Predicting uniaxial compressive strength from drilling variables aided by hybrid machine learning
Awareness of uniaxial compressive strength (UCS) as a key rock formation parameter for the
design and development of gas and oil field plays. It plays an essential role in the selection …
design and development of gas and oil field plays. It plays an essential role in the selection …
Real-time prediction of formation pressure gradient while drilling
Accurate real-time pore pressure prediction is crucial especially in drilling operations
technically and economically. Its prediction will save costs, time and even the right decisions …
technically and economically. Its prediction will save costs, time and even the right decisions …
Prediction model based on an artificial neural network for rock porosity
H Gamal, S Elkatatny - Arabian Journal for Science and Engineering, 2022 - Springer
The rock porosity is considered a key petrophysical property for the rock due to its great
impact on the hydrocarbon reserve estimation and petroleum economics. The conventional …
impact on the hydrocarbon reserve estimation and petroleum economics. The conventional …
Detecting downhole vibrations through drilling horizontal sections: machine learning study
During the drilling operations and because of the harsh downhole drilling environment, the
drill string suffered from downhole vibrations that affect the drilling operation and equipment …
drill string suffered from downhole vibrations that affect the drilling operation and equipment …
Pore pressure prediction by empirical and machine learning methods using conventional and drilling logs in carbonate rocks
MR Delavar, A Ramezanzadeh - Rock Mechanics and Rock Engineering, 2023 - Springer
Precise pore pressure estimation has high significance in terms of drilling and development
operations. Regarding its necessity, empirical and intelligence methods have been …
operations. Regarding its necessity, empirical and intelligence methods have been …
A novel data-driven model for real-time prediction of static Young's modulus applying mud-logging data
Effective drilling planning relies on understanding the rock mechanical properties, typically
estimated from petrophysical data. Real-time estimation of these properties, especially static …
estimated from petrophysical data. Real-time estimation of these properties, especially static …
Intelligent model for predicting downhole vibrations using surface drilling data during horizontal drilling
R Saadeldin, H Gamal… - Journal of …, 2022 - asmedigitalcollection.asme.org
Drillstring vibration is a major concern during drilling wellbore, and it can be split into three
types: axial, torsional, and lateral. Many problems associate with the high drillstring …
types: axial, torsional, and lateral. Many problems associate with the high drillstring …
Estimation of geomechanical rock characteristics from specific energy data using combination of wavelet transform with ANFIS-PSO algorithm
M Mohammadi Behboud, A Ramezanzadeh… - Journal of Petroleum …, 2023 - Springer
The geomechanical characteristics of a drill formation are uncontrollable factors that are
crucial to determining the optimal controllable parameters for a drilling operation. In the …
crucial to determining the optimal controllable parameters for a drilling operation. In the …
Machine Learning Solution for Predicting Vibrations while Drilling the Curve Section
The downhole vibration is one of the most crucial factors that affect downhole equipment
performance and failure, besides wellbore instability. Downhole tool failure, hole problems …
performance and failure, besides wellbore instability. Downhole tool failure, hole problems …
Machine Learning Model for Monitoring Rheological Properties of Synthetic Oil-Based Mud
The drilling fluid rheology is a critical parameter during the oil and gas drilling operation to
achieve optimum drilling performance without nonproductive time or extra remedial …
achieve optimum drilling performance without nonproductive time or extra remedial …