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В рамках программы SPE Distinguished Lecturer в Новосибирске  выступит distinguished lecturer Randal LaFollette, который в настоящее время работает в компании Baker Hughes.

Название доклада: Lessons Learned From Data Mining in Unconventional Reservoirs.

Доклад будет представлен на английском языке. Лекция организована Новосибирской секцией SPE​, приглашаются все желающие.

Краткая биография докладчика и аннотация доклада.


The task of identifying key production drivers in unconventional reservoirs remains challenging, even after decades of exploration and production in North America during which tens of thousands of horizontal unconventional wells have been drilled and completed. Tens to hundreds of variables, categorized as reservoir quality, well architecture, completion, stimulation, and production metrics, are involved and there are many different interrelationships among the variables to be considered. Further, formation evaluation is typically minimal and there are unknown variables in the system that can only be guessed at, ignored, or proxied.

The author’s team has combined Geographical Information Systems (GIS) analysis and multivariate analysis using boosted regression trees for improved data mining results as compared to univariate methods. The purpose of this lecture is to discuss key elements of data mining in unconventional reservoirs, in order to raise awareness of cutting-edge statistical tools and methods being brought to bear in the industry. The presentation will provide highlights of real world examples of data mining projects in three different shale plays.

If there were only one idea for audiences to take away from the lecture, it would be that exploiting unconventional reservoirs is a highly complex task with many moving parts and data mining is a needed tool to be applied to better understand the importance of specific well productivity drivers. Another way to say it is that the talk is intended to provide the audience with improved statistical methods for the “statistical” plays so that multi-million dollar decisions can be truly data-driven.


Randy LaFollette is the Director, Applied Reservoir Technology, for Baker Hughes Pressure Pumping. Mr. LaFollette holds a BSc degree in Geological Science from Lehigh University, Bethlehem, Pennsylvania. He has 37 years of experience in the industry. He is active in SPE, and AAPG, aiding with conference organization and presenting on various reservoir, completion / stimulation, and data-mining topics. Mr. LaFollette is a subject matter expert in Geoscience and Petroleum engineering for Baker Hughes and leads a team of experts responsible for structuring and implementing geospatial and data-mining studies of stimulation effectiveness linking reservoir quality, well architecture, well completion, and treatments performed to production results.