This work introduces a novel application for predicting the macroscopic intrinsic permeability tensor in deformable porous media, using a limited set of micro-CT images of real microgeometries. The primary goal is to develop an efficient, machine-learning (ML)-based method that overcomes the limitations of traditional permeability estimation techniques, which often rely on time-consuming experiments or computationally expensive fluid dynamics simulations. The novelty of this work lies in leveraging Convolutional Neural Networks (CNN) to predict pore-fluid flow behavior under deformation and anisotropic flow conditions. Particularly, the described approach employs binarized CT images of porous micro-structure as inputs to predict the symmetric second-order permeability tensor, a critical parameter in continuum porous media flow modeling. The methodology comprises four key steps: (1) constructing a dataset of CT images from Bentheim sandstone at different volumetric strain levels; (2) performing pore-scale simulations of single-phase flow using the lattice Boltzmann method (LBM) to generate permeability data; (3) training the CNN model with the processed CT images as inputs and permeability tensors as outputs; and (4) exploring techniques to improve model generalization, including data augmentation and alternative CNN architectures. Examples are provided to demonstrate the CNN's capability to accurately predict the permeability tensor, a crucial parameter in various disciplines such as geotechnical engineering, hydrology, and material science. An exemplary source code is made available for interested readers.

Due to the overwhelming response to our previous expert paper suggestion blog, we had to do another. We asked some of our expert community the papers they would suggest everybody read when working in the field. Haven't seen the first blog? You can read the recommendations of Andrew Ng, Jeff Clune, Myriam Cote and more here. Alexia suggested this paper as it explains how many classifiers can be thought of as estimating an f-divergence.

Artificial intelligence, energy diversification and the transformation of the workforce will be amongst the major talking points at SPE Offshore Europe 2019. Senior international industry figures will co-chair the keynote sessions which also includes late life and decommissioning, underwater innovation, transformative technologies to lower the carbon footprint, digital security, integrated technologies, digitalisation, standardisation and finance. The event will take place from 3-6 September at the new £333million The Event Complex Aberdeen (TECA), under the theme: 'Breakthrough to Excellence – Our license to operate'. Michael Borrell, SPE Offshore Europe 2019 Conference Chair & Senior Vice President, North Sea and Russia at Total said: "Our committee is full of international oil and gas industry leaders and they have developed an excellent programme which gets to the heart of the main opportunities and challenges facing the region. "Offshore Europe 2019 is a great opportunity for us to challenge ourselves in the North Sea basin.