... integration geologist american association assessment reservoir characterization cpt data prediction accuracy information foundation design Estimating soil strength using ultra high resolution seismic and geological unit Donglin Zhu*, Ge Jin, Colorado School of Mines; Yi Shen, China University...

... efficiency while ensuring accuracy. Model testing reveals that compared to conventional U-Net network, the proposed method demonstrates superior learning performance with higher accuracy in capturing intricate details. It serves as a valuable reference for fault solution identification using deep learning...

... wavelet are the most important factors that affects the accuracy of impedance estimated using PINNs. The comparisons demonstrate that the accuracy and resolution of impedance estimated using PINNs is higher than linear optimization and supervised neural networks if the seismic data has a high signal...

... Strike-slip fault identification is an important work in the oil and gas exploration. When it associates many karst caves, the accuracy of traditional methods such as coherence, curvature will be greatly affected. Although the deep learning method can identify some complex faults...

... The signal-to-noise ratio of data in mountainous areas with complex topography conditions and structures is extremely low, but exploration and development require higher accuracy in seismic imaging. The processing effect of shallow seismic data is crucial for subsequent velocity modeling...

... & energy 10 accuracy sensitivity analysis uncertainty map Supervised machine learning sedimentological characterisation workflow, a tool to bridge the gap between qualitative and quantitative facies interpretation and uncertainty quantification. Anis Seksaf*, Boris Kostic, Chloé Château, Daniel Clay...

... and time. In this paper, an intelligent velocity picking method based on Mean-Shift Clustering algorithm was proposed, which improved the accuracy and efficiency of the velocity picking. Firstly, a velocity trend band is set up on the velocity spectrum by experts to avoid multiples and other noise...

... Geofluid identification is critical to reservoir forecast. Many fluid identifications mean released in recent years use conventional linear pre-stack inversions to obtain the majority of the fluid indicators, resulting in low fluid identification accuracy. Another disadvantage is that fluid...

... and low-resolution data, and it can adapt to large time-shift variations and achieve better inversion results. Combining this method with least square full-waveform inversion (LS-FWI) can further improve the accuracy and efficiency of velocity inversion. The paper presents a successful application of TA...

... When adopting finite-difference (FD) algorithms to discretize anisotropic wave equations, the conventional FDs can only enhance the simulation accuracy in space domain. However, the temporal discretization scheme is still of low-order accuracy, which will lead to serious numerical dispersion...

... regression to determine the trend of the picked first break time. The actual data processing results show that the accuracy of the first break time of downward wave picked by this technology reaches more than 95%, and the accuracy of the trend of picked first breaks reaches 100%. Compared with traditional...

...% accuracy in isolation potential classification, further improved to 99.2% by employing Gradient-weighted Class Activation Mapping (Grad-CAM) technique. This technique identifies the most influential regions in images for the classification decision, allowing for retraining the model with a focus...

... accuracy and resolution are insufficient. In western China’s piedmont zone and loess plateau areas, there are complex near-surface issues, such as dramatic changes in the surface elevation, the development of low velocity zones, and high-velocity anomalies near the surface. Conventional methods based...

... transformation exploration geophysicist accuracy offshore seismic data discriminator GAN based data enhancement for first arrival picking on both onshore and offshore seismic data Ding Jicai*,Wei Yanwen,Wang Yichuan,Sun Wenbo and Wang Jianhua, CNOOC Research Institute; National Engineering Research Center...

... Aiming at the problem of complex mountain modeling in western China, a stepwise tomographic inversion modeling method is studied for the requirements of pre-stack depth migration processing. The method consists of a series of measures to improve the surface accuracy, the near-surface model...

... or curved faults and gaps due to data anomalies. By transforming attribute volumes into a structured dataset of spatial coordinates and orientation attributes, OE-DBSCAN uses an orientable ellipsoid to improve clustering accuracy along fault strike and dip. Comparative testing with traditional DBSCAN shows...

... dispersion curve. Finally, a high-precision velocity model in the entire computational domain is established through model merging, and the imaging accuracy of complex structures is greatly improved through prestack depth migration processing, providing an effective approach to seismic imaging quality...

... offers an optimal initial guess for the gradient inversion process. neural network machine learning correction geologist well logging resistivity data correction inversion artificial intelligence geological subdiscipline laterolog response accuracy invasion depth neuron formation...

... Full-waveform inversion approaches aim to recover the subsurface model parameters with high resolution and accuracy. However, mainly due to its non-linear nature and high computational cost, the inversion process may result in an estimated model with low resolution and high uncertainty...

... wavefield in viscoacoustic anisotropic media, as it can provide clear and stable wavefield. However, the previous pure-viscoacoustic anisotropic wave equations have low accuracy because the approximations are adopted in the derivation of the wave equation. In this paper, starting from the exact complex...