Method of modelling the evolution of the pH value of a porous medium after injection of an alkaline agent solution into this medium. The alkaline agent is considered as a soda pseudo-constituent of concentration equal to an OH— concentration corresponding to the pH value of the alkaline agent solution injected. An adsorption equation calibrated to experimental data is then used to determine an amount of soda pseudo-constituent adsorbed, from the concentration of the soda pseudo-constituent. Finally, the evolution of the pH value is modelled by modelling the transport of the alkaline agent solution by means of a soda transport simulator, by replacing the soda by the soda pseudo-constituent.

Method of modelling the evolution of the pH value of a porous medium after injection of an alkaline agent solution into this medium. The alkaline agent is considered as a soda pseudo-constituent of concentration equal to an OH— concentration corresponding to the pH value of the alkaline agent solution injected. An adsorption equation calibrated to experimental data is then used to determine an amount of soda pseudo-constituent adsorbed, from the concentration of the soda pseudo-constituent. Finally, the evolution of the pH value is modelled by modelling the transport of the alkaline agent solution by means of a soda transport simulator, by replacing the soda by the soda pseudo-constituent.

Methods are disclosed for monitoring, controlling and optimizing fouling of a two side membrane fouling process. The method for monitoring fouling of a two side membrane fouling process can include determining the process model for the two side membrane fouling process. The parameters of the process model can be grouped based on the interactions thereof between the parameters so as to form one or more groups of parameters. At least one key performance index is estimated in relation to one or more groups of parameters. The fouling of the two side membrane fouling process is monitored correspondingly in relation to at least one key performance index.

Methods are disclosed for monitoring, controlling and optimizing fouling of a two side membrane fouling process. The method for monitoring fouling of a two side membrane fouling process can include determining the process model for the two side membrane fouling process. The parameters of the process model can be grouped based on the interactions thereof between the parameters so as to form one or more groups of parameters. At least one key performance index is estimated in relation to one or more groups of parameters. The fouling of the two side membrane fouling process is monitored correspondingly in relation to at least one key performance index.

Apparatus and associated methods relate to computerized system for predicting the quantity of oil and/or gas production at an oil site, where a prediction curve for oil and/or gas data transitions from a first fitted curve (e.g., a hyperbolic decline curve) to a second fitted curve (e.g., an exponential decline curve) at a transition point, the transition point being determined by progressively/iteratively identifying curvature changes in the first fitted curve over an initial time period by comparing a running list of terminal decline rates (Dmin) with a predetermined curvature threshold, and setting the occurrence of the transition point at the point where the rate of change of the terminal decline rate is less than the predetermined curvature threshold. In an illustrative example, the second fitted curve may use the value of Dmin that minimizes the deviation between successive forecasts.

In reservoir hydrocarbon exploration, fracture characteristics of subsurface reservoir formations are analyzed based on measures obtained about the subsurface formations and rock. Models of subsurface reservoirs are developed with predictions of natural fracture networks within the subject subsurface reservoirs. The mechanical properties of the formation rock in the reservoirs serve as a main controller to model the natural fractures distribution and their properties. The models so formed are important in the location and completion of wells for hydrocarbon exploration and production.

In reservoir hydrocarbon exploration, fracture characteristics of subsurface reservoir formations are analyzed based on measures obtained about the subsurface formations and rock. Models of subsurface reservoirs are developed with predictions of natural fracture networks within the subject subsurface reservoirs. The mechanical properties of the formation rock in the reservoirs serve as a main controller to model the natural fractures distribution and their properties. The models so formed are important in the location and completion of wells for hydrocarbon exploration and production.

A method for optimizing a well production forecast includes inputting into a computer: initial production rate measurements and probability distributions to estimate production forecast model parameters. The computer generates an initial forecast of fluid production rates and total produced fluid volumes using a selected production forecast model. After a selected time, the initial forecast is compared with actual production rate and total produced fluid volume measurements to generate an error measurement. Parameters of the selected production forecast model are adjusted to minimize the error measurement, thereby generating an adjusted production forecast model. The parameter adjustment and error measurement are repeated for a plurality of iterations to generate a plurality of production forecast models each having a determined likelihood of an error measurement. The plurality of production forecast models are displayed with respect to likelihood of error.

A method for optimizing a well production forecast includes inputting into a computer: initial production rate measurements and probability distributions to estimate production forecast model parameters. The computer generates an initial forecast of fluid production rates and total produced fluid volumes using a selected production forecast model. After a selected time, the initial forecast is compared with actual production rate and total produced fluid volume measurements to generate an error measurement. Parameters of the selected production forecast model are adjusted to minimize the error measurement, thereby generating an adjusted production forecast model. The parameter adjustment and error measurement are repeated for a plurality of iterations to generate a plurality of production forecast models each having a determined likelihood of an error measurement. The plurality of production forecast models are displayed with respect to likelihood of error.

A hydraulic fracture design model that simulates the complex physical process of fracture propagation in the earth driven by the injected fluid through a wellbore. An objective in the model is to adhere with the laws of physics governing the surface deformation of the created fracture subjected to the fluid pressure, the fluid flow in the gap formed by the opposing fracture surfaces, the propagation of the fracture front, the transport of the proppant in the fracture carried by the fluid, and the leakoff of the fracturing fluid into the permeable rock. The models used in accordance with methods of the invention are typically based on the assumptions and the mathematical equations for the conventional 2D or P3D models, and further take into account the network of jointed fracture segments. For each fracture segment, the mathematical equations governing the fracture deformation and fluid flow apply. For each time step, the model predicts the incremental growth of the branch tips and the pressure and flow rate distribution in the system by solving the governing equations and satisfying the boundary conditions at the fracture tips, wellbore and connected branch joints. An iterative technique is used to obtain the solution of this highly nonlinear and complex problem.