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The AAPG/Datapages Combined Publications Database
Showing 624 Results. Searched 200,691 documents.
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user1
Search and Discovery.com
... by utilizing Convolutional Neural Networks(CNNs) and Wavelet-based approaches. This ensures a clear interpretation of subsurface characteristics for a better...
Unknown
Auto-identification and Real-time Warning Method of Multiple Type Events During Multistage Horizontal Well Fracturing
Mingze Zhao, Yue Li, Yuyang Liu, Bin Yuan, Siwei Meng, Wei Zhang, He Liu
Unconventional Resources Technology Conference (URTEC)
... identification and real-time warning method of multiple types of events during multi-stage fracturing. A new intelligent identification model is developed...
2023
Fluids characterization using cuttings extracts analyzed by gel permeation chromatography
G. Eric Michael, Julian Moore, Lloyd Jones, Alexandra Cely, Gulnar Yerkinkyzy, Tao Yang
International Meeting for Applied Geoscience and Energy (IMAGE)
... To build models with the ability to use cuttings extracted oil, model prediction is performed on topped dead oils and oil extracted from core. Figure 2...
2024
Abstract: Innovative QCs for More Effective 4D Processing; #90187 (2014)
Cyril Saint Andre, Benoit Blanco, Christian Hubans, and Benoit Paternoster
Search and Discovery.com
... problem in the framework of the 1D convolutional model. This attribute and the following developments were initially detailed by Cantillo (2012) [3...
2014
Abstracts: Revisiting Homomorphic Wavelet Estimation and Phase Unwrapping; #90173 (2015)
Roberto H. Herrera and Mirko van der Baan
Search and Discovery.com
.... The convolutional operator is denoted by and η (t ) is the additive noise. In the frequency domain equation (1) can be expressed as: = W ( f ) R( f ) + Ν...
2015
Abstract: Deterministic Marine Deghosting: Tutorial and Recent Advances; #90224 (2015)
Mike J. Perz and Hassan Masoomzadeh
Search and Discovery.com
... violates the convolutional model that forms the cornerstone of the derivation of our deterministic deghosting operator, and would lead to unacceptable...
2015
Improving Resolution and Clarity with Neural Networks; #41911 (2016)
Christopher P. Ross
Search and Discovery.com
... and anisotropic model parameters simultaneously with wave-equation modeling. Well logs may be used as part of the low-frequency initial model building...
2016
A data-feature-policy solution for multiscale geological-geophysical intelligent reservoir characterization
Wenhao Zheng, Fei Tian, Qingyun Di, Jiangyun Zhang, Hui Zhou, Wang Zhang, Zhongxing Wang
International Meeting for Applied Geoscience and Energy (IMAGE)
... on Deep Belief Network, the geological prediction model was established. It was optimized by a double-loop filtering mechanism that selected the parameter...
2022
Artificial Intelligence (AI) Based Personnel Protective Equipment (PPE) Monitoring - Case Study in Rokan Drilling Operation
Freddy Frinly Rizki, Ade Anggi N S, Ari Sukma Negara
Indonesian Petroleum Association
... and in different light conditions. The next step was to use deep learning technology such as Yolov4 and train the model using the PPE datasets...
2022
Artificial intelligence techniques to the interpretation of geophysical measurements
Desmond FitzGerald
Petroleum Exploration Society of Australia (PESA)
... SUMMARY Integration of geology and geophysics thinking requires a common earth model, that accommodates, with errors, all the features from...
2019
Accelerated deep learning-based estimation of wavefront dips and curvatures and their application to 3D prestack data enhancement
Kirill Gadylshin, Ilya Silvestrov, Andrey Bakulin
International Meeting for Applied Geoscience and Energy (IMAGE)
... Attributes Deep Neural Network. It is based on automatic local wavefront attributes estimation using a specially trained convolutional deep neural network...
2022
Predicting Hydrocarbon Production Behavior in Heterogeneous Reservoir Utilizing Deep Learning Models
Fatick Nath, Sarker Asish, Happy R. Debi, Mohammed Omar S Chowdhury, Zackary J. Zamora, Sergio Muñoz
Unconventional Resources Technology Conference (URTEC)
... of their cumbersome processing. To overcome this limitation, a supervised deep neural network (DNN) model is established in this paper to forecast hydrocarbon...
2023
DASF: A high-performance and scalable framework for large seismic datasets
Julio C. Faracco, Otávio O. Napoli, João Seródio, Carlos A. Astudillo, Leandro A. Villas, Edson Borin, Alan Souza, Daniel Miranda, João Paulo Navarro
International Meeting for Applied Geoscience and Energy (IMAGE)
..., the attribute to be calculated, the ML model to be trained or the waiting time in the HPC system’s queues. Finally, once the system finishes...
2024
From Chaos to Caves An Evolution of Seismic Karst Interpretation at the Vorwata Field
Riangguna Eloni, M.R. Husni Sahidu, Ilham Panggeleng, Christopher S. Birt, Ted Manning
Indonesian Petroleum Association
... trend that is missing in the seismic data (perhaps from well logs, or a regional velocity model). Both of these can be prone to error and require...
2016
Reservoir prediction using graph-regularized deep learning
Kaiheng Sang, Nanying Lan, Fanchang Zhang
International Meeting for Applied Geoscience and Energy (IMAGE)
... of these explicit formulas are based on strong approximation to the underground media properties, such as convolution model, Aki-Richard approximate...
2022
Seismic reservoir characterization of the Strawn Group, northern part of the Eastern Shelf, King County, North-Central Texas: Case study
Osareni C. Ogiesoba
International Meeting for Applied Geoscience and Energy (IMAGE)
... > 15 Hz are filtered out. The inversion process is based on the convolutional model expressed as Using the same procedure, I predicted the Vp/Vs...
2023
Improving pre-stack inter-trace variation extraction with a self-supervised learning approach
Yifeng Fei, Xin He, Bangli Zou, Jiandong Liang, Dajun Li
International Meeting for Applied Geoscience and Energy (IMAGE)
.... Notable examples include utilizing a geological and geophysical model-driven convolutional neural network (CNN) for the extraction of elastic parameter...
2024
Deep Learning for Quantitative Hydraulic Fracture Profiling from Fiber Optic Measurements
Weichang Li, Han Lu, Yuchen Jin, Frode Hveding
Unconventional Resources Technology Conference (URTEC)
... to the synced pump data independently; and II) a convolutional LSTM (long short-term memory) sequence learning model maps time segments...
2021
Augmented Data Management for Subsurface CCUS Data Sets
Rhys Blake, Jess B. Kozman, James Lamb, Lorena Pelegrin
Carbon Capture, Utilization and Storage (CCUS)
... workflows for using artificial and convolutional neural networks to find information in legacy documents that can predict physical properties...
2025
Automated fault surfaces extraction from 3D fault imaging volume
Nam Nguyen, Alejandro Jaramillo
International Meeting for Applied Geoscience and Energy (IMAGE)
... be integrated into a geological model for identification of hydrocarbon bearing formations, improving structural trapping definition, and preventing drilling...
2022
Improving Wolfcamp B3 Drilling and Production by Integrating Core, Mud logs, Electrical Logs, Seismic Inversion, Microseismic and Drilling Data
Hongzhuan Ye, Lowell Waite, Robert Meek
Unconventional Resources Technology Conference (URTEC)
... seismic inversion. Methods and Workflow Pre-stack seismic inversion attempts to remove the convolutional effects of the wavelet on the reflectivity...
2015
A Quantitative Application of Seismic Inversion and Multi-Attribute Analysis based on Rock Physics Linear Relationships to identify High Total Organic Carbon Shale - A Case Study from the Perth Basin, Western Australia
Y. Altowairqi, R. Rezaee, B. Evans, M. Urosevic
Unconventional Resources Technology Conference (URTEC)
...-attribute analysis is applied to predict TOC from a model-based inversion and used the AI as external attribute. A total of eight seismic attributes were...
2017
Augmented Intelligence for Geoscience Data in Mature Basins
Jess B. Kozman and Lorena Pelgrin
GCAGS Transactions
... data, such as that encountered in mature basins with decades of archived well reports. We have deployed a pre-trained convolutional neural network...
2025
Abstract: Correlation of P-P and P-S Data in Yinggehai Basin, South China Sea; #90171 (2013)
Jinfeng Ma, Le Gao, and Igor Morozov
Search and Discovery.com
... for making P-S offset synthetic seismograms using convolutional model was proposed by Stewart (1991). In the weak contrast of the boundary, P-S wave...
2013
Deep Convolutional Neural Networks for Seismic Salt-Body Delineation; #70360 (2018)
Haibin Di, Zhen Wang, Ghassan AlRegib
Search and Discovery.com
...Deep Convolutional Neural Networks for Seismic Salt-Body Delineation; #70360 (2018) Haibin Di, Zhen Wang, Ghassan AlRegib Deep Convolutional Neural...
2018