Developing algorithms to analyze data gathered during drilling using big data approaches - Features, limitations, main rules

Developing algorithms to analyze data gathered during drilling using big data approaches - Features, limitations, main rules

Big data

Gas industry

Predictive analytics

Infill drilling

Data Analytics

Well drilling

The paper describes the main approaches used in the development of predictive analytics algorithms, both of a general nature and in the field of well drilling. When describing the algorithms used, the basic assumptions of each and the ensuing limitations of the developed model are explained. The necessity of building hybrid models, involving the full amount of information collected, including calculations carried out during the construction of the well, both from the engineering and geological sides, is shown. The paper discusses the culture of working with data in the oil and gas field in general and in particular well drilling. The current level does not allow companies to create scalable solutions of predictive analysis. As a result of the work done, the basic rules were proposed, the first step was taken towards standardizing the process of collecting and analyzing information flow arising during the construction of wells. Copyright 2020, Society of Petroleum Engineers.

Zinovyev, Alexey Alexeevich

Nechaev, Artem Valentinovich

Ocheretyanyy, Anton Nikolaevich

Volkov, Dmitrii Yurievich

Petrakov, Yuriy Anatolyevich

Sobolev, Alexey Evgenyevich

SPE Russian Petroleum Technology Conference 2020, RPTC 2020, October 26, 2020 - October 29, 2020

2020

conferencePaper