A Symbolic Tree Model for Oil and Gas Production Prediction Using Time-Series Production Data

Author(s):  
Bingjie Wei ◽  
Helen Pinto ◽  
Xin Wang
2021 ◽  
Author(s):  
Aditya Kotiyal ◽  
Guru Prasad Nagaraj ◽  
Lester Tugung Michael

Abstract Digital oilfield applications have been implemented in numerous operating companies to streamline processes and automate workflows to optimize oil and gas production in real-time. These applications are mostly deployed using traditional on-premises systems; where maintenance, accessibility and scalability serves as a major bottleneck for an efficient outcome. In addition to this challenge, the sector still faces limitations in data integration from disparate data sources, liberation of consolidated data for consumption and cross domain workflow orchestration of that data. The dimensional change brought by digital transformation strategies has paved a path for the Cloud- based solutions, which have recently gained momentum in the oil and gas industry pertaining to their wider accessibility, simpler customization, greater system stability and scalability to support larger amount of data in a performant way. To address the challenges mentioned earlier, we have embarked on a journey with Production Data Foundation which brings together production and equipment data from across an organization. In this paper, we will highlight how Production Data Foundation, hosted on the cloud, provides the underlying infrastructure, services, interfaces required to support and unify production data ingestion, workflow orchestration, and through the alignment of the common domain and digital concepts, improve collaboration between people in distinct roles, such as production engineers, reservoir engineers, drilling engineers, deployment engineers, software developers, data scientists, architects, and subject matter experts (SME) working with production operations products and solutions.


2009 ◽  
Vol 41 (5) ◽  
pp. 2474-2483 ◽  
Author(s):  
Arif A. Suleymanov ◽  
Askar A. Abbasov ◽  
Aydin J. Ismaylov

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