Search Results - "Bajolvand, Mahdi"

Developing a New Model for Drilling Rate of Penetration Prediction Using Convolutional Neural Network by Matinkia, Morteza, Sheykhinasab, Amirhossein, Shojaei, Soroush, Vojdani Tazeh Kand, Ali, Elmi, Arad, Bajolvand, Mahdi, Mehrad, Mohammad

“…Before adjustable parameters of drilling can be optimized, it is necessary to have a high-accuracy model for predicting the rate of penetration (ROP), which…”
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Modeling the effect of the striker geometry on the wave propagation pattern in the Split-Hopkinson pressure bar test using the discrete element method by Majid Nikkhah, Mahdi Bajolvand

“…Split Hopkinson Pressure Bars (SHPB) test is widely used among the various methods for investigating the dynamic behavior of rocks at high strain rates…”
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Predicting uniaxial compressive strength from drilling variables aided by hybrid machine learning by Davoodi, Shadfar, Mehrad, Mohammad, Wood, David A., Rukavishnikov, Valeriy S., Bajolvand, Mahdi

“…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…”
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Developing a new rigorous drilling rate prediction model using a machine learning technique by Mehrad, Mohammad, Bajolvand, Mahdi, Ramezanzadeh, Ahmad, Neycharan, Jalil Ghavidel

“…Drilling rate of penetration (ROP) prediction is an enormously important step to optimize drilling controllable parameters. Therefore, numerous efforts have…”
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Optimization of controllable drilling parameters using a novel geomechanics-based workflow by Bajolvand, Mahdi, Ramezanzadeh, Ahmad, Mehrad, Mohammad, Roohi, Abbas

“…Drilling optimization is one of the most important management and engineering objectives in the upstream oil and gas industry, which has been the subject of…”
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Estimating shear wave velocity in carbonate reservoirs from petrophysical logs using intelligent algorithms by Mehrad, Mohammad, Ramezanzadeh, Ahmad, Bajolvand, Mahdi, Reza Hajsaeedi, Mohammad

“…Shear-wave velocity (Vs) is a key petrophysical data for a wide spectrum of applications in the upstream oil industry. In many wells, however, the…”
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A novel approach to pore pressure modeling based on conventional well logs using convolutional neural network by Matinkia, Morteza, Amraeiniya, Ali, Behboud, Mohammad Mohammadi, Mehrad, Mohammad, Bajolvand, Mahdi, Gandomgoun, Mohammad Hossein, Gandomgoun, Mehdi

“…Accurate prediction of pore pressure (PP) is among the most critical concerns to the design of drilling operation because of the remarkable role of this…”
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