Abstract: The present disclosure provides for generating multiphase flow properties of porous media based on one or more input parameters. For instance, the multiphase flow properties may be a capillary pressure-saturation relationship for the porous media. The one or more input parameters include an interfacial tension along an interface between a wetting fluid and a non-wetting fluid, a contact angle between the interface and a pore wall of the porous media, and a pore throat size. The pore throat size is based on subparameters including a saturation of the wetting fluid, a saturation of the non-wetting fluid, a porosity of the porous media, and an orientation angle between a representative pore body size and a representative pore throat size.

Abstract: The present disclosure provides for generating multiphase flow properties of porous media based on one or more input parameters. For instance, the multiphase flow properties may be a capillary pressure-saturation relationship for the porous media. The one or more input parameters include an interfacial tension along an interface between a wetting fluid and a non-wetting fluid, a contact angle between the interface and a pore wall of the porous media, and a pore throat size. The pore throat size is based on subparameters including a saturation of the wetting fluid, a saturation of the non-wetting fluid, a porosity of the porous media, and an orientation angle between a representative pore body size and a representative pore throat size.

Abstract: A method for dynamically determining at least one physico-chemical property and the composition of a multiphase fluid flow in a porous medium: including the building of a geological model of said the porous medium and the discretization of said model into elementary meshes, the determination (40) of an initial state of each mesh, including determination of the composition of said mesh, and the determination (42) of a time-dependent change, in at least one mesh and in at least one predetermined time interval, of at least one physico-chemical property and of the composition of phases of said fluid in each component, including at least one step (52, 54) for determining an equilibrium within said mesh, comprising the application of at least the one that neuron network for determining characteristics at equilibrium of said fluid from its characteristics out of equilibrium.

Abstract: Method for forming, by means of an inversion technique, a model of an underground zone, constrained by static data: data obtained by seismic exploration or measured in situ (logs), and by dynamic data: production measurement, well testing, etc. From an a priori selected meshed geologic model and from relations between parameters or physical quantities characteristic of the medium: acoustic impedance and cabsolute permeability for example, a simultaneous inversion of the two parameters is performed by minimizing a global cost function, which has the effect of considerably decreasing the number of possible solutions and of improving characterization of the underground zone. The method can be used notably for modelling hydrocarbon reservoirs, of zones likely to be used as gas, waste storage places, etc.

Abstract: A method for automatic modelling of the stratigraphic structure of an underground zone with fast adjustment of the parameters of the model with observed or measured data is disclosed.

Abstract: A model for simulating the behaviour of an underground reservoir is defined from initial geologic knowledge and available data. It allows production forecasts to be achieved from parameters representative of the initial data. The method notably consists in defining one or several possible production evolution scenarios by creating, for each of these scenarios, new production data corresponding to hypotheses on the future states of the reservoir. For each scenario considered, it is checked whether it is possible to adjust the available parameters of the simulation model, considering the constraints of the initial geologic model, so that the simulation model reproduces both the production data measured and the data added. The method can be used to quantify uncertainties on the production forecasts by seeking the min/max extremes of the future production values. Application : production of hydrocarbons for example.