservoir Characterization Specialist at ConocoPhillips Canada. He was president of TerraMod Consulting for 6 years applying geostatistics and geomodeling techniques mainly for large international reservoir studies and mining resources. As a volunteer, Mr. Garner currently serves as a co-chair for the CSPG Geomodeling Technical Division committee and was chairman for three CSPG Gussow conferences, Closing the Gap I, II, and III: Advances in Geomodeling for Petroleum Reservoirs held in 2011, 2014, and 2018. He co-edited of the special edition December 2015 BCPG on Geomodeling Advances and the 2013 CSPG Memoir 20. He served a board term as CSPG Finance Chair. 

Mr Garner is registered as a Professional Geophysicist (P.Geoph) through the Alberta’s Association of Professional Engineers and Geoscientists (APEGA). - https://www.linkedin.com/in/dlgarner/ 


Are you waiting for approval to register for this course? Please let us know that you are waiting for approval to attend this course and we will try and protect a spot for you. You will also be helping us out in deciding if we must cancel a course or continue with registration. Email Kristy.casebeer@cspg.org

Cancellation Policy:
Cancellation policy: No refunds available. Substitutes acceptable.
Please email Kristy.casebeer@cspg.org

CPD Credits 1 hour of technical training is 1 APEGA CPD Credit
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