A machine learning (kNN) approach to predicting global seafloor total organic carbon
Seafloor properties, including total organic carbon (TOC), are sparsely measured on a
global scale, and interpolation (prediction) techniques are often used as a proxy for …
global scale, and interpolation (prediction) techniques are often used as a proxy for …
Sedimentary parameters control the sulfur isotope composition of marine pyrite
Reconstructions of coupled carbon, oxygen, and sulfur cycles rely heavily on sedimentary
pyrite sulfur isotope compositions (δ34Spyr). With a model of sediment diagenesis, paired …
pyrite sulfur isotope compositions (δ34Spyr). With a model of sediment diagenesis, paired …
Transfer efficiency of organic carbon in marine sediments
Quantifying the organic carbon (OC) sink in marine sediments is crucial for assessing how
the marine carbon cycle regulates Earth's climate. However, burial efficiency (BE)–the …
the marine carbon cycle regulates Earth's climate. However, burial efficiency (BE)–the …
Deriving nickel (Ni (II)) and chromium (Cr (III)) based environmentally safe olivine guidelines for coastal enhanced silicate weathering
Enhanced silicate weathering (ESW) by spreading finely ground silicate rock along the
coastal zone to remove atmospheric carbon dioxide (CO2) is a proposed climate change …
coastal zone to remove atmospheric carbon dioxide (CO2) is a proposed climate change …
Predicting global marine sediment density using the random forest regressor machine learning algorithm
Marine sediment density is of vital importance due to its influence on many geoacoustic and
nongeoacoustic parameters, including but not limited to: acoustic impedance, sediment …
nongeoacoustic parameters, including but not limited to: acoustic impedance, sediment …
An improved method for lithology identification based on a hidden Markov model and random forests
Subsurface petrophysical properties usually differ between different reservoirs, which affects
lithology identification, especially for unconventional reservoirs. Thus, the lithology …
lithology identification, especially for unconventional reservoirs. Thus, the lithology …
Identifying channel sand-body from multiple seismic attributes with an improved random forest algorithm
Abstract Machine learning provides numerous data-driven tools for automatic pattern
recognition. Even though various algorithms such as neural networks and support vector …
recognition. Even though various algorithms such as neural networks and support vector …
A deep CNN-LSTM model for predicting interface depth from gravity data over thrust and fold belts of North East India
S Maiti, RK Chiluvuru - Journal of Asian Earth Sciences, 2024 - Elsevier
Geological interface depth modeling from the gravity field data is crucial for the exploration
of oil and gas, mapping of sediment-basement interfaces and many other geological …
of oil and gas, mapping of sediment-basement interfaces and many other geological …
The contribution of water radiolysis to marine sedimentary life
JF Sauvage, A Flinders, AJ Spivack, R Pockalny… - Nature …, 2021 - nature.com
Water radiolysis continuously produces H2 and oxidized chemicals in wet sediment and
rock. Radiolytic H2 has been identified as the primary electron donor (food) for …
rock. Radiolytic H2 has been identified as the primary electron donor (food) for …
Lithium isotopic constraints on the evolution of continental clay mineral factory and marine oxygenation in the earliest Paleozoic Era
The evolution of oxygen cycles on Earth's surface has been regulated by the balance
between molecular oxygen production and consumption. The Neoproterozoic–Paleozoic …
between molecular oxygen production and consumption. The Neoproterozoic–Paleozoic …