Three-dimensional geoacoustic perturbative inverse technique for the shallow ocean water column [PDF]
textThis work focuses on developing an inversion scheme to estimate water-column sound-speed fields in three dimensions. The inversion scheme is based on a linearized perturbative technique which utilizes estimates of modal travel times.
Bender, Christopher Matthew
core
Upper-plate conduits linked to plate boundary that hosts slow earthquakes. [PDF]
Arai R +11 more
europepmc +1 more source
Prestack amplitude versus offset (AVO) inversion is an essential tool to estimate elastic properties. Approximations of P-wave reflection coefficients based on the Zoeppritz equation are limited by the assumption of weak contrast and are inaccurate for ...
Yuxing Chen +6 more
doaj +1 more source
A new method of alternating shooting of two different seismic sources for deep geophysical surveys. [PDF]
Liu C +8 more
europepmc +1 more source
The Nash-MTL-STCN for Prestack Three-Parameter Inversion [PDF]
Deep learning (DL) techniques have been widely used in prestack three-parameter inversion to address its ill-posed problems. Among these DL techniques, Multi-task learning (MTL) methods can simultaneously train multiple tasks, thereby enhancing model ...
Liao, Zhangquan +5 more
core +1 more source
Wenchang A oilfield is a recently discovered low-permeability oilfield in the western South China Sea. The exploration target is the Zhuhai Formation, which reservoir lithology changes significantly, and the distribution of favorable reservoirs is ...
Jianning Liu
doaj +1 more source
Insights into dike nucleation and eruption dynamics from high-resolution seismic imaging of magmatic system at the East Pacific Rise. [PDF]
Marjanović M +10 more
europepmc +1 more source
Episodic intraplate magmatism fed by a long-lived melt channel of distal plume origin. [PDF]
Naif S +6 more
europepmc +1 more source
Bidirectional Long Short-term Neural Network Based on the Attention Mechanism of the Residual Neural Network (ResNet-BiLSTM-Attention) Predicts Porosity through Well Logging Parameters. [PDF]
Sun Y, Zhang J, Yu Z, Zhang Y, Liu Z.
europepmc +1 more source
Shale gas geological "sweet spot" parameter prediction method and its application based on convolutional neural network. [PDF]
Qin Z, Xu T.
europepmc +1 more source

