Seismic Models of a Shelf-margin Depositional Sequence: Upper San Andres Formation, Last Chance Canyon, New Mexico

Jan Stafleu , Mark D. Sonnenfeld

Journal of Sedimentary Research (SEPM)

... Geologists Memoir 26, p. 3-14. SKINNER, J.W., 1946, Correlation of Permian of west Texas and southeast New Mexico: American Association of Petroleum...

Depositional Framework of Sandy Mid-Fan Complexes of Tourelle Formation, Ordovician, Quebec

Richard N. Hiscott

AAPG Bulletin

... are by far the most common depositional structures, with varied convolution superimposed. The climbing ripples most closely resemble types A or C...

Constraining uncertainty in interpretation of seismically imaged clinoforms in deltaic reservoirs, Troll field, Norwegian North Sea: Insights from forward seismic models of outcrop analogs

Nicholas E. Holgate, Gary J. Hampson, Christopher A.-L. Jackson, and Steen A. Petersen

AAPG Bulletin

... intervals shows a strong correlation between the two parameters ( = 0.91; Figure 10D). Thus, three pairs of values of the parameters were chosen...

Numerical RTA for Dry Gas Wells

Mathias L. Carlsen, Curtis Hays Whitson, Mohamad M. Dahouk

Unconventional Resources Technology Conference (URTEC)

... models, time, and spatial superposition (convolution), pseudopressure and pseudotime transforms are not required. 2 LA URTeC 4026063 Introduction...

Estimating CO2 saturation maps from seismic data using deep convolutional neural networks

Zi Xian Leong, Tieyuan Zhu, Alexander Y. Sun

International Meeting for Applied Geoscience and Energy (IMAGE)

... of training to produce 20 different of weights. At each iteration and at every training epoch, the kernels at every convolution layer (Conv2D) sample the input...

A Unified Leak-off and Flow-back Model for Fractured Reservoirs

Dylan Copeland

Unconventional Resources Technology Conference (URTEC)

...roducing any additional unknowns for pressure in the compressible region. However, the disadvantage is that the convolution must be evaluated at each . ...

Accurate seismic data interpolation based on multiband intelligent training

Xueyi Sun, Benfeng Wang, Tongtong Mo

International Meeting for Applied Geoscience and Energy (IMAGE)

... nonlinear features. The input data is passed through convolutional layers, where convolution kernels are applied to capture and highlight important...

Transitional Flow Regimes in Multi-Fractured Horizontal Wells

Shail Apte, W. J. Lee

Unconventional Resources Technology Conference (URTEC)

... rate we use the convolution theorem which is p− = wD 1 𝑞− 𝑠2 𝐷 . A.39 Applying the convolution theorem to equations A.33 and A.34 and using...

Seismic inversion with implicit neural representations

Juan Romero, Wolfgang Heidrich, Nick Luiken, Matteo Ravasi

International Meeting for Applied Geoscience and Energy (IMAGE)

... be mathematically represented via the socalled convolutional model (Goupillaud, 1961). This entails the convolution of a source function or wavelet w...

Efficient Bayesian full-waveform inversion using a deep convolutional autoencoder prior

Shuhua Hu, Mrinal K Sen, Zeyu Zhao, Abdelrahman Elmeliegy, Shuo Zhang

International Meeting for Applied Geoscience and Energy (IMAGE)

... channels. We use 3×3 kernel size for all the convolution, and stride size of 2 to reduce and upscale the dimension of the extracted features after...

Fractured Reservoir Prediction … A Case Study in the Sichuan Basin; #10512 (2013)

Ling Yun, Xiangyu Guo, Qianggong Song, and Weisheng He

Search and Discovery.com

... convolution and phase processing Uphole data +shallow refractions + 3D Tomo-inversion statics Field statics Velocity analysis: 1. VSP-surface V analysis 2...

Chapter 11: Kimmeridge Clay Formation, United Kingdom—A Mesozoic Clastic-Carbonate Shelf-to-Intrashelf Basin System: An Outcrop-to-Subsurface Analog for the Haynesville, Vaca Muerta, and Bazhenov Formations

K. M. Bohacs, J. Macquaker, O. R. Lazar

AAPG Special Volumes

.... W., 2009, Correlation problems in the Kimmeridge Clay Formation (Upper Jurassic, UK): Lithostratigraphy versus biostratigraphy and chronostratigraphy...

Sedimentology and Dispersal pattern of a Cretaceous Flysch Sequence, Patagonian Andes, Southern Chile

Kevin M. Scott

AAPG Bulletin

..., correlation between amplitude of flute casts and bed thickness; (2) general, but again far-from-perfect, correlation between amplitude of flute casts...

A Delta-Slope-Submarine Fan Model for Maestrichtian Part of Great Valley Sequence, Sacramento and San Joaquin Basins, California

Victor B. Cherven

AAPG Bulletin

.... Exploration in lower and upper fan deposits has barely begun. Almgren, A. A., 1972, Age and correlation of the Alcalde Shale Formation--an alternate...

Search and Discovery

Search and Discovery.com

Chapter 16: Controls on Stratal Record: Mechanisms and Contingencies Affecting Sediment Supply and Accommodation

Kevin M. Bohacs

AAPG Special Volumes

.... 10, p. 417–439. Chalmers, G. R. L., R. Boyd, and C. F. K. Diessel, 2013, Accommodation-based coal cycles and significant surface correlation of low...

Siliciclastic Sequence Development in Foreland Basins, with Examples from the Western Canada Foreland Basin: Chapter 2

Macomb T. Jervey

AAPG Special Volumes

... of Sedimentary Petrology, v. 57, p. 639-650. Plint, A. G., R. G. Walker, and W. L. Duke, 1988, An outcrop to subsurface correlation of the Cardium Formation...

Architecture, process, and environmental diversity in a late Cretaceous slope channel system

Benjamin Kneller, Guilherme Bozetti,, Richard Callow,,† Mason Dykstra, Larissa Hansen,, Ian Kane,,‡ Pan Li,,§ Adam McArthur,, Amanda Santa Catharina, Thisiane Dos Santos, Philip Thompson,¶

Journal of Sedimentary Research (SEPM)

...) Representative logs and correlation of Stage II (CCS-B) (from Li et al. 2018). Stage II. Stage II conglomerates are generally finer-grained than Stage I...

The influence of sediment supply on the stratigraphic evolution of an ancient passive margin deep-marine slope channel system, Windermere Supergroup, British Columbia, Canada

Patricia E. Fraino,, R. William C. Arnott, Lilian Navarro

Journal of Sedimentary Research (SEPM)

...), but only data from CC-SE and CC-South are presented here (see supplemental Fig. S1 for full correlation panel). Identification of stratal elements...

Incorporating Artificial Intelligence into Traditional Exploration Workflows in the Cooper-Eromanga Basin, South Australia

H. M. Garcia, W. G. "Woody" Leel Jr., M. Riehle, P. Szafian

International Meeting for Applied Geoscience and Energy (IMAGE)

... color blends can be combined with the faults detected by the convolution neural network. This allowed us to define the compartments delineated...

Physics-directed unsupervised machine learning: Quantifying uncertainty in seismic inversion

Sagar Singh, Yu Zhang, David Thanoon, Pandu Devarakota, Long Jin, Ilya Tsvankin

International Meeting for Applied Geoscience and Energy (IMAGE)

..., the second dimension is unity. The “stride” represents the number of rows/columns in the filter shifts over the input matrix while applying the convolution...

Seismic speckle as multiplicative noise explaining land reflections distorted by near-surface scattering

Andrey Bakulin, Dmitry Neklyudov, Ilya Silvestrov

International Meeting for Applied Geoscience and Energy (IMAGE)

... with some random parameters, 𝑛 𝑡 is additive random noise, “*” means convolution, k=1,…,K (K is a number of the channels). In the Fourier domain (1...

Robust joint inversion and segmentation of 4D seismic data

Juan Romero, Matteo Ravasi, Nick Luiken

International Meeting for Applied Geoscience and Energy (IMAGE)

... the natural logarithm of the acoustic impedance model m from post-stack seismic data d. The modelling operator G is defined as the convolution...

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...

Bringing ML models into mainstream applications by enabling cloud platform connections

Rafael Pinto, Ilya Agurov, Roman Emreis, Iurii Koniaev-Gurchenko, Dmitrii Zolotukhin, Viktar Huleu, Evgeny Shulikin, Andrey Derevyanka, Pavel Shashkin, Maksim Krug, Ivan Grechikhin, Anton Petrov, Simon Shaw, Brian Macy, Chengbo Li, Chuck Mosher, Anand Malgi

International Meeting for Applied Geoscience and Energy (IMAGE)

..., we applied a 1D convolution to the timedomain reflectivity volume using the SEAM project wavelet to create the synthetic seismic data, i.e., our ML...