... contrastive learning methodology in a semantic segmentation task. neural network machine learning partition upstream oil & gas reservoir characterization contrastive learning artificial intelligence learning segmentation volumetric supervised contrastive learning presented american...

... of a seismic attribute that may be significant in seismic fault interpretation or a seismic fault attribute is treated as an image segmentation problem and using different deep learning (DL) architectures. For doing this, the researchers mainly concentrate on applying cutting-edge DL architectures in computing...

... We combine the ideas of transfer learning and semantic segmentation of seismic facies in a dataset-to-dataset transfer learning research problem with the goal of reducing the number of inputted labeled seismic slices while also improving computational cost and accuracy of predicting geological...

... drilling measurement mud logging / surface measurements exploration geophysicist lithology cuttings american association texture society photograph applied geoscience segmentation energy 10 drilling cuttings international figure characteristic application The digital revolution...

... the noise. In this work, we propose two novel elements for enhancing blind-spot denoising: (1) the introduction of a 2-class segmentation task to aid the network in identification of interest areas of signals that require particular attention during denoising, and; (2) the introduction of a trace-wise noise...

.... fracture characterization reservoir characterization exploration geophysicist upstream oil & gas artificial intelligence reservoir fracture delineation conditional generative adversarial network international neural network dataset applied geoscience segmentation deep learning machine...

... coefficient machine learning-based residual moveout picking society editing segmentation information energy 10 Machine learning-based residual moveout picking Farhad Bazargani Wenjun Zhang , Anu Chandran , Zaifeng Liu , and Harry Rynja Shell International Exploration and Production; Shell India...

... the North Sea. Next we implemented aleatoric uncertainty as a proxy to filter out areas where high uncertainty and low probability exist. The results show different levels to improve the continuity of fault segments and decrease the occurrence of false-positive faults. upstream oil & gas...

..., the resulting 4D effects are usually oversmoothed and their strength is underestimated. We instead propose to adapt the joint inversion and segmentation algorithm introduced by Ravasi and Birnie (2021) to the problem of 4D seismic inversion. Our technique produces two acoustic impedance models by inverting...

... but was not presented at IMAGE 2022 in Houston, Texas. upstream oil & gas artificial intelligence exploration geophysicist deep learning reservoir characterization algorithm neural network machine learning international china university segmentation american association dianyong ruan institute...

... digitization engine to transform well log data embedded in raster images into digital data that is saved in JSON, CSV, or LAS format. A typical raster image captures the well log information in its constituents as document header, tables, plot segments, depth tracks, and log header sections. The proposed...

... The difficulties involved in studying micrometer-sized micrite crystals, and quantifying the associated impact on large scale geophysical properties, have long hindered our society’s understanding of both Middle Eastern and global microporous limestones. Instance segmentation procedures, from...

... learning generator exploration geophysicist dataset augmented fomel geophysics fault association interpretation segmentation energy 10 wasserstein gan augmentation applied geoscience american association characteristic Seismic data augmentation for automatic faults picking using deep...

...Digital Rock Physics - Estimating the impact of unresolved voxels on elasticity Chaitanya Pradhan* & Nishank Saxena Shell India Markets Pvt Ltd, Shell International Exploration and Production Summary labels, to prepare the image to be fed into numerical simulators. Image segmentation techniques...

.... Several machine-learning (ML) models have been proposed to automate this interpretation but there are still significant practical challenges in multiclass facies segmentation. We present supervised and semisupervised Bayesian deep-learning methodologies designed to improve analysis of seismic facies...

... the interpretative workflow by combining the power of ensemble methods in ambiguities of inverted reservoir properties. data integration and deep learning techniques in feature Feature segmentation plays an important role in the feature- segmentation. The performance of the developed workflow oriented integration...

... algorithms, while convolutional neural networks (CNNs) are excellent for image classification tasks, typically involves a fixed-length input and a huge amount of training data for a low-resolution output. Instead, fully convolutional networks (FCNs) exceed in semantic segmentation, they handle variable...

... to the CNN. Presentation Date: Monday, October 12, 2020 Session Start Time: 1:50 PM Presentation Time: 3:05 PM Location: 351F Presentation Type: Oral neural network synthetic seismic image workflow artificial intelligence segmentation channel interpretation machine learning deep learning...

... carried out separately. Integrating deep learning and image semantic segmentation, we perform an image-to-image sedimentary microfacies division by using an improved U-net. Allowing for the features of logging data and U-net algorithm in deep learning, we change the pooling layer, convolution kernel...

... segmentation to polygons and or multipolygons that describe exclusion zones. Presentation Date: Wednesday, September 18, 2019 Session Start Time: 1:50 PM Presentation Time: 3:55 PM Location: Poster Station 12 Presentation Type: Poster geometric segmentation polygon exclusion zone source point...