Artificial intelligence and machine learning approaches in composting process: a review
Studies on develo** strategies to predict the stability and performance of the composting
process have increased in recent years. Machine learning (ML) has focused on process …
process have increased in recent years. Machine learning (ML) has focused on process …
Can artificial intelligence accelerate fluid mechanics research?
The significant growth of artificial intelligence (AI) methods in machine learning (ML) and
deep learning (DL) has opened opportunities for fluid dynamics and its applications in …
deep learning (DL) has opened opportunities for fluid dynamics and its applications in …
Recent Advances in Carbon Dioxide Sequestration in Deep Unmineable Coal Seams Using CO2-ECBM Technology: Experimental Studies, Simulation, and Field …
GC Mwakipunda, Y Wang, MM Mgimba… - Energy & …, 2023 - ACS Publications
CO2-enhanced coalbed methane (CO2-ECBM) technology helps to store CO2 while
producing a clean source of energy (CH4) through the sorption process. This technique can …
producing a clean source of energy (CH4) through the sorption process. This technique can …
Predicting rate of penetration in ultra-deep wells based on deep learning method
C Peng, J Pang, J Fu, Q Cao, J Zhang, Q Li… - Arabian Journal for …, 2023 - Springer
The accurate prediction of the rate of penetration (ROP) is crucial for optimizing drilling
parameters and enhancing drilling efficiency in ultra-deep wells. However, this task is …
parameters and enhancing drilling efficiency in ultra-deep wells. However, this task is …
Real-time prediction of logging parameters during the drilling process using an attention-based Seq2Seq model
In recent years, there has been a notable upsurge within the drilling industry regarding the
construction of machine learning models that leverage logging parameters to augment …
construction of machine learning models that leverage logging parameters to augment …
Advancements in machine learning techniques for coal and gas outburst prediction in underground mines
Coal and gas outbursts are a major cause of fatalities in underground coal mines and pose
a threat to coal power generation worldwide. Among the current mitigation efforts include …
a threat to coal power generation worldwide. Among the current mitigation efforts include …
Real-time and multi-objective optimization of rate-of-penetration using machine learning methods
C Zhang, X Song, Z Liu, B Ma, Z Lv, Y Su, G Li… - Geoenergy Science and …, 2023 - Elsevier
Rate of penetration and mechanical specific energy are two widely used objectives when
optimizing the drilling process, yet a simultaneous optimization of both is still a challenge …
optimizing the drilling process, yet a simultaneous optimization of both is still a challenge …
[HTML][HTML] Ore/waste identification in underground mining through geochemical calibration of drilling data using machine learning techniques
Chemical X-ray fluorescence (XRF) analyses of drill cuttings and measurement-while-
drilling (MWD) records were jointly collected in two production levels with different …
drilling (MWD) records were jointly collected in two production levels with different …
New insights into fracture porosity estimations using machine learning and advanced logging tools
Fracture porosity is crucial for storage and production efficiency in fractured tight reservoirs.
Geophysical image logs using resistivity measurements have traditionally been used for …
Geophysical image logs using resistivity measurements have traditionally been used for …
[HTML][HTML] Artificial general intelligence for the upstream geoenergy industry: a review
Abstract Artificial General Intelligence (AGI) is set to profoundly impact the traditional
upstream geoenergy industry (ie, oil and gas industry) by introducing unprecedented …
upstream geoenergy industry (ie, oil and gas industry) by introducing unprecedented …