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The AAPG/Datapages Combined Publications Database
Showing 622 Results. Searched 200,357 documents.
Deep learning-based 3D microseismic event direct location using simultaneous surface and borehole data: An application to the Utah FORGE site
Yuanyuan Yang, Omar M. Saad, Tariq Alkhalifah
International Meeting for Applied Geoscience and Energy (IMAGE)
... Hydraulic Fracturing Technology Conference and Exhibition, OnePetro. Mesimeri, M., K. L. Pankow, and J. Rutledge, 2021, A frequency domain based...
2024
VSP Guided Reprocessing and Inversion of Surface Seismic Data
R. Gir, Dominique Pajot, Serge Des Ligneris
Southeast Asia Petroleum Exploration Society (SEAPEX)
... seismic data is known as the “convolutional model of the seismogram”. This model states that after proper data processing, the final seismic data has...
1988
Looking for a simplified and generalized training set in ML applications for gravity modelling
Luigi Bianco, Ciro Messina, Maurizio Fedi
International Meeting for Applied Geoscience and Energy (IMAGE)
... be seen as the building blocks of each gravimetric anomaly. Here, we discuss preliminary results obtained with a Convolutional Neural Network (CNN...
2023
A method of relative impedance holography-inversion based on reflection coefficient inversion
Jiangfeng Zheng, Jialin Sun, Zongyu Zhen, Shaoxuan Li
International Meeting for Applied Geoscience and Energy (IMAGE)
...) 𝑤 Where r(t, f) is the time-frequency spectrum of r(t), 𝑡 𝑤 is half-length of the time window. Assuming a convolutional seismogram and known wavelet...
2022
Synthetic-data-driven deep learning method for elastic parameter inversion
Shuai Sun, Luanxiao Zhao, Huaizhen Chen, Zhiliang He, Jianhua Geng
International Meeting for Applied Geoscience and Energy (IMAGE)
... coefficient sequences; Finally, the Zoeppritz equation and the convolutional model is adopted to synthesize the AVO gather sets. The wavelets used...
2023
Deep compressed learning for 3D seismic inversion
Maayan Gelboim, Amir Adler, Yen Sun, Mauricio Araya-Polo
International Meeting for Applied Geoscience and Energy (IMAGE)
... (sorted seismic records) to a 3D velocity model, implemented using a deep convolutional neural network (DCNN). The proposed method provides a solution...
2023
High-Resolution DFN Modeling via Seismic Attribute Integration in the Sichuan Basin for Completion Optimization
Xuefeng Yang, Shengxian Zhao, Dongchen Liu, Deliang Zhang, Lieyan Cao, Joseph Leines Artieda, Chuxi Liu, Wei Yu, Jijun Miao
Unconventional Resources Technology Conference (URTEC)
... discrete fracture network (DFN) model. The DFN captures both small- and large-scale geological discontinuities, providing critical insights for optimizing...
2025
Feature Detection for Digital Images Using Machine Learning Algorithms and Image Processing
Xiao Tian, Hugh Daigle, Han Jiang
Unconventional Resources Technology Conference (URTEC)
... is increased greatly. There are 16 weight layers in vgg16 model, including 13 convolutional layers and 3 fully-connected layers. There are 19 weight...
2018
Chapter Nine: Inversion and Interpretation of Impedance Data
Rebecca B. Latimer
AAPG Special Volumes
... of inversion and forward modeling. Figure 9-3. Graphic representation of trace inversion from the reflection series to the low-frequency earth model...
2011
Interactive channel interpretation using deep learning
Hao Zhang, Peimin Zhu, Zhiying Liao, Zewei Li, Dianyong Ruan
International Meeting for Applied Geoscience and Energy (IMAGE)
..., it is difficult to extract channels completely. With the development of machine learning technology, convolutional neural network (CNN) is widely...
2022
Deep neural networks for 1D impedance inversion
Vladimir Puzyrev, Anton Egorov, Anastasia Pirogova, Chris Elders, Claus Otto
Petroleum Exploration Society of Australia (PESA)
... such as the 160-layer velocity model used as an example in this study require large synthetic datasets for training, which are not always possible...
2019
Physics-Constrained Deep Learning for Production Forecast in Tight Reservoirs
Nguyen T. Le, Roman J. Shor, Zhuoheng Chen
Unconventional Resources Technology Conference (URTEC)
.... The above limitation necessitates the incorporation of domain knowledge into deep learning model. First, to investigate whether it is possible for deep...
2021
An approach for three-dimensional quantitative carbonate reservoir characterization in the Pampo field, Campos Basin, offshore Brazil
Danilo Jotta Ariza Ferreira, and Wagner Moreira Lupinacci
AAPG Bulletin
... can use the convolutional model of the seismic trace-in-time domain,where s(t), r(t), ω(t), and n(t) represent, respectively, the seismic trace...
2018
Velocity continuation with Fourier neural operators for accelerated uncertainty quantification
Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann
International Meeting for Applied Geoscience and Energy (IMAGE)
... in the background squared-slowness model. Uncertainty quantification is essential for determining how variability in the background models affects seismic...
2022
A novel approach to hydrocarbon reserves estimation through the integration of AI-based solutions: 3D gamma-ray prediction and 3D seismic clustering
Konstantin Matrosov, Orkhan Mammadov, Tarek Eliva, Ruslan Malikov, Izat Shahsenov
International Meeting for Applied Geoscience and Energy (IMAGE)
... Ray (GR) prediction requires a seismic reflectivity stack and GR log from the wells. In the background, it utilizes the Convolutional Neural Network...
2024
Adaptive Eigenstructure Classification and Stochastic Decorrelation Filters for Coherent Interference Suppression in the Acoustic Zoom Method, #41503 (2014).
J. Guigne, S. Azad, C. Clements, A. Gogacz, W. Hunt, A. Pant, J. Stacey
Search and Discovery.com
...) and to whiten the frequency spectrum so that all phases are uniformly distributed. If all the in-phase amplitudes of reverberation are the same...
2014
This thin section doesnt exist: On the generation of synthetic petrographic datasets
Ivan Ferreira, Luis Ochoa, Ardiansyah Koeshidayatullah
International Meeting for Applied Geoscience and Energy (IMAGE)
... a geological dataset that is indistinguishable from a real dataset, based on a survey made with domain experts and with an FID Score of 12.49. This model can...
2022
Simulating seismic data using generative adversarial networks
Bradley C. Wallet, Eyad Aljishi, Hussain Alfayez
International Meeting for Applied Geoscience and Energy (IMAGE)
... International Conference on Machine Learning, 70, 214–223. Chellapilla, K., S. Puri, and P. Simard, 2006, High performance convolutional neural...
2022
Improved UCR Development Decision Through Probabilistic Modeling with Convolutional Neural Network
Han Young Park, Yunhui Tan, Baosheng Liang, Yuguang Chen
Unconventional Resources Technology Conference (URTEC)
...Improved UCR Development Decision Through Probabilistic Modeling with Convolutional Neural Network Han Young Park, Yunhui Tan, Baosheng Liang...
2022
Semisupervised learning with knowledge embedding for horizon volumes calculation
Rui Guo, He Lin, Maoshan Chen, Chunfeng Tao, Yingnan Gao, Ruochong Wen
International Meeting for Applied Geoscience and Energy (IMAGE)
..., Ruochong Wen. BGP, CNPC. Summary Different from purely data-driven supervised deep learning, we propose a theory-guided model to autonomously produce...
2023
Inference of Induced Fracture Geometries Using Fiber-Optic Distributed Strain Sensing in Hydraulic Fracture Test Site 2
Stephen Bourne, Kees Hindriks, Alexei A. Savitski, Gustavo A. Ugueto, Magdalena Wojtaszek
Unconventional Resources Technology Conference (URTEC)
... ℒ̇w = ℒ̇ij 𝑛 𝑖 𝑛 𝑗 , (9) The convolutional model for DSS, εw or ε̇ w, due to the proximal fracture aperture field, 𝑎, may then be wr...
2021
Supervised vs unsupervised deep learning for time-lapse seismic repeatability enforcement
Son Phan, Wenyi Hu, Aria Abubakar
International Meeting for Applied Geoscience and Energy (IMAGE)
.... Unfortunately, due to the non-stationarity of seismic data, the high-frequency content is filtered out during wave propagation through absorptive...
2024
Unsupervised compensation of spiral-shaped drone magnetic survey using a recurrent convolutional autoencoder
Brett Bernstein, Yaoguo Li, Richard Hammack, Colton Kohnke
International Meeting for Applied Geoscience and Energy (IMAGE)
...Unsupervised compensation of spiral-shaped drone magnetic survey using a recurrent convolutional autoencoder Brett Bernstein, Yaoguo Li, Richard...
2024
Lithology and Fluid Seismic Determination for the Acae Area, Puerto Colon Oil Field, Colombia
F. H. Gómez, J. P. Castagna
Asociación Colombiana de Geólogos y Geofisicos del Petróleo (ACGGP)
...), the difference in frequency between the well log and seismic data is handled by using a convolutional operator and assuming that each sample of the target log...
2004
Effectiveness of dip-in DAS observations for low-frequency strain and microseismic analysis: The CanDiD experiment
David W. Eaton, Yuanyuan Ma, Chaoyi Wang, Kelly MacDougall
International Meeting for Applied Geoscience and Energy (IMAGE)
...Effectiveness of dip-in DAS observations for low-frequency strain and microseismic analysis: The CanDiD experiment David W. Eaton, Yuanyuan Ma...
2022