Applications of AI in oil and gas projects towards sustainable development: a systematic literature review
Oil and gas construction projects are critical for meeting global demand for fossil fuels, but
they also present unique risks and challenges that require innovative construction …
they also present unique risks and challenges that require innovative construction …
Field data analysis and risk assessment of gas kick during industrial deepwater drilling process based on supervised learning algorithm
During industrial offshore deep-water drilling process, gas kick event occurs frequently due
to extremely narrow Mud Weight (MW) window (minimum 0.01 sg) and negligible safety …
to extremely narrow Mud Weight (MW) window (minimum 0.01 sg) and negligible safety …
Machine learning for deepwater drilling: Gas-kick-alarm Classification using pilot-scale rig data with combined surface-riser-downhole monitoring
Gas kicks occur frequently in deepwater drilling because of the extremely narrow mud-
weight window [minimum 0.01 specific gravity (sg)]. The traditional kick-detection method …
weight window [minimum 0.01 specific gravity (sg)]. The traditional kick-detection method …
Downhole quantitative evaluation of gas kick during deepwater drilling with deep learning using pilot-scale rig data
Gas kick occurs frequently during deep-water drilling operations caused by the lack of safe
margin between pore pressure and leakage pressure. The existing research is limited to gas …
margin between pore pressure and leakage pressure. The existing research is limited to gas …
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 …
Application of machine learning to quantification of mineral composition on gas hydrate-bearing sediments, Ulleung Basin, Korea
Mineral quantification is essential to evaluate gas hydrate (GH) resources because the
mineral composition is closely related to the origin of sediment, the reservoir properties, and …
mineral composition is closely related to the origin of sediment, the reservoir properties, and …
Variable seismic waveforms representation: Weak-supervised learning based seismic horizon picking
Seismic horizon picking via deep learning models have been advanced rapidly and proven
popular. However, the prediction result is highly depended on the quality of the train set and …
popular. However, the prediction result is highly depended on the quality of the train set and …
A generalized machine learning workflow to visualize mechanical discontinuity
Accurate detection and mapping of mechanical discontinuity in materials has widespread
industrial and research applications. We developed a generalized machine-learning …
industrial and research applications. We developed a generalized machine-learning …
A novel method for fracture pressure prediction in shallow formation during deep-water drilling
J Yang, S Liu, H Wang, X Zhou… - Journal of …, 2022 - asmedigitalcollection.asme.org
Large numbers of deep-water drilling practices have shown that more than 60% of deep-
water wells have complex leak-off during the drilling process, which poses great difficulties …
water wells have complex leak-off during the drilling process, which poses great difficulties …
Lithology spatial distribution prediction based on recurrent neural network with kriging technology
L Zeng, W Ren, L Shan, F Huo, F Meng - Journal of Petroleum Science and …, 2022 - Elsevier
Deep learning technology can fit the non-linear and non-stationary characteristics in
geological statistics. It has become an important tool for predictive modeling. However, the …
geological statistics. It has become an important tool for predictive modeling. However, the …