Duration: 1 or 2 Days
Instructor: Shahab Mohaghegh
Disciplines: Data Science and Engineering Analytics | Reservoir
Data-driven analytics is becoming an important point of competitive differentiation in the upstream oil and gas industry. When it comes to production from shale, companies are realizing that they possess a vast source of important facts and information in their data. In analysis and modeling of production from shale, our traditional techniques leave much to be desired. Field measurement data can provide much needed insight. Data-driven analytics is the set of tools and techniques that provides the means for extraction of patterns and trends in data and construction of predictive models that can assist in decision-making and optimization.
In advanced data-driven analytics, data from the well and the formation are integrated with field measurements that represent completion and hydraulic fracturing practices and are correlated with production from each well. As the number of wells in an asset increases, so does the accuracy and reliability of the analytics.
Attendees will become familiar with the fundamentals of data-driven analytics and the most popular techniques used to apply them such as conventional statistics, artificial neural networks, and fuzzy set theory.
This course will demonstrate through actual case studies (and real field data from thousands of shale wells) how to impact well placement, completion, and operational decision-making based on field measurements rather than human biases and preconceived notions.
CEUS: 0.8 or 1.6 CEUs (Continuing Education Units) are awarded for this 1- or 2-day course.