... association geophysics abubakar seismic modeling detection impedance inversion modeling estimation learning-accelerated seismic modeling isolation An integrated workflow for deep learning-accelerated seismic modeling of the Groningen gas field, the Netherlands Haibin Di*, Vanessa Simoes, Zhun Li...

... The A-scan monostatic reflection and transmission radargrams have been effectively computed by the z-transform and accurately jointly inverted with the Gramian constraint. Existing literature review provides GPR methods which do not satisfactorily detect anti-human landmines, considering...

... intelligence pipeline signature diagnostic medicine international upstream oil & gas health & medicine machine learning detection pipeline detection accuracy applied geoscience american association geophysics cnn automated metallic pipeline detection energy 10 probability exploration...

... We consider the task of channel detection as a regression problem and propose a workflow to identify the complex channels in 3D seismic volumes with complex structure using an end-to-end 3D convolutional neural network. To train the network, we automatically generate a training dataset...

... The robust and automatic detection of faults within seismic images remains a challenging issue within the field of seismic interpretation. Recently, supervised deep learning-based approaches using synthetics have shown much promise towards accomplishing a robust and automatic fault detection...

... sundaramoorthi applied geoscience detection Fault surface extraction based on computational topology Cheng Zhou*1, Cun Yang2, Ruoshui Zhou1, Xingmiao Yao3, and Guangmin Hu3 1School of Information and Communication Engineering, University of Electronic Science and Technology of China; 2PetroChina Hangzhou...

... machine learning exploration geophysicist american association boundary mtl overhang society geobody energy 10 flank summary upstream oil & gas reservoir characterization international detection courtesy delineation SaltCrawler: AI solution for accelerating velocity model building...

... individual micrite crystal within gray-scale SEM images. Leveraging Transfer Learning, the ResNet50 neural architecture is used with weights initialized through a pre-training on Microsoft’s Common Objects in COntext (COCO) dataset. The resulting model accurately detects and separates a number of crystals...

... Downhole Distributed Acoustic Sensing (DAS) fibers lie within close proximity to microseismic events, and thus are able to detect events with very high resolution and accuracy. With this high resolution comes a substantial amount of data several terabytes (TB) in size over a few days worth...

... designs an automatic velocity spectrum picking method based on object detection, and applies neural network model named FCOS (Fully Convolutional One-Stage Object Detection) (Tian et al., 2019) to implement the automatic velocity spectrum picking. In this method, the velocity spectrum is processed...

... multiple seismic sensors to identify P and S wave arrivals. Despite using machine learning algorithms for picking, considerable human oversight is required to ensure detection fidelity. This paper proposes a workflow consisting of machine learning and physics-informed methods to achieve total automation...

... of magnetic source detection is the geological interface parallel to the coil surface; The best target of electrical source detection is the geological interface parallel to the electrode arrangement. There is a strong correlation between the time-domain electromagnetic response characteristics of borehole...

.... Finally, the edge detection technology quality. The original fault interpretation scheme can only is used to extract the fault boundary from the maximum identify large faults, but cannot identify the intersection of likelihood attribute volume, and linearly combine it with the large faults and some small...

... The deep buried-hill reservoir of Archaean metamorphic rocks are the main target layers in Bozhong-19 structure of Bohai Sea. Due to fracture reservoirs’ strong heterogeneity and poor quality of the old seismic data, precise fracture detection is still a challenging task. To overcome...

... The primary objective of this work was to detect and delineate abandoned cavities related to mining using full-waveform inversion (FWI) in the city of Galena, Kansas. The shear-wave velocity (Vs) model obtained from FWI was compared to results previously obtained in the area using backscatter...

...Numerical simulation study on transient electromagnetic logging detection characteristics and influencing factors Zhanshan Xiao*, Haitao Hu, Rongxin Zhang, Junjie Yan, Huiying Li, Yan Bai China Petroleum Logging Co., Ltd Summary conversion. In 1996, Tabarovsky studied the time-domain response...

...Automated detection of bad borehole sections and evaluation of log quality using Toeplitz Inverse Covariance-based Clustering Shuvajit Bhattacharya*, The University of Texas at Austin Summary compensated formation density logs, the spine-and-rib method is used to correct mudcake and stand-off...

... of the pipe account for the frequency spectra of the surface measurements. The multichannel active test also reveals that the acoustic modes of the pipe can appear in time domain and spectral domain and can be helpful in detection of the pipe. reservoir characterization acoustic mode source location...

... of energy lost at the air-ground interface. Today, airborne GPR is being considered for applications This table demonstrates that for most soil types, well over commonly addressed by conventional GPR, such as utilities 50% of the energy transmitted is lost in the ground detection and lake bathymetry surveys...

... detecting microseismic signals in continuous data is challenging and timeconsuming. DAS acquisitions generate substantial data volumes, and microseismic events have a low signal-to-noise ratio in individual DAS channels. Herein we design, train, and deploy a deep learning model to automatically detect...