Course Descriptions

Essential Geoprocessing and Data Management Tools

Essential Geoprocessing and Data Management

This course provides users with essential information on geoprocessing and data management including tools and best practices. Designed to promote high quality, consistent data management practices, this course is recommended for all users.  Some of the key topics covered include:

• Data Types
• Workspaces and Geodatabases
• Choosing the Right Geoprocessing Tools
• Optimizing Performance
• Considerations When Working with Large Datasets
• Setting Up the Geoprocessing Environment
• Error Handling

Model Builder - The Essentials

Knowing how to properly and efficiently analyze and manage your data and making the most of the tools available means higher data quality and the elimination of repetitive data processing tasks.  This course provides students with the essential skills necessary to use this graphical modeling framework to design models for geoprocessing and data management.  Some of the key topics covered include:

• Model Elements
• Managing Intermediate Data
• Managing Environment Settings
• Error Handling/Interpreting Errors
• Model Documentation
• Saving and Sharing Models

Geoprocessing Using Python

This course is designed for intermediate level users who are seeking to expand their data management tools and techniques. Students will learn the essentials of using Python as a geoprocessing tool.  When combined with our Model Builder courses this course gives users a comprehensive knowledge of available geoprocessing tools.  Some of the key topics covered include:

• Batch Processes
• Scripting Fundamentals
• Overview of the Geoprocessor
• Reading/Writing Feature Geometry
• Tool Parameters
• Error Handling
• Creating Tools from Scripts and Vice Versa

Advanced Data Management Techniques  

Model Builder - Advanced Techniques

Students learn to use advanced Model Builder techniques to build more complex models. This course builds on our Model Builder - The Essentials course to introduce more advanced procedures and workflows.  Some of the key topics covered include:

• Batch Processes
• Conditional Processing
• Using In-Line Variables
• Working with Lists
• Looping and Feedback
• Running External Models
• Managing Outputs

Advanced Scripting with Python

This course is designed for advanced users already familiar with using Python as a geoprocessing tool. Some of the key topics covered include:

• Data Access with Cursers
• Creating and Using Objects for Parameter Values
• Script Tools and Tricks
• Making Scripts More Efficient
• Effective Error Handling

GIS Essentials

GIS for the Oil and Gas Industry

This course is taught at an introductory level and examines the concepts behind spatial data and use of GIS software in the Oil and Gas industry. This course provides students with an excellent overview of general spatial data concepts and software, as well as providing hands-on experience working with the components, functions and applications of ArcGIS. Some of the key topics covered include:

• Coordinate Systems, Map Projections, and Datums
• Map Design and Presentation
• Labeling, Annotation and Map Graphics
• Geoprocessing Techniques
• Attribute and Spatial Data Queries

Spatial Analysis using Raster Techniques

This course offers GIS users an opportunity to learn about the power behind the ESRI Spatial Analyst extension for ArcGIS. This extension offers a broad range of spatial modeling and analysis tools that are particularly suited for Oil and Gas analysis and decision support. Students will be given a broad overview of the Spatial Analyst extension as well as a deep understanding of relevant Oil and Gas applications. Hands-on sessions are used to explore:

• Raster Datasets - Types and Properties 
• Raster Analysis and Analysis Environment
• File Format Support and Data Conversions
• Generating and Managing Digital Elevation Models
• Choosing Interpolation Techniques
• Raster Calculator Capabilities
• Automation Using Model Builder

Where's My Data?

Businesses make a significant investment into the development of their data resouces. As important as the investment into the data itself is ensuring that the business users are aware of the resources that are available to them. This course is a 100% customized course that introduces students to the data resources available for them to incorporate into their workflow.

• Data Resoures
• Templates
• Data Management Approach
• Data Standards (Naming Convention, Symbology)
• Metadata Standards
• Querying and Selecting Events

 Data Integration using Linear Referencing

Although linear referencing has long been associated with pipeline data management, its relevance in well, seismic, and land data is becoming better known and understood.  This main goal of this course is to give each student a solid knowledge base on linear referencing, dynamic segmentation, and how these are both used for management and integration Oil and Gas datasets.  Hands-on examples will allow students to gain experience with:

• Terminology of Linear Referencing 
• Creating Route Geometry
• Designing Event Tables
• Applying Dynamic Segmentation
• Route Calibration Approaches
• Querying and Selecting Events

Metadata - Increasing your Data's Value

With the amount of spatially based data and the number of people making use of it on the rise the importance of good Data Management and documentation has never been more at the forefront.  Metadata should be a key piece of every GIS Data Management system.  Well maintained metadata increases the value of data to your users not only by making it easier to locate, but also by providing key documentation that improves the user's interpretation and use of the data.  Students will be introduced to:

• Metadata as a Data Management Tool
• Navigation of the ArcCatalog Metadata Interface
• Existing Metadata Guidelines and Standards
• Best Practices
• Restrictive Vocabulary
• Interaction with Metadata Search Tools

Editing and Georeferencing

This course covers important aspects of Editing and Georeferencing. This includes how to create new datasets as well as edit existing data including attributes using a variety of editing tools and commands. Shortcuts and good practice approaches are presented to develop efficient workflows. A variety of techniques are introduced that can be used to georeference datasets to real world coordinates. Methods for working with CAD, raster and vector data formats will be explored in a hands on environment. Some of the key topics covered include:

• Feature Structure
• Field Calculator
• Spatial Adjustment
• Transformations
• Rectifying an Image

Label Management

This course covers the many approaches that can be taken when using text in your mapping projects. The course starts with basic labeling techniques including a discussion of best practices and advances through more advanced labeling methods. Students will learn efficient labeling techniques that can be incorporated directly into their workflows. Some of the key topics covered include:

• Maplex
• Label Classes
• Basic Annotation
• Advanced Expressions
• Flow of Control Expressions
• Conditional Logic Expressions