Modeling of resistivity and acoustic borehole logging measurements using finite element methods
Modeling of Resistivity and Acoustic Borehole Logging Measurements Using Finite Element
Methods provides a comprehensive review of different resistivity and sonic logging …
Methods provides a comprehensive review of different resistivity and sonic logging …
A deep learning approach to the inversion of borehole resistivity measurements
Borehole resistivity measurements are routinely employed to measure the electrical
properties of rocks penetrated by a well and to quantify the hydrocarbon pore volume of a …
properties of rocks penetrated by a well and to quantify the hydrocarbon pore volume of a …
Error control and loss functions for the deep learning inversion of borehole resistivity measurements
Deep learning (DL) is a numerical method that approximates functions. Recently, its use has
become attractive for the simulation and inversion of multiple problems in computational …
become attractive for the simulation and inversion of multiple problems in computational …
A deep neural network as surrogate model for forward simulation of borehole resistivity measurements
Inverse problems appear in multiple industrial applications. Solving such inverse problems
require the repeated solution of the forward problem. This is the most time-consuming stage …
require the repeated solution of the forward problem. This is the most time-consuming stage …
3-D induction log modelling with integral equation method and domain decomposition pre-conditioning
The deployment of electromagnetic (EM) induction tools while drilling is one of the standard
routines for assisting the geosteering decision-making process. The conductivity distribution …
routines for assisting the geosteering decision-making process. The conductivity distribution …
Modeling extra-deep electromagnetic logs using a deep neural network
Modern geosteering is heavily dependent on real-time interpretation of deep
electromagnetic (EM) measurements. We have developed a methodology to construct a …
electromagnetic (EM) measurements. We have developed a methodology to construct a …
Physics-guided deep-learning inversion method for the interpretation of noisy logging-while-drilling resistivity measurements
Deep learning (DL) inversion is a promising method for real-time interpretation of logging-
while-drilling (LWD) resistivity measurements for well-navigation applications. In this context …
while-drilling (LWD) resistivity measurements for well-navigation applications. In this context …
Limits of three‐dimensional target detectability of logging while drilling deep‐sensing electromagnetic measurements from numerical modelling
Subsurface energy resources are often found in three‐dimensional and non‐spatially
continuous rock formations that exhibit electrical anisotropy. Deep‐sensing tri‐axial …
continuous rock formations that exhibit electrical anisotropy. Deep‐sensing tri‐axial …
Neural network architecture optimization using automated machine learning for borehole resistivity measurements
Deep neural networks (DNNs) offer a real-time solution for the inversion of borehole
resistivity measurements to approximate forward and inverse operators. Using extremely …
resistivity measurements to approximate forward and inverse operators. Using extremely …
Limits of 3D detectability and resolution of LWD deep-sensing borehole electromagnetic measurements acquired in the Norwegian Continental Shelf
ABSTRACT The Grane Field in the central North Sea contains numerous sandstone
injectites embedded in shale formations and located above the main sandstone reservoir …
injectites embedded in shale formations and located above the main sandstone reservoir …