Imaging and fold comparison of mirror reverse time migration vs. interferometric imaging for VSP data

Liwei Cheng, James Simmons, Ali Tura

International Meeting for Applied Geoscience and Energy (IMAGE)

.... Mirror migration and interferometric imaging utilize free-surface multiples to extend the subsurface illumination. We design a 2-D synthetic model...

Using machine learning to interpret 3D airborne electromagnetic inversions

Eldad Haber, Jen Fohring, Mike McMillan, Justin Granek

Petroleum Exploration Society of Australia (PESA)

... types of regularization and constraints to the model, but another approach is to learn what underlying structures or boundaries these smooth...

Post Migration Processing of Seismic Data

Dashuki Mohd.

Geological Society of Malaysia (GSM)

... or multiples. The basis for deconvolution is the convolutional model (Robinson, 1984). In the convolutional model, a seismic trace is viewed...

An immersed absorbing boundary condition for scalar wavefield modeling under topography

KeJi Chen, Hanming Chen, Hui Zhou

International Meeting for Applied Geoscience and Energy (IMAGE)

... interface. The Ricker wavelet with the main frequency of 20 Hz is used as the source to be excited under the surface. The sinusoidal surface model is used...

Micro transient EM for seismic sand corrections through physics-coupled deep learning

Daniele Colombo, Ersan Turkoglu, Ernesto Sandoval-Curiel, Javier Giraldo-Buitrago

International Meeting for Applied Geoscience and Energy (IMAGE)

.... data-driven approaches (e.g., tomography), at exploration seismic acquisition specifications, are inadequate to reliably model the extremely low sand...

Unsupervised machine learning for seismic facies classification using a 3D grid approach

David Manzano, Edgar Galvan, Dan Ferdinand Fernandez

International Meeting for Applied Geoscience and Energy (IMAGE)

... that describe characteristics such as amplitude, frequency, phase. With advances in ML, technology has emerged for applications to seismic facies...

Deep-learning application of salt geometry detection in deep water Brazil

Ruichao Ye, Anatoly Baumstein, Kirk A. Wagenvelt, Erik R. Neumann

International Meeting for Applied Geoscience and Energy (IMAGE)

... a novel workflow based on a deep convolutional neural network for automatically detecting salt geometry from a seismic image. By developing...

Reservoir Modeling With Deep Learning

Search and Discovery.com

Abstract: FaciesNet: Machine Learning Applications for Facies Classification in Well Logs;

Chayawan Jaikla, Pandu Devarakota, Neal Auchter, Mohamed Sidahmed, Irene Espejo

Search and Discovery.com

... information, facies stacking pattern, and geologic correlations, FaciesNet. Our proposed model incorporates decoding and encoding deep convolutional...

Fast viscoacoustic forward modeling method based on U-net Fourier neural operator

Wenbin Tian, Yang Liu

International Meeting for Applied Geoscience and Energy (IMAGE)

... variations within the data. On the other hand, the wavenumber-domain CNN operates as a trainable wavenumber filter, enabling nonlocal spatial convolutional...

Seismic data augmentation for automatic faults picking using deep learning

Nam Pham, Sergey Fomel

International Meeting for Applied Geoscience and Energy (IMAGE)

... these newly generated data for training a convolutional neural network for faults picking, as the training data will resemble the field test data...

Increasing The Resolution of Seismic Imaging With Spectral Blueing, Spectral Decomposition RGB And HSV Blending to Delineate The Fluvial Facies on Fluvio Deltaic Environment

Aji Darma Maulana, Nine Safira, Ongki Ari Prayoga, Egie Wijaksono, Alit Ascaria

Indonesian Petroleum Association

... surveys (Partyka et al., 1999). Spectral decomposition is carried out by converting seismic data into the frequency domain using time-frequency...

Robust localized adaptive waveform inversion: A new regularization for Gabor deconvolution

Peng Yong, Romain Brossier, Ludovic Mtivier

International Meeting for Applied Geoscience and Energy (IMAGE)

...) used in LAWI, can be defined by a non-stationary ˆ convolutional model in the time-frequency domain (Yong et al., 2021): ˆ w(t, ω)d(t, ω) = p(t, ω), ˆ ˆ...

2D isotropic and vertical transversely isotropic RTM using SEG Hess VTI Model

Richa Rastogi, Abhishek Srivastava, Monika Gawade, Nithu Mangalath, Laxmaiah Bathula, Bhushan Mahajan, Suhas Phadke

International Meeting for Applied Geoscience and Energy (IMAGE)

...2D isotropic and vertical transversely isotropic RTM using SEG Hess VTI Model Richa Rastogi, Abhishek Srivastava, Monika Gawade, Nithu Mangalath...

GeoMind: An intelligent earth model building tool

Saleh Al Saleh, Ewenet Gashawbeza, Mustafa Marzooq, Hussam Banaja, Husain Al Shakhs, Jianwu Jiao

International Meeting for Applied Geoscience and Energy (IMAGE)

...GeoMind: An intelligent earth model building tool Saleh Al Saleh, Ewenet Gashawbeza, Mustafa Marzooq, Hussam Banaja, Husain Al Shakhs, Jianwu Jiao...

Modeling Distributed Fiber Optic Sensor Signals Using Computational Rock Mechanics

Christopher S. Sherman, Robert J. Mellors, Joseph P. Morris, Frederick J. Ryerson

Unconventional Resources Technology Conference (URTEC)

... the numerical model and tied to an underlying finite element mesh. Both the low-frequency strain as created by an opening (or closing) fracture and the high...

Unconventional Reservoir Microstructural Analysis Using SEM and Machine Learning

Amanda S. Knaup, Jeremy D. Jernigen, Mark E. Curtis, John W. Sholeen, John J. Borer IV, Carl H. Sondergeld, Chandra S. Rai

Unconventional Resources Technology Conference (URTEC)

... specifically Convolutional Neural Networks (CNN), are being used for pixel labeling and feature identification using the CNN U-Net. This network...

Jointly data and model driven pre-stack inversion of elastic and anisotropy parameters in HTI media

Xin Zhang, Jianhua Geng

International Meeting for Applied Geoscience and Energy (IMAGE)

...Jointly data and model driven pre-stack inversion of elastic and anisotropy parameters in HTI media Xin Zhang, Jianhua Geng Jointly data and model...

3D ultra high resolution seismic processing „ A case study from offshore USA

Bertrand Caselitz, Luca Limonta, Julien Oukili, Jonas Tegnander, Vicky Catterall

International Meeting for Applied Geoscience and Energy (IMAGE)

... reflections. The demultiple step, utilizing methods like convolutional 3D Surface Related Multiple Elimination (SRME) and 3D wave-equation multiple...

Estimating soil strength using ultra high-resolution seismic and geological unit

Donglin Zhu, Ge Jin, Yi Shen, Xuefeng Shang, Shuang Hu, Jinbo Chen, Vanessa Goh

International Meeting for Applied Geoscience and Energy (IMAGE)

... soil assessment for foundation design, due to their high foundation costs and complex integration into marine environments. We propose a convolutional...

Automatic microseismic event detection in downhole DAS data through convolutional neural networks: A comparison of events during and post-stimulation of the well

Paige Given, Fantine Huot, Ariel Lellouch, Bin Luo, Robert G. Clapp, Biondo L. Biondi, Tamas Nemeth, Kurt Nihei

International Meeting for Applied Geoscience and Energy (IMAGE)

... present a convolutional neural network (CNN) which takes inputted images from DAS arrays and accurately detects microseismic events. Our model is able...

3D seismic image-to-image translation

Xiaolei Song, Muhong Zhou, Lifeng Wang, Rodney Johnston

International Meeting for Applied Geoscience and Energy (IMAGE)

... by adopting two convolutional Bayesian layers as the network output layers to analyze the model uncertainties by calculating an uncertainty map from a local...

Time-lapse seismic joint inversion based on Zoeppritz equation in depth domain

Wenjin Li, Jingye Li, Lei Han, Zhen Liao

International Meeting for Applied Geoscience and Energy (IMAGE)

... with velocity (depth) in the depth domain leads to seismic records exhibiting non-stationary. Time-frequency analysis techniques for time-window wavelet...

An integrated machine learning-based fault classification workflow

Jie Qi, Carolan Laudon, Kurt Marfurt

International Meeting for Applied Geoscience and Energy (IMAGE)

... on the human interpreter. We first compute a 3D fault probability volume from pre-conditioned seismic amplitude data using a 3D convolutional neural network...

A hybrid deep learning network for tight and shale reservoir characterization using pressure and rate transient data

Hamzeh Alimohammadi, Hamid Rahmanifard, and Shengnan Nancy Chen

AAPG Bulletin

... at a batch size of 20. Figure 5. Optimum number of batch size (A) and dropout rate (B) for hybrid convolutional neural networks–long short-term memory model...