Abstract: A method of developing a petroleum reservoir from a reservoir model and optimized history matching is disclosed having application for petroleum reservoir characterization. A global objective function measuring the differences between the measured historical data and the simulated historical data is defined according to M parameters. The global objective function is then decomposed into a sum of k local objective functions. Each local objective function measures the differences on a geographic region from mk parameters, selected from among the M parameters, and having a significant impact on the historical data of the region. The region is determined by minimizing this number mk of parameters. The model is then modified by minimizing the global objective function by a gradient method wherein the derivatives of the local objective functions are estimated by means of a parameter perturbation technique.

Abstract: The invention is a method of constructing an image of a petroleum reservoir from dynamic data having application for petroleum reservoir characterization. At least two independent realizations of the reservoir are generated from at least two Gaussian white noises. At least one region is defined within the reservoir and a parameter allowing the shape and the size of this region to be modified is defined. A new realization of the reservoir is then generated from a linear combination of the white noises. The coefficients of this linear combination depend on the parameter allowing the region to be modified. A local objective function measuring, within this region, a difference between dynamic data simulated from the new realization and the measured dynamic data is then calculated. Finally, the image of the reservoir is constructed by iteratively modifying the parameter so as to minimize the local objective function.

Abstract: This method for evaluating fluid flows in a heterogeneous medium, uses a hybrid grid constructed from a CPG type structured grid and from a radial grid. The first stage includes locally deforming a CPG type grid into a non-uniform Cartesian grid. These local grid cell deformations correspond to the change from a “CPG” frame to a “Cartesian” frame defined by the deformation. These deformations are then quantified, by a deformation function ?, and applied to the radial grid so as to shift to the “Cartesian” frame. The second stage includes locally correcting the definition of this deformation function around the radial grid, so that the radial grid, in the “Cartesian” frame, keeps its geometrical characteristics. A hybrid grid is then generated in the “Cartesian” frame from the two grids thus deformed. Finally, this hybrid grid is deformed to return to the “CPG” frame, using the inverse of deformation function ?.

Abstract: Method for optimizing the development of an underground reservoir, wherein a geological model is updated using dynamic data and well tests. A reservoir model is constructed by performing a geological model scale change. Dynamic data are simulated from this reservoir model. Influence zones are identified within the geological model where the well tests induce a pressure variation during well testing. Well tests are then simulated for each influence zone. An objective function measuring the difference between the simulated data and the measured data is calculated. The geological model is then modified so as to reduce to the maximum the objective function using a geostatistical parametrizing technique. Finally, development of the underground reservoir is optimized by evaluating, by means of a flow simulator, the reservoir production for various production schemes. Application: notably oil reservoir development.

Abstract: A method for gradually modifying a geological model representative of an underground reservoir to respect fixed average proportions of lithologic facies. A group of facies is selected and a subgroup of associated facies are selected. A transformation parameter is defined by the ratio between the average proportions of the facies of the association and the selection. Within the context of historical matching, a difference between measured dynamic data values and values calculated by a flow simulator from the geological model is measured. An optimization algorithm is used to obtain therefrom a new value for the transformation parameter that minimizes the difference and the transformation is applied to the lithologic facies of the selection. The modification can be applied to the entire model or to a given zone.

Abstract: A method of developing a petroleum reservoir from a reservoir model and optimized history matching is disclosed having application for petroleum reservoir characterization. A global objective function measuring the differences between the measured historical data and the simulated historical data is defined according to M parameters. The global objective function is then decomposed into a sum of k local objective functions. Each local objective function measures the differences on a geographic region from mk parameters, selected from among the M parameters, and having a significant impact on the historical data of the region. The region is determined by minimizing this number mk of parameters. The model is then modified by minimizing the global objective function by a gradient method wherein the derivatives of the local objective functions are estimated by means of a parameter perturbation technique.

Abstract: Method of constructing an image of a petroleum reservoir from dynamic data Id disclosed having application for petroleum reservoir characterization. At least two independent realizations of the reservoir are generated from at least two Gaussian white noises. At least one region is defined within the reservoir and a parameter allowing the shape and the size of this region to be modified is defined. A new realization of the reservoir is then generated from a linear combination of the white noises. The coefficients of this linear combination depend on the parameter allowing the region to be modified. A local objective function measuring, within this region, a difference between dynamic data simulated from the new realization and the measured dynamic data is then calculated. Finally, the image of the reservoir is constructed by iteratively modifying the parameter so as to minimize the local objective function.

Abstract: Method for evaluating fluid flows in a heterogeneous medium, by means of a hybrid grid constructed from a CPG type structured grid and from a radial grid. The first stage consists in locally deforming the CPG type grid into a non-uniform Cartesian grid. These local grid cell deformations correspond to the change from a reference frame referred to as “CPG” frame to a reference frame referred to as “Cartesian” frame defined by the deformation. These deformations are then quantified, by a deformation function ?, and applied to the radial grid so as to shift to the “Cartesian” frame. The second stage consists in locally correcting the definition of this deformation function around the radial grid, so that the radial grid, in the “Cartesian” frame, keeps its geometrical characteristics necessary for generation of a transition grid. A hybrid grid is then generated in the “Cartesian” frame from the two grids thus deformed.

Abstract: A method of reconstructing a stochastic realization, continuous or discrete, resulting from a random function representing a numerical model, can be representative of a porous heterogeneous medium such as an underground reservoir. It is based on identification, for a given realization, of a random function and of a set of random numbers allowing, from a given geostatistical simulator, to reconstruct the reference realization. The reconstruction techniques proposed are either general or specific to a type of geostatistical simulator. They concern the sphere of optimization, relaxation, filtering and sequential approaches. The reconstruction method allows to estimate a set of random numbers for regenerating the reference realization, this reference realization can then be locally or globally modified, by gradual deformation, so as to better reproduce newly acquired dynamic data (production data for example). The method is applicable notably to oil reservoir development for example.

Abstract: Method for optimizing the development of an underground reservoir, wherein a geological model is updated using dynamic data and well tests. A reservoir model is constructed by performing a geological model scale change. Dynamic data are simulated from this reservoir model. Influence zones are identified within the geological model where the well tests induce a pressure variation during well testing. Well tests are then simulated for each influence zone. An objective function measuring the difference between the simulated data and the measured data is calculated. The geological model is then modified so as to reduce to the maximum the objective function using a geostatistical parametrizing technique. Finally, development of the underground reservoir is optimized by evaluating, by means of a flow simulator, the reservoir production for various production schemes. Application: notably oil reservoir development.

Abstract: Method for gradually modifying a geological model representative of an underground reservoir so as to respect fixed average proportions of these lithologic facies. A group of facies referred to as selection and a subgroup of facies referred to as association are selected. A transformation parameter is defined by the ratio between the average proportions of the facies of the association and those of the selection. Within the context of history matching, a difference between measured dynamic data values and values calculated by means of a flow simulator from the geological model is measured. An optimization algorithm is used to deduce therefrom a new value for the transformation parameter that minimizes this difference and this transformation is applied to the lithologic facies of the selection. The modification can be applied to the entire model or to a given zone.

Abstract: A method for more rapidly forming a stochastic model of Gaussian or Gaussian-related type, representative of a porous heterogeneous medium such as an underground reservoir, constrained by data characteristic of the displacement of fluids and punctual observations, these observations being uncertain and characterized by a probability law. The method transforms static information, given in form of probability laws, into Gaussian punctual pseudo-data which has the advantage of being compatible with a gradual deformation method. An objective function J measuring the difference between the dynamic data (production data for example) and the corresponding responses simulated for the reservoir model considered may be minimized.

Abstract: Method of reconstructing a stochastic realization, continuous or discrete, resulting from a random function representing a numerical model, that can be representative of a porous heterogeneous medium such as an underground reservoir. It is based on identification, for a given realization, of a random function and of a set of random numbers allowing, from a given geostatistical simulator, to reconstruct the reference realization. The reconstruction techniques proposed are either general or specific to a type of geostatistical simulator. They concern the sphere of optimization, relaxation, filtering and sequential approaches. The reconstruction method allows to estimate a set of random numbers for regenerating the reference realization, this reference realization can then be locally or globally modified, by gradual deformation, so as to better reproduce newly acquired dynamic data (production data for example). Application: notably oil reservoir development for example.

Abstract: Method for more rapidly forming a stochastic model of Gaussian or Gaussian-related type, representative of a porous heterogeneous medium such as an underground reservoir, constrained by data characteristic of the displacement of fluids and punctual observations, these observations being uncertain and characterized by a probability law. It is based on a method for transforming static information, given in form of probability laws, into Gaussian punctual pseudo-data. This transformation technique has the advantage of being fully compatible with a gradual deformation method. In fact, it makes it possible to minimize an objective function J measuring the difference between the dynamic data (production data for example) and the corresponding responses simulated for the reservoir model considered. Minimization is carried out by combining realizations of a stochastic model on the one hand for the reservoir model and, on the other hand, for the Gaussian pseudo-data representative of the static information.

Abstract: The invention is a method for direct updating, by dynamic production data, of a fine geologic model representative of the distribution, in a reservoir, of a physical quantity characteristic of the subsoil structure. The method couples inversion and upscaling techniques allowing optimization of petrophysical parameters of a rougher simulation model resulting from the fine geologic model. Direct parameterization of the fine geologic model is performed followed by upscaling only as a means of obtaining rapidly an approximation of simulation results and of derivatives thereof in relation to the parameterization of the fine geologic model. The model has applications for determination of a development scheme such as optimizing the production of a hydrocarbon reservoir.

Abstract: Method for gradually deforming, totally or locally, a Gaussian or similar type stochastic model of a heterogeneous medium such as an underground zone, constrained by a series of parameters relative to the structure of the medium. The method comprises drawing a number p, at least equal to two, of independent realizations of at least part of the selected medium model from all the possible realizations, and linear combination of these p realizations with p coefficients such that the sum of their squares is equal to 1. This linear combination constitutes a new realization of the stochastic model and it gradually deforms when the p coefficients are gradually modified. More generally, the method can comprise several iterative gradual deformation stages, with combination at each stage of a composite realization obtained at the previous stage with q new independent realizations drawn from all the realizations.

Abstract: Method intended for direct updating, by dynamic production data, of a fine geologic model representative of the distribution, in a reservoir, of a physical quantity characteristic of the subsoil structure.

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.