Abstract: It is hereby proposed a computer-implemented method of machine-learning a plurality of predictive basin-wise models. Each predictive basin-wise model is configured for predicting a concentration of an element at a given location in a saline aquifer of a respective basin. The machine-learning method comprises, for each basin and with respect to a predetermined set of one or more geochemical variables, providing a dataset, and learning the predictive basin-wise model based on the dataset. The dataset comprises, for respective saline aquifer locations of the basin, training samples. Each training sample includes a measurement of one or more geochemical variables of the predetermined set. Each training sample further includes a respective ground truth value. The ground truth value represents a concentration of the element at the respective saline aquifer location. Such a method forms an improved solution for analysis of a saline aquifer with respect to a given element of interest.

Abstract: The invention notably relates to a computer-implemented method of machine-learning a predictive model configured for predicting a concentration of an element in produced water of a given well of hydrocarbon production in a hydrocarbon reservoir having wells of hydrocarbon production. The method comprises providing a dataset comprising values of one or more geoscience well-wise variables. Each value corresponds to a respective well of hydrocarbon production in the hydrocarbon reservoir other than the given well. Each value that corresponds to a respective well is associated to a respective ground truth value representing a concentration of the element in the respective well. The method further comprises learning the predictive model based on the dataset. This forms an improved solution for predicting a concentration of an element in produced water of a given well of hydrocarbon production in a hydrocarbon reservoir.

Abstract: The disclosure relates to a method for recovering lithium (Li) and iron (Fe) from a substrate (S) containing LiFePO4/C(s), the method comprising the steps of: i.—Bringing the substrate (S) into contact with an aqueous leaching solution comprising an organic acid chosen from alkylsulfonic, alkylarylsulfonic, arylsulfonic acids, ethylenediamine-N,N?-bis(2-hydroxyphenylacetic acid) or a mixture thereof, and optionally an oxidizing agent, whereby a liquid phase L1 rich in lithium and iron is recovered; ii.—Precipitation of iron in the liquid phase L1 obtained in step i), and recovery of the iron precipitate; iii.—Precipitation of lithium in the L2 liquid phase obtained in step ii) and recovery of the lithium precipitate; and optionally iv.—Recovery of the liquid phase L3 obtained in step iii) and recovery of the organic acid used in step i).

Abstract: The invention notably relates to a computer-implemented method of machine-learning a predictive model configured for predicting a concentration of an element in produced water of a given well of hydrocarbon production in a hydrocarbon reservoir having wells of hydrocarbon production. The method comprises providing a dataset comprising values of one or more geoscience well-wise variables. Each value corresponds to a respective well of hydrocarbon production in the hydrocarbon reservoir other than the given well. Each value that corresponds to a respective well is associated to a respective ground truth value representing a concentration of the element in the respective well. The method further comprises learning the predictive model based on the dataset. This forms an improved solution for predicting a concentration of an element in produced water of a given well of hydrocarbon production in a hydrocarbon reservoir.

Abstract: The invention relates to a modular installation for the treatment of an aqueous stream of produced water from an oil or gas field, said aqueous stream comprising water, suspended solids, residual hydrocarbons, at least one metal to be recovered and a first metal different from the metal to be recovered, the installation comprising: one or more movable metal treatment tanks (1) configured to precipitate the first metal in the aqueous stream; a filtration container (4) comprising a filtration unit (4c) configured to remove at least part of the suspended solids; and a separation container (6) comprising power and fluidic connectors, configured to receive and be connected to a separation unit (6c), the separation unit (6c) being configured to separate the metal to be recovered from the aqueous stream; the one or more movable metal treatment tanks (1), the filtration container (4) and the separation container (6) being fluidically connected, and the filtration container (4) being arranged downstream of the one or

Abstract: The invention notably relates to a method for performing a 3D structural restoration of a geological setting with a computer system, including unfolding one or more geological surfaces of the geological setting. The unfolding comprises for each respective geological surface providing a 3D triangulated surface representing the respective geological surface, and determining a conformal flattening that transforms the 3D triangulated surface into a 2D triangulated surface. The conformal flattening is an iso-topographic mapping which substantially preserves angles. This provides an improved solution of 3D structural restoration of a geological setting.

Abstract: The invention notably relates to a method for performing a 3D structural restoration of a geological setting with a computer system, including unfolding one or more geological surfaces of the geological setting. The unfolding comprises for each respective geological surface providing a 3D triangulated surface representing the respective geological surface, and determining a conformal flattening that transforms the 3D triangulated surface into a 2D triangulated surface. The conformal flattening is an iso-topographic mapping which substantially preserves angles. This provides an improved solution of 3D structural restoration of a geological setting.