In petroleum engineering, it is essential to determine the ultimate recovery factor, RF, particularly before exploitation and exploration. However, accurately estimating requires data that is not necessarily available or measured at early stages of reservoir development. We, therefore, applied machine learning (ML), using readily available features, to estimate oil RF for ten classes defined in this study. To construct the ML models, we applied the XGBoost classification algorithm. Classification was chosen because recovery factor is bounded from 0 to 1, much like probability. Three databases were merged, leaving us with four different combinations to first train and test the ML models and then further evaluate them using an independent database including unseen data. The cross-validation method with ten folds was applied on the training datasets to assess the effectiveness of the models. To evaluate the accuracy and reliability of the models, the accuracy, neighborhood accuracy, and macro averaged f1 score were determined. Overall, results showed that the XGBoost classification algorithm could estimate the RF class with reasonable accuracies as high as 0.49 in the training datasets, 0.34 in the testing datasets and 0.2 in the independent databases used. We found that the reliability of the XGBoost model depended on the data in the training dataset meaning that the ML models were database dependent. The feature importance analysis and the SHAP approach showed that the most important features were reserves and reservoir area and thickness.

Gardeners want to make their grass even greener. As petrol prices rocket and people become ever more conscious of their environmental impact, many are turning to the latest generation of lawnmowers to keep their gardens looking good. While the fronts of our houses are gradually seeing the replacement of petrol cars with electric vehicles, advances in lithium-ion batteries have meant that the trusted back garden mower has also been given a modern overhaul – but at a price. So is it time to replace your current mower with a battery-powered or "robot" version, stick with petrol despite the spiralling costs, or stay plugged in? The length and breadth of your garden will heavily influence what type of machine you need.

Galway start-up Chatspace has developed an artificial intelligence answers and insights platform that prevents projects on track and prevents costly failures. Chatspace works with the world's largest companies unleashing new insights for company strategy that traditional teams can't reach, automating repeatable tasks and scaling capabilities across the enterprise. The company believes that the future of work is engaged and connected employees taking advantage of the capabilities that technology provides. Its clients to date include ATOS, Nestle and Medtronic. "Project Management is integral to Enterprise," explains Chatspace CEO and founder John Clancy.

Some say that the insurance industry is a long, quiet river on which stately steamships cruise. Others say it is a shark tank where only the strongest survive. The insurance market is clearly mature, with a limited scope of action for individual players. There is, however, no question that merciless predatory competition is taking place, probably precisely because of this saturation. It is the perfect recipe for a ruinous price war, even though this is something that insurers really cannot afford in the long term.