A systematic review of data science and machine learning applications to the oil and gas industry
This study offered a detailed review of data sciences and machine learning (ML) roles in
different petroleum engineering and geosciences segments such as petroleum exploration …
different petroleum engineering and geosciences segments such as petroleum exploration …
Unconfined compressive strength (UCS) prediction in real-time while drilling using artificial intelligence tools
Unconfined compressive strength (UCS) is a major mechanical parameter of the rock which
has an essential role in develo** geomechanical models. It can be estimated directly by …
has an essential role in develo** geomechanical models. It can be estimated directly by …
Rock strength prediction in real-time while drilling employing random forest and functional network techniques
The rock unconfined compressive strength (UCS) is one of the key parameters for
geomechanical and reservoir modeling in the petroleum industry. Obtaining the UCS by …
geomechanical and reservoir modeling in the petroleum industry. Obtaining the UCS by …
Machine learning approach to model rock strength: prediction and variable selection with aid of log data
Comprehensive knowledge and analysis of in situ rock strength and geo-mechanical
characteristics of rocks are crucial in hydrocarbon and mineral exploration stage to …
characteristics of rocks are crucial in hydrocarbon and mineral exploration stage to …
Real-time prediction of rheological properties of invert emulsion mud using adaptive neuro-fuzzy inference system
Tracking the rheological properties of the drilling fluid is a key factor for the success of the
drilling operation. The main objective of this paper is to relate the most frequent mud …
drilling operation. The main objective of this paper is to relate the most frequent mud …
Predictive models and feature ranking in reservoir geomechanics: A critical review and research guidelines
MI Miah - Journal of Natural Gas Science and Engineering, 2020 - Elsevier
Comprehensive investigation and accurate models of geo-mechanical properties are crucial
to maintain wellbore stability and optimize the hydraulic fracturing process. This review …
to maintain wellbore stability and optimize the hydraulic fracturing process. This review …
Dynamic risk modeling of complex hydrocarbon production systems
This study presents a dynamic risk modeling strategy for a hydrocarbon sub-surface
production system under a gas lift mechanism. A data-driven probabilistic methodology is …
production system under a gas lift mechanism. A data-driven probabilistic methodology is …
Intelligent prediction for rock porosity while drilling complex lithology in real time
Rock porosity is an important parameter for the formation evaluation, reservoir modeling,
and petroleum reserve estimation. The conventional methods for determining the rock …
and petroleum reserve estimation. The conventional methods for determining the rock …
New correlations for better monitoring the all-oil mud rheology by employing artificial neural networks
The rheological properties of the drilling fluid are crucial to the success of the drilling project.
The traditional mud experiments normally performed by the mud engineers provide …
The traditional mud experiments normally performed by the mud engineers provide …
Machine learning models for equivalent circulating density prediction from drilling data
Equivalent circulating density (ECD) is considered a critical parameter during the drilling
operation, as it could lead to severe problems related to the well control such as fracturing …
operation, as it could lead to severe problems related to the well control such as fracturing …