Improving Depth Prediction Accuracy of Quantified Drilling Hazards

W. Scott Leaney, William H. Borland

Geological Society of Malaysia (GSM)

... problem without a forward problem, and the forward problem underlying seismic trace inversion is the convolutional model. A processed seismic trace...

A Deep Learning Workflow for Integrated Geological, Petrophysical, and Geomechanical Interpretation

Vanessa Simoes, Atul Katole, Bhuvaneswari Sankaranarayanan, Tao Zhao, Aria Abubakar

Unconventional Resources Technology Conference (URTEC)

... wells, which serve as the basis for training an DL model for marker propagation. This model predicts major markers on the remaining wells, and a marker QC...

VSP Guided Reprocessing and Inversion of Surface Seismic Data

R. Gir, Dominique Pajot, Serge Des Ligneris

Southeast Asia Petroleum Exploration Society (SEAPEX)

... in wavelets are the more statistical aspects of wavelets processing. This effect is usually time varying. The common interpretive model for surface...

Impact of an Integrated Seismic Data Processing Approach: A Case Study in Central Sumatra

Mars E. Semaan, Eddy Murhantoro, Maryanto, Achmad Bermawi, Budi Subianto, Hari Santoso

Indonesian Petroleum Association

... traces are the result of convolving a wavelet with a reflection coefficient series, as defined by the convolutional model. Given a seismic trace...

Abstract: A Deep Learning Saturation Imaging Framework to Optimize Reservoir Contact While Drilling; #91204 (2023)

Abdallah AlShehri, Klemens Katterbauer, Ali AlYouesf

Search and Discovery.com

... framework for the optimization of hydrocarbon contact while drilling. The framework utilizes a deep learning convolutional imaging framework in order...

Volumetric Calculations Using 3D Seismic Calibrated Against Porosity Logs - Pretty Hill Formation Reservoirs, Onshore Otway Basin

P. J. Boult, J. Donley

Petroleum Exploration Society of Australia (PESA)

... be considered an extension of the conventional post-stack inversion process. The latter method uses a convolutional model, which is based on an extracted...

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

.... A time window (Figure 2) of a flattened gather of data is defined as The Acoustic Zoom (AZ) seismic beamforming method is an unconventional oil and gas...

Harnessing AI and Computer Vision for Efficient Geothermal Field Exploration and Prospect Evaluation

Moamen Gasser, Danny Rehg, Marcus Oesterberg, Nathan Meehan

Unconventional Resources Technology Conference (URTEC)

.... The model showed a great alliance with the experts’ prediction of the geothermal potential presence. This AI tool is an immensely powerful tool especially...

Abstract: Kirchhoff Imaging with Adaptive Greens Functions for Compensation for Dispersion, Attenuation, and Velocity Imprecision; #90187 (2014)

Andrew V. Barrett

Search and Discovery.com

... frequencies appear to propagate at the velocity of the asymptotic high frequency. If we know the attenuation constant ‘Q’, and if the model for attenuation...

Automated active learning for seismic facies classification

Haibin Di, Leigh Truelove, Aria Abubakar

International Meeting for Applied Geoscience and Energy (IMAGE)

..., 521–535, doi: https://doi.org/10.1111/1365-2478.12865. Di, H., Z. Li, and A. Abubakar, 2022, Using relative geologic time to constrain convolutional...

Multiple, Diffractions and Diffracted Multiples in the South China Sea: How Dense Does Our Acquisition Geometry Need to be? (Geophysics Paper 16)

Rosemary K Quinn, Lynn B Comeaux

Geological Society of Malaysia (GSM)

... be horizontal over the scale of the SRME aperture in order for the model to be predicted accurately. Clearly, this is rarely the case, but as long...

Improved Resolution of Thin Turbiditic Sands in Offshore Sabah with Bandwidth Extension … A Pilot Study (Paper C11)

G. Yu, N. Shah, M. Robinson, N. H. Nghi, A. A. Nurhono, G. S. Thu

Geological Society of Malaysia (GSM)

... by a convolutional-like process in the CWT domain as illustrated in Figure 2. This effectively reshapes the wavelet and broadens the spectrum. Any...

Deep learning-based raster digitization engine

Atul Laxman Katole, Purnaprajna Mangsuli, Omkar Gune, Mohd Saood Shakeel, Abhiman Neelakanteswara, Aria Abubakar

International Meeting for Applied Geoscience and Energy (IMAGE)

... methods used to digitize the raster images are extremely time-consuming and prone to human error. The authors propose a fully automated robust...

Assessment of Micro-Fracture Density using Combined Interpretation of NMR Relaxometry and Electromagnetic Logs

Lu Chi, Marcus, Elliot, Zoya Heidari, Mark Everett

Unconventional Resources Technology Conference (URTEC)

... from the time-convolutional form of Ohm’s law using a Reimann-Liouville derivative. It is displayed below in Equation (6): σ ∂ ∂ σβ *E = β ∂t Γ ( β...

Deep Learning Applied to Fault Interpretation and Attribute Computation

Search and Discovery.com

ABSTRACT: Seismic Heterogeneity Cubes and Corresponding Equiprobable Simulations; #90013 (2003)

Matthias Imhof, William Kempner

Search and Discovery.com

... attributes. Instead, model statistics with only six parameters are fitted to the raw statistics. These six parameters include three orthogonal...

Abstract: A Transfer Learning Approach to Rock Property Estimation Workflows;

Ahmad Mustafa, Motaz Alfarraj, Ghassan Alregib

Search and Discovery.com

.... This results in vertical discontinuities in the computed property volumes using such a model, since it becomes sensitive to lateral changes...

Multi-Modal Neural Network for Porosity and Permeability Estimation in Tight Gas Reservoirs: A Case Study in the Ordos Basin, China

Shengjuan Cai, Yitian Xiao, Han Wang, Feifei Gou, Hanqing Wang, Yujie Zhou, Tianrui Ye

Unconventional Resources Technology Conference (URTEC)

... capture vertical and lateral variations across the reservoir. The network is designed to handle these multimodal inputs, with convolutional layers...

Seismic image-to-image translation using a conditional GAN with Bayesian inference

Xiaolei Song, Muhong Zhou, Petr Jilek, Rodney Johnston, Sean Cardinez, Kareem Vincent

International Meeting for Applied Geoscience and Energy (IMAGE)

... uncertainties. We take a similar approach by adopting two convolutional Bayesian layers as the network output layers to capture the model...

Seismic Meta-Attributes and the Illumination of the Internal Reservoir Architecture of a Deepwater Synthetic Channel Model, #41267 (2014)

Staffan Van Dyke, Renjun Wen

Search and Discovery.com

...  over time of 9  distinctive lithofacies. CLC Model  Velocity and Density CLC Model –Velocity and Density • The facies model was  populated...

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)

... the specialists, it also requires a significant amount of time and effort, both of which significantly affect economic decisions. We propose...

Transfer Learning Applied to Seismic Images Classification

Search and Discovery.com

Perceptual quality-based model training under annotator label uncertainty

Chen Zhou, Mohit Prabhushankar, Ghassan AlRegib

International Meeting for Applied Geoscience and Energy (IMAGE)

...Perceptual quality-based model training under annotator label uncertainty Chen Zhou, Mohit Prabhushankar, Ghassan AlRegib Perceptual quality-based...

Operator chains and seismic data decomposition

Sergey Fomel

International Meeting for Applied Geoscience and Energy (IMAGE)

... operator with a chain of weights alter- The paper is organized as follows. First, I consider chaining weights in alternation between the time domain...

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...