Automated Rig State Identification Using Machine Learning Algorithms

Recorded On: 04/17/2020

In the era of the Fourth Industrial Revolution (IR 4.0), the advancement in technology empowered engineers with integrated tools to help achieve maximum operation efficiency. These tools can use diverse types of data from high-level corporate reports to data generated by physical sensors attached to the equipment in remote operation fields. The low oil prices and the realization of the new industry revolution encouraged many oil companies and major rig contractors to utilize advanced technologies to further optimize the operation and reduce the operating cost.

In the oil and gas drilling industry, modern rigs are already equipped with tens of sensors to collect vast types of data. This data is then fed into software that employs artificial intelligent (AI) and machine learning algorithms to translate the raw data into information that can be used to derive knowledge. The analysis of such data was shown to be very successful in reducing the invisible lost time (ILT) and increasing the operational performance. The key building block of such analysis is the classification of the rig operation at micro-scale, i.e., the identification of the rig state.

This presentation will strive to give an overview of the key components to build a fully automated system to identify rig states and provide rig operations performance key performance indicators (KPIs). Starting with the data requirement, feature engineering, machine learning, and how the sensor’s noise can be reduced in real-time. It will also provide information on drilling operation’s specific challenges (such as KPI validation) and how it can be addressed. Finally, we will discuss lessons learned of running such a system, and how such an effort can establish the foundation of advanced data science driven solutions.

This webinar is categorized under the Data Science and Engineering Analytics discipline. 

All content contained within this webinar is copyrighted by Dr. Majed Alzahrani and its use and/or reproduction outside the portal requires express permission from Dr. Majed Alzahrani.

Dr. Majed Alzahrani

Drilling Data Scientist, Saudi Aramco

Dr. Majed Alzahrani holds a PhD in computer science in the fields of machine learning and artificial intelligence from King Abdullah University of Science and Technology in Saudi Arabia (KAUST). Majed is working for Saudi Aramco Drilling Systems for the last 20 years during which he has been the technical project manager of key strategic projects and solutions to support drilling engineers. Dr. Majed played a major and integral role in the development and delivery of many systems that introduced major business impact and led to optimizing and improving the day-to-day activities in Aramco Drilling and Workover community.

SPE Webinars are FREE to members courtesy of the

image

Key:

Complete
Failed
Available
Locked
Webinar
04/17/2020 at 9:30 AM (EDT)   |  90 minutes
04/17/2020 at 9:30 AM (EDT)   |  90 minutes
Survey
20 Questions
Certificate
0.15 CEU/1.5 PDH credits  |  Certificate available
0.15 CEU/1.5 PDH credits  |  Certificate available