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 …
An insight into the prediction of scale precipitation in harsh conditions using different machine learning algorithms
Scale precipitation in petroleum equipment is known as an important problem that causes
damages in injection and production wells. Scale precipitation causes equipment corrosion …
damages in injection and production wells. Scale precipitation causes equipment corrosion …
[HTML][HTML] Hydrate Blockage in Subsea Oil/Gas Pipelines: Characterization, Detection, and Engineering Solutions
Y Meng, B Han, J Wang, J Chu, H Yao, J Zhao… - Engineering, 2024 - Elsevier
With the development of offshore oil and gas resources, hydrates pose a significant
challenge to flow assurance. Hydrates can form, accumulate, and settle in pipelines, causing …
challenge to flow assurance. Hydrates can form, accumulate, and settle in pipelines, causing …
Enabling site-specific well leakage risk estimation during geologic carbon sequestration using a modular deep-learning-based wellbore leakage model
Amid growing climate concerns, geologic carbon sequestration (GCS) is a promising
technology for mitigating net carbon emissions by storing CO 2 in reservoirs. Oil and gas …
technology for mitigating net carbon emissions by storing CO 2 in reservoirs. Oil and gas …
Machine learning models for fast selection of amino acids as green thermodynamic inhibitors for natural gas hydrate
Natural amino acids are non-toxic thermodynamic hydrate inhibitors without negative
environmental impact, but it is difficult to accurately select the appropriate amino acid as a …
environmental impact, but it is difficult to accurately select the appropriate amino acid as a …
[HTML][HTML] Synergistic enhancement of productivity prediction using machine learning and integrated data from six shale basins of the USA
This study aimed to validate the synergistic enhancement of the machine learning model
random forest (RF) to predict the oil and gas estimated ultimate recovery (EUR) by …
random forest (RF) to predict the oil and gas estimated ultimate recovery (EUR) by …
Toward Field Soil Surveys: Identifying and Delineating Soil Diagnostic Horizons Based on Deep Learning and RGB Image
R Yang, J Chen, J Wang, S Liu - Agronomy, 2022 - mdpi.com
The diagnostic horizon in a soil is reflective of the environment in which it developed and the
inherent characteristics of the material, therefore quantitative approaches to horizon …
inherent characteristics of the material, therefore quantitative approaches to horizon …
Geochemical Biodegraded Oil Classification Using a Machine Learning Approach
S Bispo-Silva, CJF de Oliveira, G de Alemar Barberes - Geosciences, 2023 - mdpi.com
Chromatographic oil analysis is an important step for the identification of biodegraded
petroleum via peak visualization and interpretation of phenomena that explain the oil …
petroleum via peak visualization and interpretation of phenomena that explain the oil …
[HTML][HTML] Improved prediction of shale gas productivity in the Marcellus shale using geostatistically generated well-log data and ensemble machine learning
This study proposes the application of geostatistically generated well-log data to predict well
productivity in Marcellus shale reservoirs using ensemble machine learning (ESM). ESM …
productivity in Marcellus shale reservoirs using ensemble machine learning (ESM). ESM …
[HTML][HTML] Spatiotemporal interpretation of three-phase saturation behaviors in gas hydrate formation and dissociation through deep learning modeling
This study provides an interpretation of the three-phase saturation (water, gas, gas hydrate
(GH); SW, SG, S GH) in the GH cores during GH formation and depressurization …
(GH); SW, SG, S GH) in the GH cores during GH formation and depressurization …