Prepocessing and Analytical Results of the Tidal Gravity Observations Recorde…

Edisi

-

ISBN/ISSN

-

Deskripsi Fisik

12 hlm. illus.

Judul Seri

-

No. Panggil

526.1 CHE p

EQGraphNet: Advancing single-station earthquake magnitude estimation via deep…

Magnitude estimation is a critical task in seismology, and conventional methods usually require dense seismic station arrays to provide data with sufficient spatiotemporal distribution. In this con…

Enhanced permeability prediction in porous media using particle swarm optimiz…

Accurately and efficiently predicting the permeability of porous media is essential for addressing a wide range of hydrogeological issues. However, the complexity of porous media often limits the e…

ResGraphNet: GraphSAGE with embedded residual module for prediction of global…

Data-driven prediction of time series is significant in many scientific research fields such as global climate change and weather forecast. For global monthly mean temperature series, considering t…

High resolution pre-stack seismic inversion using few-shot learning

We propose to use a Few-Shot Learning (FSL) method for the pre-stack seismic inversion problem in obtaining a high resolution reservoir model from recorded seismic data. Recently, artificial neural…

A study on geological structure prediction based on random forest method

The Xingmeng orogenic belt is located in the eastern section of the Central Asian orogenic belt, which is one of the key areas to study the formation and evolution of the Central Asian orogenic bel…

Near-surface velocity inversion from Rayleigh wave dispersion curves based on…

The utilization of urban underground space in a smart city requires an accurate understanding of the underground structure. As an effective technique, Rayleigh wave exploration can accurately obtai…

Data-driven approaches for time series prediction of daily production in the …

The Sulige tight gas field is presently the largest gas field in China. Owing to the ultralow permeability and strong heterogeneity of the reservoirs in Sulige, the number of production wells has e…

Seismic labeled data expansion using variational autoencoders

Supervised machine learning algorithms have been widely used in seismic exploration processing, but the lack of labeled examples complicates its application. Therefore, we propose a seismic labeled…

X-ray Micro-CT based characterization of rock cuttings with deep learning

Rock cuttings from destructive boreholes are a common and cheaper source of drilling materials that can be used to determine underground geology compared to rock core samples. Classifying manually …

Streamlining geoscience data analysis with an LLM-driven workflow

Large Language Models (LLMs) have made significant advancements in natural language processing and human-like response generation. However, training and fine-tuning an LLM to fit the strict require…

Geological object recognition in legacy maps through data augmentation and tr…

Maps are crucial tools in geosciences, providing detailed representations of the spatial distribution and relationships among geological features. Accurate recognition and classification of geologi…

DIFFUSUP: A graphical user interface (GUI) software for diffusion modeling

Advancements in high-resolution in-situ analyses have led to the extensive use of mineral diffusion zonings in determining petrologic and orogenic rates. The diffusion simulation, especially in mul…

A novel few-shot learning framework for rock images dually driven by data and…

In the field of geosciences, the integration of artificial intelligence is transitioning from perceptual intelligence to cognitive intelligence. The simultaneous utilization of knowledge and data i…

Super-resolution in thin section of lacustrine shale reservoirs and its appli…

Lacustrine shale reservoirs present intricate attributes such as the prevalence of lamination, rapid sedimentary phase transitions, and pronounced heterogeneity. These factors introduce substantial…

Geoscience language models and their intrinsic evaluation

Geoscientists use observations and descriptions of the rock record to study the origins and history of our planet, which has resulted in a vast volume of scientific literature. Recent progress in n…

Great SCO2T! Rapid tool for carbon sequestration science, engineering, and ec…

CO2 capture and storage (CCS) technology is likely to be widely deployed in the coming decades in response to major climate and economics drivers: CCS is part of every clean energy pathway that lim…

Performance analysis of ultra-wideband positioning for measuring tree positio…

Accurate individual tree locations enable efficient forest inventory management and automation, support precise forest surveys, management decisions and future individual-tree harvesting plans. In …

Automatic labelling for semantic segmentation of VHR satellite images: Applic…

The application of deep learning methods to remote sensing data has produced good results in recent studies. A promising application area is automatic land cover classification (semantic segmentati…

Advances in data, methods, models and their applications in geoscience

Edisi

-

ISBN/ISSN

978-953-307-737-6

Deskripsi Fisik

vi, 336 hlm. : illus.

Judul Seri

-

No. Panggil

550 Don A