Results 41 to 50 of about 2,839,750 (318)

A New Method of Lithology Classification Based on Convolutional Neural Network Algorithm by Utilizing Drilling String Vibration Data

Energies, 2020
Formation lithology identification is of great importance for reservoir characterization and petroleum exploration. Previous methods are based on cutting logging and well-logging data and have a significant time lag.
Gang Chen, Mian Chen, Guobin Hong, Yunhu Lu, Bo Zhou, Yanfang Gao   +5 more
doaj   +1 more source

Evaluation of mineralogy per geological layers by Approximate Bayesian Computation

, 2019
We propose a new methodology to perform mineralogic inversion from wellbore logs based on a Bayesian linear regression model. Our method essentially relies on three steps.
Bruned, Vianney, Cleynen, Alice, Mas, André, Wlodarczyck, Sylvain   +3 more
core   +3 more sources

Enhanced machine learning tree classifiers for lithology identification using Bayesian optimization

Applied Computing and Geosciences, 2022
Lithology identification is a fundamental activity in oil and gas exploration. The application of artificial intelligence (AI) is currently being adopted as a state-of-the-art means of automating lithology identification.
Solomon Asante-Okyere, Chuanbo Shen, Harrison Osei   +2 more
doaj   +1 more source

Coherence methods in mapping AVO anomalies and predicting P-wave and S-wave impedances [PDF]

, 2005
Filters for migrated offset substacks are designed by partial coherence analysis to predict ‘normal’ amplitude variation with offset (AVO) in an anomaly free area.
Barnola, A.S., White, Roy E.
core   +1 more source

A hybrid model for mapping simplified seismic response via a GIS-metamodel approach [PDF]

, 2014
In earthquake-prone areas, site seismic response due to lithostratigraphic sequence plays a key role in seismic hazard assessment. A hybrid model, consisting of GIS and metamodel (model of model) procedures, was introduced aimed at estimating the 1-D ...
Bonito, L., Grelle, G., Guadagno, F. M., Guerriero, L., Revellino, P.   +4 more
core   +1 more source

Feature fusion of single and orthogonal polarized rock images for intelligent lithology identification

AI in Civil Engineering
This paper presents an intelligent lithology identification method that utilizes the feature fusion of single polarized and orthogonal polarized rock images.
Wen Ma, Tao Han, Zhenhao Xu, Peng Lin
semanticscholar   +1 more source

Identification of Rock Properties of Rock Wall Cut by Roadheader Based on PSO-VMD-LSSVM

Frontiers in Earth Science, 2022
The problem of low digging efficiency and mining imbalance due to outdated digging technology and low degree of equipment intelligence has long existed in coal mine roadway excavation work.
Pengfei Qi, Jucai Chang, Xiao Chen, Tuo Wang, Mengyun Wu   +4 more
doaj   +1 more source

Lithology Identification Method and Application Based on Generative Adversarial Neural Network

Cejing jishu
Lithology identification is the basis of reservoir evaluation and the key to reservoir parameter calculation and reservoir evaluation and development.
YIN Qiong
doaj   +1 more source

Flora algal de la cuenca del río Guadalquivir: Su valor en la determinación de la ecorregionalización de la cuenca [PDF]

, 2018
In compliance with the Water Framework Directive of the European Union, we needed to diagnose the ecologic quality of the different sections of the rivers of the Guadalquivir basin. In order to establish a regional classification of the water bodies by a
Casco, Maria Adela, Fernández, María R., Martín, Gonzalo, Reyes, Isabel, Sala, Silvia Estela, Toja, Julia   +5 more
core   +2 more sources

A lithology identification method while drilling based on KAN neural network

Meitan xuebao
Lithology identification while drilling is an important geological guarantee means for transparent detection of coal mine geology. The traditional lithology identification method mainly relies on manual judgment, which relies on the accumulation of ...
Bo WANG, Liujun XIE, Hongyun CHEN, Linfeng ZENG, Sihongren SHEN, Naichuan WANG, Dewei ZHANG   +6 more
doaj   +1 more source