Blar i Vitenskapelige publikasjoner (TN-IEP) på forfatter "Sui, Dan"
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Automated Characterization of Non-Newtonian Fluids Using Laboratory Setup
Sui, Dan; Vidaur, Juan Carlos Martinez (Peer reviewed; Journal article, 2020-07)The automation towards drilling fluid properties’ measurement has been pursued in the recent years in order to increase drilling efficiency with less human intervention. Adequately monitoring and adjusting density and ... -
Data-Driven Approaches Tests on A Laboratory Drilling System
Løken, Erik Andreas; Løkkevik, Jens; Sui, Dan (Peer reviewed; Journal article, 2020)In recent years, considerable resources have been invested to exploit vast amounts of data that get collected during exploration, drilling and production of oil and gas. Data-related digital technologies potentially become ... -
Data-driven sensitivity analysis of complex machine learning models: A case study of directional drilling
Tunkiel, Andrzej Tadeusz; Sui, Dan; Wiktorski, Tomasz (Peer reviewed; Journal article, 2020-12)Classical sensitivity analysis of machine learning regression models is a topic sparse in literature. Most of data-driven models are complex black boxes with limited potential of extracting mathematical understanding of ... -
Downhole Temperature Modeling for Non-Newtonian Fluids in ERD Wells
Sui, Dan; Langåker, Vebjørn (Journal article; Peer reviewed, 2018)Having precise information of fluids' temperatures is a critical process during planning of drilling operations, especially for extended reach drilling (ERD). The objective of this paper is to develop an accurate temperature ... -
Drilling data quality improvement and information extraction with case studies
Geekiyanage, Suranga C. H.; Tunkiel, Andrzej Tadeusz; Sui, Dan (Peer reviewed; Journal article, 2020)Data analytics is a process of data acquiring, transforming, interpreting, modelling, displaying and storing data with an aim of extracting useful information, so that decision-making, actions executing, events detecting ... -
Impact of data pre-processing techniques on recurrent neural network performance in context of real-time drilling logs in an automated prediction framework
Tunkiel, Andrzej Tadeusz; Sui, Dan; Wiktorski, Tomasz (Peer reviewed; Journal article, 2021-11)Recurrent neural networks (RNN), which are able to capture temporal natures of a signal, are becoming more common in machine learning applied to petroleum engineering, particularly drilling. With this technology come ... -
Reference Dataset for Rate of Penetration Benchmarking
Tunkiel, Andrzej Tadeusz; Sui, Dan; Wiktorski, Tomasz (Peer reviewed; Journal article, 2020-10)In recent years, there were multiple papers published related to rate of penetration prediction using machine learning vastly outperforming analytical methods. There are models proposed reportedly achieving R2 values as ... -
Review and investigations on geothermal energy extraction from abandoned petroleum wells
Sui, Dan; Wiktorski, Ekaterina; Røksland, Marius; Basmoen, Tommy A. (Journal article; Peer reviewed, 2018-08)Geothermal energy is a sustainable and renewable energy source, which can be used in electricity production, space heating/cooling, and other industrial applications. In the recent years, it has been gathering more and ... -
Study on separation factor models for well anti-collision analysis
Madeira, Rafael; Sui, Dan (Peer reviewed; Journal article, 2021-07)Anti-collision analysis has been becoming even more important in the past few years with the increasing amount of wells drilled in highly congested fields. The separation factor (SF) is a critical safety parameter to avoid ...