A computer-implemented method comprising: obtaining known data describing a subsurface region; estimating an initial state of the subsurface region; predicting data describing a subsequent state of the subsurface region; and outputting a representation of the subsurface region based on the predicted data CHARACTERISED IN THAT: the method is a method for correlating data predicted by a process- or physics-based geologic model to describe a subsurface region with the obtained known data describing the subsurface region by conditioning data predicted by a process-based model of meandering channel/river systems in fluvial, shallow, or deep water environments in the field of hydrocarbon exploration and production; the data is predicted by performing a forward simulation to compute the evolution of a channel by modeling the dynamics of the interplay between channel migration and changing sedimentary environment; and the method includes the steps of: comparing the predicted data with the obtained known data by computing an objective function taking into account whether the predicted data represent a discontinuous event; and determining a sensitivity of the predicted data if the predicted data is not within an acceptable range of the obtained known data, wherein determining the sensitivity comprises computing an adjoint of the objective function; and adjusting the initial state of the subsurface region based on the sensitivity before performing a subsequent iteration of predicting data describing the subsequent state of the subsurface region. obtaining known data describing a subsurface region; estimating an initial state of the subsurface region; predicting data describing a subsequent state of the subsurface region; and outputting a representation of the subsurface region based on the predicted data CHARACTERISED IN THAT: the method is a method for correlating data predicted by a process- or physics-based geologic model to describe a subsurface region with the obtained known data describing the subsurface region by conditioning data predicted by a process-based model of meandering channel/river systems in fluvial, shallow, or deep water environments in the field of hydrocarbon exploration and production; the data is predicted by performing a forward simulation to compute the evolution of a channel by modeling the dynamics of the interplay between channel migration and changing sedimentary environment; and the method includes the steps of: comparing the predicted data with the obtained known data by computing an objective function taking into account whether the predicted data represent a discontinuous event; and determining a sensitivity of the predicted data if the predicted data is not within an acceptable range of the obtained known data, wherein determining the sensitivity comprises computing an adjoint of the objective function; and adjusting the initial state of the subsurface region based on the sensitivity before performing a subsequent iteration of predicting data describing the subsequent state of the subsurface region. the method is a method for correlating data predicted by a process- or physics-based geologic model to describe a subsurface region with the obtained known data describing the subsurface region by conditioning data predicted by a process-based model of meandering channel/river systems in fluvial, shallow, or deep water environments in the field of hydrocarbon exploration and production; the data is predicted by performing a forward simulation to compute the evolution of a channel by modeling the dynamics of the interplay between channel migration and changing sedimentary environment; and the method includes the steps of: comparing the predicted data with the obtained known data by computing an objective function taking into account whether the predicted data represent a discontinuous event; and determining a sensitivity of the predicted data if the predicted data is not within an acceptable range of the obtained known data, wherein determining the sensitivity comprises computing an adjoint of the objective function; and adjusting the initial state of the subsurface region based on the sensitivity before performing a subsequent iteration of predicting data describing the subsequent state of the subsurface region. comparing the predicted data with the obtained known data by computing an objective function taking into account whether the predicted data represent a discontinuous event; and determining a sensitivity of the predicted data if the predicted data is not within an acceptable range of the obtained known data, wherein determining the sensitivity comprises computing an adjoint of the objective function; and adjusting the initial state of the subsurface region based on the sensitivity before performing a subsequent iteration of predicting data describing the subsequent state of the subsurface region.