Unsupervised Machine Learning Applied to Seismic Interpretation: Towards an Unsupervised Automated Interpretation Tool [PDF]
Sensors, 2021 Seismic interpretation is a fundamental process for hydrocarbon exploration. This activity comprises identifying geological information through the processing and analysis of seismic data represented by different attributes.
Alimed Celecia +8 more
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Increasing the quality of seismic interpretation [PDF]
Interpretation, 2016 Geologic models are based on the interpretation of spatially sparse and limited resolution data sets. Nonunique interpretations often exist, resulting in commercial, safety, and environmental risks. We surveyed 444 experienced geoscientists to assess the validity of their interpretations of a seismic section for which multiple concepts honor the data.
Macrae, Euan J. +3 more
semanticscholar +7 more sources
Quantification of uncertainty in 3-D seismic interpretation: implications for deterministic and stochastic geomodeling and machine learning [PDF]
Solid Earth, 2019 In recent years, uncertainty has been widely recognized in geosciences, leading to an increased need for its quantification. Predicting the subsurface is an especially uncertain effort, as our information either comes from spatially highly limited direct
A. Schaaf, C. E. Bond
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Learnable Gabor Kernels in Convolutional Neural Networks for Seismic Interpretation Tasks [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2023 The use of convolutional neural networks (CNNs) in seismic interpretation tasks, like facies classification, has garnered a lot of attention for its high accuracy.
Fu Wang, T. Alkhalifah
semanticscholar +1 more source
A Joint Inversion-Segmentation approach to Assisted Seismic Interpretation [PDF]
82nd EAGE Annual Conference & Exhibition, 2021 Structural seismic interpretation and quantitative characterization are historically intertwined processes. The latter provides estimates of the properties of the subsurface, which can be used to aid structural interpretation alongside the original ...
M. Ravasi, C. Birnie
semanticscholar +1 more source
3D seismic interpretation with deep learning: A brief introduction
The Leading Edge, 2021 Understanding the internal structure of our planet is a fundamental goal of the earth sciences. As direct observations are restricted to surface outcrops and borehole cores, we rely on geophysical data to study the earth's interior.
T. Wrona +5 more
semanticscholar +1 more source
Identification and Interpretation of fan deposits in Block H12 of Beixi subsag, Beier depression, Hailar basin [PDF]
E3S Web of Conferences, 2020 Fan deposits in the Nantun formation in Beier depression have been drilled in the past two decades. It’s difficult to identify and describe subtle traps formed by fans by seismic interpretation. By using a combination of seismic interpretation techniques
Yu-lin QI, Yue ZHOU
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Generating Paired Seismic Training Data with Cycle-Consistent Adversarial Networks
Remote Sensing, 2023 Deep-learning-based seismic data interpretation has received extensive attention and focus in recent years. Research has shown that training data play a key role in the process of intelligent seismic interpretation.
Zheng Zhang +4 more
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Energies, 2020 A good understanding of different rock types and their distribution is critical to locate oil and gas accumulations in the subsurface. Traditionally, rock core samples are used to directly determine the exact rock facies and what geological environments ...
Nilesh Dixit +2 more
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A Quantitative Interpretation of Seismicity and Seismic Activity [PDF]
Geophysical Journal International, 1967 Summary A new method for computation of seismicity has been worked out and the concept seismic activity has been mathematically formulated as an enlargement of seismicity. For computation of seismic activity a mathematical representation of the energy density function of an earthquake is needed.
W. Ullmann, R. Maaz
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