Background:

Adopting digital technology to support critical decisions has transitioned from an opportunity to a necessity for oil & gas companies. Management teams are challenged to find solutions in a landscape of:

• Rapid increases in the volume of metrics and data sources
• A deluge of new and existing vendors claiming capabilities
• Uncertainty about the impact that innovation and proprietary locks will have on obsolescence/compatibility

This forum will bridge the previous two forums (Analytics & Machine Learning (AML) and Internet of Things (IoT)) with a focus on ensuring the data captured by source systems is accurate, complete and available for use by analytics tools in time to support decisions. Data management is an often-overlooked process that is as complex as it is unglamorous, yet without it, digital investments are of little or no value.

The marketplace is inundated with data-quality cure-all claims. Our scouting and research efforts are focused on exposing only the most talented Data Management firms that possess unique solutions to the exclusive problems facing the oil and gas industry.

Study Scope:

The study will be focused on solutions that apply advanced analytics, machine learning and automation (methods typically reserved for complex decision support) to address data management challenges for the following components of data management:

USE CASE SPECIFIC SOLUTIONS

• Land
• Reservoir characterization
• Field (drilling, completions, production)
• Supply chain

MASTER DATA MANAGEMENT

• Data definitions, standards and governance

EXTRACTION FROM SOURCE SYSTEMS

• Protocols, pipelines and scheduling

TRANSFORMATION

• Cleansing data to resolve exceptions
• Translating field names and data types to standard conventions
• Integrating (joining/matching) based on relationships

LOADING & STORAGE

• Tools and table structures to feed analytics platforms